News

IEEE COMPSAC 2023

COMPSAC is the IEEE Computer Society Signature Conference on Computers, Software, and Applications. The theme of COMPSAC 2023 is "Resilient Computing and Computing for Resilience in a Sustainable Cyber-Physical World."

The 47th IEEE Annual Computers, Software, and Applications Conference (COMPSAC) is held in-person in Torino (Turin), Italy on June 27-29. It is an in-person conference that allows absentee authors to provide us with their papers plus a video presentation of those papers. Authors who are not able to attend in-person will have their video presentations made available for dissemination through IEEE. All the in-person authors have also provided a video presentation of their papers. There are no live-streamed sessions.

IEEE COMPSAC 2023
June 26–30, 2023
Università di Torino
Torino, Italy | CET (UTC-2)

The 8th IEEE International Workshop on Distributed Big Data Management (DBDM 2023) and The 5th IEEE International Workshop on Deep Analysis of Data-Driven Applications (DADA 2023):
Thursday, June 29 1:30 PM – 3:00 PM CEST (6:30 AM – 8:00 AM CDT)
Room E2

Virtual On-Demand Presentations:
- (DBDM 2023) Evolution of Big Data Models from Hierarchical Models to Knowledge Graphs (3050)
Anifat Olawoyin, Carson Leung, and Alfredo Cuzzocrea

- (DBDM 2023) Privacy Preservation of Big Spatio-Temporal Co-occurrence Data (4208)
(Privacy preserving record linkage with spatio-temporal hierarchy)
Anifat Olawoyin, Carson Leung and Alfredo Cuzzocrea

IDEAS 2023

The 27th International Database Engineered Applications Symposium (IDEAS 2023), ranked B (CORE), in an in-person conference held in Heraklion, Crete, Greece on 05-07 May 2023. Remote/online participation (on Zoom) is possible for those having travel restrictions.

IEEE ICIT 2023

IEEE ICIT is one of the flagship conferences of the IEEE Industrial Electronics Society, devoted to the dissemination of new ideas, research and works in progress within the fields of intelligent and computer control systems, robotics, factory communications and automation, flexible manufacturing, data acquisition and signal processing, vision systems, and power electronics.

The 24th IEEE International Conference on Industrial Technology is a hybrid conference (in-person and virtual on Zoom) held April 04-06, 2023 in Oralndo, FL, USA.

AINA 2023

37th International Conference on Advanced Information Networking and Applications (AINA-2023) was scheduled to be held March 29-31, 2023, in Juiz de Fora, MG, Brazil. Instead, it takes place online in a synchronous mode, with presentations and Q&A on Zoom. Day 1 (March 29) runs 09h30-15h30 AMT/EDT (UTC-4) = 14h30-21h30 CEST (UTC+2), i.e., 08h30-14h30 CDT (UTC-5). Day 2 (March 30) runs 06h-15h CEST = 13h-22h JST (UTC+9), i.e., 23h (-1d)-08h CDT.

Research.com

In 2023 Edition of our Ranking of Top 1000 Scientists in the field of Computer Science (9th edition of Research.com ranking of the best scientists in the arena of Computer Science), Carson Kai-Sang Leung is ranked #245 in Canada and #5582 in the world among Top Scientists for 2023.

Best Computer Science scientists at University of Manitoba on the ranking list are:

Ekram Hossain (World #260, Canada #9, D-Index 96; 35396 citations, 597 publications)
James F. Peters (World #4859, Canada #218, D-Index 44; 6529 citations, 410 publications)
Carson Kai-Sang Leung (World #5582, Canada #245, D-Index 41; 6009 citations, 288 publications)
Pourang Irani (World #5873, Canada #257, D-Index 40; 5589 citations, 218 publications)
Yang Wang (World #7995, Canada #336, D-Index 34; 6286 citations, 119 publications)
Attahiru Sule Alfa (World #10232, Canada #415, D-Index 30; 3868 citations, 252 publications)

ACPMB Saturday Seminar Series for Youth

Dr. Carson K. Leung is invited to give a seminar in the Saturday Seminar Series for Youth, hosted by ACPMB, on Saturday, February 18. It features Dr. Carson Leung, Professor of Computer Science, who presents "Knowledge discovery from big data".

CRA-ASM 2023

Dr. Carson K. Leung is invited to co-present an interactive workshop on the topic of artificial intelligence at Canadian Rheumatology Association (CRA) & Arthritis Health Professions Association (AHPA) Annual Scientific Meeting 2023 in Québec City, Québec on February 08-11, 2023.

Workshop 2F: Artificial Intelligence in Practice: Pattern Mining of Healthcare Data for Complex Chronic Conditions (IN PERSON ONLY)

Learning objectives:

Through a case study of our pilot project, we will demonstrate the novel application of pattern mining in health administrative data to discover healthcare behaviours leading up to the diagnosis of a rheumatic disease. We will discuss considerations when applying machine learning to such an environment, share the challenges encountered and steps taken to overcome them.

At the end of this session, participants will be able to:

Describe the types of healthcare data and research questions for which pattern mining techniques can be used.
Identify the steps in applying pattern mining to healthcare data to produce reliable and valid research results, using a case example of juvenile arthritis
Describe the potential benefits of pattern mining techniques for exploring both expected and unexpected patterns of healthcare contacts that lead to the diagnosis of complex chronic conditions

CanMEDS roles

Medical Expert
Communicator
Collaborator
Leader
Health Advocate
Scholar
Professional

Session evaluation:

Learning objectives have been set for this session, do you feel that they have been met?
Content was scientifically valid and balanced.
Session was free from indicators of undue industry bias.
Session was free from indicators of undue personal/other bias.
For this session, new information I acquired includes:
For this session, potential impact on my practice or changes I will make include:

Dr. Lily Lim, Paediatric rheumatologist, clinical epidemiologist, statistics and machine learning enthusiast

Dr. Carson Leung, Professor, Computer Science, University of Manitoba, Canada

Dr. Lisa Lix, Professor of Biostatistics and Canada Research Chair, University of Manitoba, Winnipeg

Olawoyin's & Pazdor's Teaching

1. Anifat Olawoyin, a PhD student in our lab, teaches:
  - COMP 3380 (Database concepts and usage) in Winter 2023 on every Tuesday and Thursday at 10:00am-11:15am in St. John's College 118 from January 10 to April 11, 2023.
  - By the end of Winter 2023, Olawoyin has taught a total of 3 sections of two distinct courses at two undergraduate year-levels (COMP 1012 in Fall 2022; COMP 3380 in Winter 2022/2023).
2. Adam G. Pazdor, a PhD student in our lab, teaches:
  - COMP 4380 A02 (Database implementation) in Winter 2023 on every Tuesday and Thursday at 2:30pm-3:45pm in University College 244 from January 10 to April 11, 2023.
  - COMP 4380 A01 in Winter 2023 on every Tuesday and Thursday at 4:00pm-5:15pm in University College 244 from January 10 to April 11, 2023.
  - COMP 2080 (Analysis of algorithms) in Summer 2023 on every Monday to Thursday at 12:30pm-1:45pm in Armes 200 from July 03 to August 11, 2023.

By the end of Summer 2023, Pazdor has taught a total of 24 sections of seven distinct courses at all four undergraduate year-levels (COMP 1012 in Summer 2016, Winter/Summer/Fall 2017, Fall 2018 & Winter 2019, Summer 2021/2022; COMP 1020 in Winter 2020; COMP 2080 in Summer 2023; COMP 2130 in Summer 2018; COMP 3380 in Fall 2016/2017/2019/2020/2021; COMP 4380 in Winter 2018/2020/2021-2023; COMP 4710 in Fall 2022).

USRA 2022

Several lab members won undergraduate student research awards:

- Each of the following students won a Faculty of Science Undergraduate Student Research Award (USRA) to conduct a full-time 16-week research project in the area of data mining under the academic supervision of Dr. Carson K. Leung:
  - - Mr. Denys Popov, who is enrolled in B.Sc.(Maj.) in COMP and minor in CHEM

His fellow students also won the awards: Bikramjit Singh Dhaliwal won a FoS USRA, and Junyi (Andre) Lu won a SSA/FoS USRA.

- Each of the following students won an UofM Vice-President (Research and International) Undergraduate Research Award (URA) to conduct a full-time 16-week research project under the academic supervision of Dr. Carson K. Leung. Among ~25,000 undergraduate students across the campus and ~400 applicants, they were two of 170 UM VP(RI)/UMSU URA winners:

- - Mr. Junyi (Andre) Lu, who is enrolled in B.Sc.(Maj.) and focuses on the design of a data science solution for big data mining;
  - Mr. Sanskar Raval, who is enrolled in B.C.Sc.(Hons.) and focuses on the design of human-centered explanatory data mining solution.
  - Second-year undergraduate student Mr. Thanh Huy (Daniel) Mai, who is enrolled in B.C.Sc.(Hons.) program with major in CS and minor in Statistics.
  - Fourth-year undergraduate student Ms. Yan Wen, who is enrolled in B.Sc.(Maj.) program with double major in CS and Chemistry, and minor in Math. She won this award last summer (2020) and conducted research in our lab.

- Mr. Bikramjit Singh Dhaliwal, who is enrolled in B.C.Sc.(Hons.) program, won an NSERC USRA to conduct a full-time 16-week research project on "A data science solution for big data mining and analytics" under the academic supervision of Dr. Carson K. Leung.
- Each of the following students was selected as a winner of a MITACS Globalink Internship awards:
  - - Third-year undergraduate student, Ms. Canran Li (李璨然), who is enrolled in a B.Eng. program in e-commerce and law from Beijing University of Posts and Telecommunications (BUPT) (北京邮电大学), China, was selected for the project on "Big data science and data analytics for useful information". She participated in the Oxford Global Exchanges at Queen Mary University of London, UK.
    - Third-year undergraduate student, Mr. Zhihan Xu (徐之涵), who is enrolled in a B.Eng. program from College of Software at Jilin University (吉林大学), China, was selected for the project on "Social network analysis and mining". He participated a virtual internship for an company located in Waterloo, ON, Canada.
    - Third-year undergraduate student, Mr. Krunal Murlidhar Kumbhare, who is enrolled in a B.Tech. program in Computer Science and Engineering from Vellore Institute of Technology (VIT) Chennai, India, was selected for the project on "Data visualization and visual analytics".

IEEE BigData 2022

IEEE BigDataSE 2022

IEEE BIBM 2022

The IEEE International Conference on Bioinformatics and Biomedicine (BIBM) has established itself as the premier research conference in bioinformatics and biomedicine.IEEE BIBM 2022 is held 06-08 December 2022. It was planned as an in-person conference in two sites: Las Vegas, NV, USA, and Changsha, Hunan (湖南省长沙市), China. Participants can attend the Las Vegas sessions (Dec 06-07, mostly 09h-21h PST (UTC-8) = 11h-23h CST (UTC-6)) in-person as well as access all the workshops and keynote sessions online, plus all the video recordings submitted by the paper authors on Zoom via RD Mobile. The Changsha program is moved from in-person to online/virtual (Dec 07-08, mostly 09h-18h30 China Standard Time (UTC+8) = 19h(-1d)-04h30 Central Standard Time (UTC-6)) on Tencent meeting.

BigDAS 2022

Dr. Carson K. Leung is a Program Chair of the 10th International Conference on Big Data Applications and Services (BigDAS) is held November 24-26, 2022 in Jeju Island (濟州島), South Korea. He gives a Welcoming Speech at the Opening Ceremony on (Thu) Nov 24 via Zoom.

IEEE/WIC/ACM WI-IAT 2022

The 21st IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2022) is held 17-20 November 2022 (mostly 08h45-20h30 EST (UTC-5) = 07h45-19h30 CST (UTC-6)) in Niagara Falls, ON, Canada as a hybrid conference with both online (on Zoom and 揣摩研习社) and offline modes.

IEEE/ACM ASONAM 2022

The 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Minng (ASONAM) is held 10-13 November 2022 (mostly 09h-22h TRT (UTC+3) = 00h-13h CST (UTC-6)) in a hybrid mode, i.e., in-person in Istanbul, Turkey, and virtual on Zoom.

ISCB-LA SolBio BioNetMX 2022

ISCB-Latin America SoIBio BioNetMX Conference on Bioinformatics 2022, organized by the Bioinformatics Network Mexico (BioNetMX) together with the Iberoamerican Society of Bioinformatics (SoIBio) and the International Society for Computational Biology (ISCB), is held November 03-07, 2022 in Querétaro, Mexico (mostly 08h45-19h CDT (UTC-5)/CST (UTC-6)) as a dual channel distribution conference, offering both in-person and virtual attendance.

Virtual Platform Only

Bioinformatics of Microbes and Microbiomes

Virtual: A self-knowledge distillation-driven CNN-LSTM model for predicting disease outcomes using longitudinal microbiome data

COSI: la

Daryl Fung, University of Manitoba, Canada
Xu Li, University of Toronto, Canada
Carson Leung, University of Manitoba, Canada
Pingzhao Hu, Western University, Canada

Presentation Overview:
Human gut microbiome is complex and highly dynamic in nature. Dynamic patterns of the gut microbiome can capture more information than single point inference of the gut microbiome as it contains the temporal changes information of the gut microbiome. However, dynamic information of the human gut microbiome can be hard to be captured due to the complexity of obtaining the longitudinal data with large volume of missing values that in conjunction with heterogeneity may provide a challenge for the data analysis. We propose using an efficient hybrid deep learning architecture CNN-LSTM (convolutional neural network - Long Short-Term Memory), which is combined with self-knowledge distillation to create high accurate models to analyse the longitudinal gut microbiome to predict disease outcomes. Using our proposed models, we analysed the data sets from PROTECT (Predicting Response to Standardized Pediatric Colitis Therapy) study and DIABIMMUNE study. We showed the significant improvement in the area under the receiver operating characteristic curve (ROC-AUC) scores, achieving 0.889 and 0.798 on PROTECT study and DIABIMMUNE study respectively, compared to state-of-the-art temporal deep learning models. Our findings provide an effect artificial intelligence-based tool to predict disease outcomes using longitudinal gut microbiome profiles from collected patients.

IEEE HealthCom 2022

IEEE International Conference on E-health Networking, Application & Services (HealthCom) 2022 is held 17-19 October 2022 in Genoa, Italy (mostly 09h-22h30 CEST (UTC+2) = 02h-15h30 CDT (UTC-5)). In case authors cannot attend the event physically due to health, budget or safety limitations, it provides the chance to present papers remotely on Zoom with slides and videos on Duetone.

IEEE IEMCON 2022

Dr. Carson K. Leung is a keynote speaker for the 2022 13th IEEEAnnual Information Technology, Electronics and Mobile Communication Conference (IEMCON 2022). It was scheduled to be held in Vancouver, BC, Canada on 12-15 October 2022. Due to the COVID-19 pandemic, it is held virtually to mantain continuity.

https://ieee-iemcon.org/research-talk/

Carson K. Leung
(Professor, University of Manitoba)

Bio: Carson K. Leung obtained his BSc(Hons), MSc and PhD all from the University of British Columbia (UBC), Vancouver, Canada. He is currently a Professor of Computer Science at the University of Manitoba, Canada. He has contributed more than 350 refereed publications on the topics of big data, bioinformatics, computational intelligence, cognitive computing, data analytics, data mining, data science, fuzzy systems, health informatics, information technology, machine learning, social network analysis, and visual analytics. He received Best Paper awards in IEEE DataCom 2021, IEEE SmartData 2021, IEEE BigComp 2022, and IEEE IRI 2022. He has also served on the Organizing Committee of the ACM CIKM, ACM SIGMOD, IEEE DSAA, IEEE ICDM, and other conferences. He is a Senior Member of the ACM and the IEEE; he is also an IEEE Computer Society Distinguished Contributor.

Title for Talk: Big data analytics on COVID-19 epidemiological data

Abstract: In the current era of big data, high volume of big data can be generated and collected from a wide variety of rich data sources at a rapid rate. Embedded in these big data are useful information and valuable knowledge. Examples include healthcare and epidemiological data such as data related to patients who suffered from viral diseases like the coronavirus disease 2019 (COVID-19). Knowledge discovered from these epidemiological data via data science helps researchers, epidemiologists, and policy makers to get a better understanding of the disease, which may inspire them to come up ways to detect, control and combat the disease. This talk presents big data analytics solutions for analyzing COVID-19 epidemiological data. The solutions help users to get a better understanding of information about COVID-19 cases. Evaluation on real-life COVID-19 data across Canadian provinces and territories show the benefits of big data analytics in discovering useful knowledge from COVID-19 epidemiological data. It also showcases the usefulness of information technology (e.g., data science, data mining, and machine learning techniques) to the healthcare sector.

IEEE/ACM/ASA/CCF DSAA 2022

Dr. Carson K. Leung serves as a JDSA Journal Track Chair for the Ninth IEEE International Conference on Data Science and Advanced Analytics (DSAA), which was scheduled to be held October 13-16, 2022 in Shenzhen, China. Due to COVID-19, it is held online (09h-17h10 China Standard Time (UTC+9) = 20h(-1d)-04h10 Central Daylight saving Time (UTC-5)) with presentation choices like (1) present the contribution live and have the recorded video as a backup (submitted via CMT) and (2) play back the recorded video and live Q&A on Zoom.

IEEE CyberSciTech 2022

Dr. Carson K. Leung serves as the General Chair for the Eighth IEEE International Conference on Cloud and Big Data Computing (CBDCom 2022). It is held, in conjunction with IEEE PICom and DASC, as part of CyberSciTech 2021, on September 12-15, 2021, in Calabria, Italy, as a physcial conference (mostly 08h30-20h CEST (UTC+2).

NiBiS & INCoS 2022

The 25th International Conference on Network-Based Information Systems (NBiS-2022) and the 14th International Conference on Intelligent Networking and Collaborative Systems (INCoS-2022) were both scheduled to be held September 07-09 at Kwansei Gakuin University, Sanda-shi, Hyōgo Prefecture (兵庫県三田市), Japan. Because of COVID-19 situation, both conference are held online (mostly 11h-20h JST (UTC+9), i.e., 21h(-1d)-06h CDT (UTC-5)) in a synchronous mode, with live presentations and Q&A on Zoom.

Dr. Carson K. Leung gave a keynote speech at both NBiS 2022 and INCoS 2022:

Keynote II

Prof. Carson K. Leung, University of Manitoba, Canada

Title: Big data analytics on COVID-19 epidemiological data

In the current era of big data, high volume of big data can be generated and collected from a wide variety of rich data sources at a rapid rate. Embedded in these big data are useful information and valuable knowledge. Examples include healthcare and epidemiological data such as data related to patients who suffered from viral diseases like the coronavirus disease 2019 (COVID-19). Knowledge discovered from these epidemiological data via data science helps researchers, epidemiologists, and policy makers to get a better understanding of the disease, which may inspire them to come up ways to detect, control and combat the disease. This talk presents big data analytics solutions for analyzing COVID-19 epidemiological data. The solutions help users to get a better understanding of information about COVID-19 cases. Evaluation on real-life COVID-19 data across Canadian provinces show the benefits of big data analytics in discovering useful knowledge from COVID-19 epidemiological data.

Biography

Prof. Carson Leung obtained his BSc(Hons), MSc and PhD all from the University of British Columbia, Canada. He is currently a Professor of Computer Science at the University of Manitoba, Canada. He has contributed more than 300 refereed publications on the topics of big data, bioinformatics, computational intelligence, cognitive computing, data analytics, data mining, data science, fuzzy systems, health informatics, machine learning, social network analysis, and visual analytics. He received Best Paper awards in IEEE DataCom 2021, IEEE SmartData 2021, and IEEE BigComp 2022. He has also served on the Organizing Committee of the ACM CIKM, ACM SIGMOD, IEEE DSAA, IEEE ICDM, and other conferences. He is a Senior Member of the ACM and the IEEE; he is also an IEEE Computer Society Distinguished Contributor.

DaWaK 2022

24th International Conference on Big Data Analytics and Knowledge Discovery (DaWaK 2022) is held, in conjunction with 33rd International Conference on Database and Expert Systems Applications (DEXA 2022), in Vienna, Austria, on August 22-24 (mostly 08h-21h CEST (UTC+2), i.e., 01h-14h CDT (UTC-5)) at Vienna University of Economics and Business (Wirtschaftsuniversität (WU) Wien), with in-person and online participants. For those who are unable to attend the conference in person, online presentations are given in a synchronous mode, with live presentation and Q&A on Zoom.

IDEAS 2022

26th International Database Engineered Applications Symposium (IDEAS) is held in Budapest, Hungary, on August 22-24 (mostly 09h-17h10 CEST (UTC+2), i.e., 02h-10h10 CDT (UTC-5)) in Eötvös Loránd University (Eötvös Loránd Tudományegyetem (ELTE)).

IEEE Cybermatics 2022

2022 IEEE Cybermatics Congress, which consists of five conferences (IEEE Blockchain 2022, IEEE CPSCom 2022, IEEE GreenCom 2022, IEEE iThings 2022, and IEEE SmartData 2022) is held in Espoo, Finland, on August 22-25 (mostly 08h30-22h EEST (UTC+3), i.e., 00h30-14h CDT (UTC-5)) in a hybrid way. There are onsite presentation, online presentation (on Zoom), and hybrid sessions.

Dr. Carson K. Leung is on the Steering Committee of IEEE SmartData 2022.

IRI 2022

IEEE 23rd International Conference on Information Reuse and Integration for Data Science (IRI 2022) took place virtually on August 09-11 (mostly 09h-15h10 PDT (UTC-7), i.e., 11h-17h10 CDT (UTC-5)) a synchronous mode, with live presentation and Q&A on Zoom.

https://homepages.uc.edu/~niunn/IRI22/
Best paper (8/12/2022)

Congratulations to Carson Leung, Joshua Thomas, and Matthew Kwiatkowski on receiving this year's Best Paper Award for their paper: "A Multi-Dimensional Analysis of Traffic Incident Data for Disaster Management in Smart".

DIST & DMBDA 2022

Dr. Carson K. Leung is a Conference Chair of both the Fifth International Conference on Data Science and Information Technology (DSIT 2022) and the Fifth International Conference on Data Mining and Big Data Analytics (DMBDA 2022) held July 22-24 (mostly 09h-19h China Standard Time (UTC+8), i.e., 20h(-1d)-06h Central Daylight saving Time (UTC-5)) in Shanghai (上海), China. Proceedings are published by the ACM Press.

IEEE CBMS 2022

IEEE 35th International Symposum on Computer Based Medical Systems (CBMS) was scheduled to be held July 21-23 in Shenzhen (深圳), China. Due to COVID-19, it is held online (mostly 09h30-18h15 China Standard Time (UTC+8), i.e., 20h30-05h15 CDT (UTC-5)) in a synchronous mode, with pre-recorded videos and live Q&A on Zoom.

IV 2022

26th International Conference on Information Visualisation (IV 2022) is held July 19-22 (mostly 09h-22h30 CEST (UTC+2), i.e., 09h15-16h CDT (UTC-5)) in Vienna University of Technology (Technische Universität Wien (TU Wien)), Austria, in a hybrid mode. Due to COVID-19 related restrictions to travel, it is planned in a physical venue and face-to-face presentation, but accomodates online presentation or recorded video delivery. Online presentation is delivered in a synchronous mode, with live presentations Q&A on Zoom. Prerecorded video presentation on ConfTool is for backup.

IEEE WCCI 2022

IEEE World Congress on Computational Intelligence (WCCI) is the world's largest technical event on computational intelligence, featuring the three flagship conferences of the IEEE Computational Intelligence Society (CIS) under one roof: The 2022 International Joint Conference on Neural Networks (IJCNN 2022), 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2022), and 2022 IEEE Congress on Evolutionary Computation (IEEE CEC 2022). It is held July 18-23 in Centro Congressi, Padua (Padova), Italy, in-person (mostly 08h45-23h CEST (UTC+2), i.e., 01h45-16h CDT (UTC-5)), and provided videos for remote presentations on Whova (esp. for authors coming from China or Chinese authors living abroad that would need to enter China to renew their visa, since they would be subject to a 14-day quarantene).

https://whova.com/portal/webapp/ccec1_202106/Agenda/2489149

Transportation Analytics with Fuzzy Logic and Regression
Tue. Jul 19, 2022, 10:20 AM - 10:40 AM CEST (3:20 AM - 3:40 AM CDT), Mantegna SA1

Speaker
LEUNG Carson / PAZDOR Adam

SPEAKING AT
Transportation Analytics with Fuzzy Logic and Regression: July 19, 2022, 3:20 AM - 3:40 AM
A fuzzy-logic based multi-dimensional analysis of traffic incident data: July 19, 2022, 3:40 AM - 4:00 AM
A Rough Set System for Mining from Streaming Data: July 21, 2022, 2:05 AM - 2:25 AM

AFFILIATION: University of Manitoba, Computer scientist

EDUCATION: The University of British Columbia

SOCIAL ACCOUNT LINKS: Linkedin

PERSONAL WEBPAGES: http://www.cs.umanitoba.ca/~kleung/

OTHER WEBPAGES:
http://www.cs.umanitoba.ca/~kleung/trtech/
https://scholar.google.com/citations?user=NJaW9s0AAAAJ&hl=en

Authors: Carson K. Leung (University of Manitoba)*; Jason Tran (University of Manitoba); Tanisha Turner (University of Manitoba); Tommy Wu (University of Manitoba); Nurida Karimbaeva (University of Manitoba); Juhee Kim (University of Manitoba); Alfredo Cuzzocrea (Universitá della Calabria)

https://whova.com/portal/webapp/ccec1_202106/Agenda/2489150

A fuzzy-logic based multi-dimensional analysis of traffic incident data
Tue. Jul 19, 2022, 10:40 AM - 11:00 AM CEST (3:40 AM - 4:00 AM CDT), Mantegna SA1

https://whova.com/portal/webapp/ccec1_202106/Agenda/2489385

A Rough Set System for Mining from Streaming Data
Thu. Jul 21, 2022, 9:05 AM - 9:25 AM CEST (2:05 AM - 2:25 AM CDT), Mantegna SA1

Authors: Carson K. Leung (University of Manitoba)*; Yidong Wei (University of Manitoba); Cheng Li (University of Manitoba)

ICEME 2022

Dr. Carson K. Leung is a (Technical) Program Chair of the 13th International Conference on E-business, Management and Economics (ICEME 2022) (第13届电子商务, 管理与经济国际会) held July 16-18 (mostly 09h-20h China Standard Time (UTC+8), i.e., 20h(-1d)-09h Central Daylight saving Time (UTC-5)) in Beijing (北京), China. Proceedings are published by the ACM Press.

ICCSA 2022

The 22nd International Conference on Computational Science and Its Applications (ICCSA 2022) is held July 04-07, 2002 (running mostly 08h30-20h30 CEST (UTC+2), i.e., 01h30-13h30 CDT (UTC-5)) at University of Malaga, Malaga, Spain, in a hybrid mode (with virtual and in-presence modes). Presenters join Jitsi, and audience watches YouTube live stream.

IEEE COMPSAC 2022

IEEE Annual Computers, Software, and Applications Conference (COMPSAC) was designated the IEEE Computer Society signature conference on computers, software and applications in 2006. As its 46th anniversary conference, COMPSAC 2022 was scheduled to be held in Torino, Italy. Due to COVID-19, it is completely virtual only June 27-July 01 (running mostly 08h-09h CEST (UTC+2), i.e., 01h-02h CDT (UTC-5)) in an asynchronous mode, with videos of all sessions for asynchronous watching, on RD Mobile. The theme of COMPSAC 2021 is "computers, software & applications in an uncertain world".

https://events.rdmobile.com/Sessions/Details/1382232Predictive Analytics for Supporting Environmental Sustainability and Disaster ManagementMonday, June 27 9:00 AM – 10:00 AM CEST (Monday, June 27 2:00 AM – 3:00 AM CDT)

Speakers:Adam Bouttell, University of ManitobaAlfredo Cuzzocrea, University of CalabriaCarson Leung, University of ManitobaMartin J. Levesque, University of Manitoba, CanadaSeunggon Son, University of Manitoba, CanadaWeihong Zhang, University of Manitoba

Tracks: DBDM - 7th IEEE International Workshop on Distributed Big Data Management

https://events.rdmobile.com/Sessions/Details/1382395A Data Science Solution for Mining Weather Data and Transportation Data for Smart CitiesWednesday, June 29 9:00 AM – 10:00 AM CEST

Speakers:Sukhmandeep Kaur, University of Manitoba, CanadaNikola N. Kokilev, University of Manitoba, CanadaMichael R. Kuzie, University of Manitoba, CanadaCarson Leung, University of ManitobaBen Nguyen, University of Manitoba, CanadaMark J. Shinnie, University of Manitoba, Canada

Tracks: SSMLS - Smart and Sustainable Mobility and Logistics in Smart Cities

https://events.rdmobile.com/Sessions/Details/1382407Mining Popular Topics from the MediaFriday, July 1 9:00 AM – 10:00 AM CEST

Speakers:Kyle Boch, University of ManitobaAlfredo Cuzzocrea, University of CalabriaFreyja Kristjanson, University of ManitobaCarson Leung, University of ManitobaYu Liu, University of Manitoba, CanadaAndrea M. Unrau, University of Manitoba, CanadaShuai April Zhang, University of Manitoba, Canada

Tracks: DBDM - 7th IEEE International Workshop on Distributed Big Data Management

IEEE ICHI 2022

10th IEEE International Conference on Healthcare Informatics (ICHI 2022) is a premier forum for advances in healthcare informatics. It is held June 11-14 in-person (mostly 07h30-18h CDT (UTC-5)) at Mayo Civic Center, Rochester, MN, USA, and provided virtual-on-demand on Zoom.

ACM BSCI 2022

Fourth ACM international Symposium on Blockchain and Secure Critical Infrastructure (BSCI 2022), which is held in conjunction with the 17th ACM Asis Conference on Information, Computer and Communications Security (ACM AsiaACCS 2022), is held in Nagasaki (長崎), Japan. It was scheduled to be held May 30-June 03, and shortened to May 30-June 02. They are held (mostly 08h30-22h40 JST (UTC+9), i.e., 18h30 (-1d)-08h40 CDT (UTC-5)) as a hybrid conference (in-person and virtual), with presentations and Q&A on Zoom. ACM BSCI was scheduled to be held May 30 at 09h-16h50 JST, and was postponed to 16h-22h50 JST, i.e., 11h-18h50 GST (UTC+4) = 02h-09h50 CDT.

Evan Madill won the Best Student Paper.

Arthritis Society - Ignite Innovation Grant 2022

UM Today News

Creating a clearer picture of lupus

MAY 16, 2022—UM clinician scientist Dr. Lily Lim is using artificial intelligence (AI) to better recognize lupus in patients. Known as "the disease with a thousand faces" symptoms vary from person to person. Lab tests aren't always conclusive. The autoimmune disorder is infamously difficult to diagnose, leaving patients and medical providers confused. But Lim is working with AI to make the face of lupus more recognizable.

Lim, a pediatric rheumatologist and associate professor of pediatrics and child health at Max Rady College of Medicine, has been awarded an Innovation Grant worth over $100,000 from the Arthritis Society as principal investigator of "Machine Learning to Identify Lupus Patients and Define Lifetime Disease Association Trajectories: Preventing Future Morbidities & Improving Health."

The Ignite Innovation Grant supports cutting-edge projects in rheumatic diseases research with the potential to transform patient care. Co-principal investigators are Dr. Lisa Lix, Canada Research Chair in methods for electronic health data quality and associate professor of community health sciences and Dr. Carson Leung, professor of computer science.

Research.com

In 2022 Edition of our Ranking of Top 1000 Scientists in the field of Computer Science (8th edition of Research.com ranking of the best scientists in the arena of Computer Science), Carson Kai-Sang Leung is ranked #226 in Canada and #5072 in the world among Top Scientists for 2022.

APBC 2022

20th Asia Pacific Bioinformatics Conference (APBC 2022) was scheduled to be held January 25-27, and postponed to March 29-31 and then April 26-28. It is hosted in Malaysia and held as a virtual conference

3h-17h (0h-4h), 09h-12h40 (20h-23h40 (-1d)), 13h-17h15 MYT (UTC+8)

in a ...synchronous mode, with presentations and Q&A on Zoom. Day 1 (April 13) runs 10h-18h AMT/EDT (UTC-4), i.e., 09h-17h CDT (UTC-5). Day 3 (April 15) runs 11h-23h JST (UTC+9) = 03h-14h30 CEST (UTC+2), i.e., 20h (-1d)-09h CDT.

AINA 2022

36th International Conference on Advanced Information Networking and Applications (AINA-2022) was scheduled to be held April 13-15, 2022, in Sydney, Australia. Because of COVID-19 situation, it takes place online in a synchronous mode, with presentations and Q&A on Zoom. Day 1 (April 13) runs 10h-18h AMT/EDT (UTC-4), i.e., 09h-17h CDT (UTC-5). Day 3 (April 15) runs 11h-23h JST (UTC+9) = 03h-14h30 CEST (UTC+2), i.e., 20h (-1d)-09h CDT.

IEEE Distinguished Contributor 2021

Dr. Carson K. Leung was selected to the Inaugural Class of IEEE Computer Society Distinguished Contributors. This recognition showcases his contributions to the society and the profession (e.g., well-cited papers, keynote talks, article publications, book chapters, conference publications, panelist presentations at conferences). In this first cohort, only 66 Distinguished Contributors were selected.

Recognizing the First Designated Distinguished Contributorshttps://www.computer.org/publications/tech-news/insider/ieee-computer-society-distinguished-contributors

IEEE Computer Society Team03/14/2022

Introducing the first designated IEEE Computer Society Distinguished Contributors!

The IEEE Computer Society Distinguished Contributor Program was introduced in 2021 as part of the Society’s 75th Anniversary. The program showcases the immense combined technical expertise and innovation power of its membership while recognizing volunteer commitment.

In the program’s first year, 52 Charter Members and 66 members by application were awarded this designation.

2021 IEEE Computer Society Distinguished Contributors

Leung, Carson K.

Congratulations to this first cohort of IEEE Computer Society Distinguished Contributors.

ACM TMIS 13(1)

Jerry Chun-Wei Lin, Nachiketa Sahoo, Gautam Srivastava, Weiping Ding: Introduction to the special issue on pattern-driven mining, analytics, and prediction for decision making, Part 1. ACM TMIS 13(1), special issue on pattern-driven mining, analytics and prediction for decision making: 1:1-1:3 (March 2022)

In A new approach for mining correlated frequent subgraphs [8], the authors proposed a new model to aid in the analysis for large subgraphs, mined from various types of graph transactions in the dataset. The developed model investigated a few measurements to define the confidences and correlations between any two subparts of a frequent subgraph. With the help of the measurement bFact, explosive generation of association rules can be restricted. In addition, these subgraphs are immense in terms of their structural composition and thus parallel the entire set of graphs in the real-world. A complete framework for discovering the relations among parts of a frequent subgraph is proposed by the developed method. Evaluation results show the usefulness and accuracy of the newly-defined measure on real-life graphical datasets.

Prof. Jerry Chun-Wei Lin Western Norway University of Applied Sciences, Bergen, Norwayemail: jerrylin@ieee.orgDr. Nachiketa Sahoo Boston University, USAemail: nachi@bu.eduDr. Gautam Srivastava Brandon University, Canadaemail: SRIVASTAVAG@brandonu.caProf. Weiping DingNantong University, Chinaemail: ding.wp@ntu.edu.cn

REFERENCES

[8] M. E. Chowdhury, C. F. Ahmed, and C. Leung. 2021. A new approach for mining correlated frequent subgraphs. ACM Transactions on Management Information Systems 2021.

IEEE BigComp 2022

1. Dr. Carson K. Leung serves as a Publication Chair for the 2022 IEEE International Conference on Big Data and Smart Computing (BigComp 2022), which was scheduled to held January 17-20, 2022, in Bangkok, Thailand. Due to COVID-19, it is relocated to Daegu (大邱), South Korea, and held (mostly 08h30-19h KST (UTC+9), i.e., 17h (-1d)-04h CST (UTC-6)) as the hybrid of offline and online events. It takes place in a synchronous mode, with prerecorded video presentation and live Q&A on Zoom.
2. Dr. Carson K. Leung also serves the Chair/moderator and a panelist for a panel on "big data lakes: models, frameworks, and techniques".

Steven Euijong Whang, Tok Wang Ling, Carson Leung, Neha Bharill, Won Hwa Kim, Giltae Song: Panel. IEEE BigComp 2022: xxviii

Panel

Chair: Steven Euijong Whang, KAIST, KoreaTitle: Data-centric approaches for Trustworthy AIPanel list- Tok Wang Ling (NUS, Singapore)- Carson Leung (Univ. Manitoba, Canada)- Neha Bharill (Mahindra Univ., India)- Won Hwa Kim (POSTECH)- Giltae Song (Pusan National Univ.)

Inf Sci 582

Kashob Kumar Roy, Md Hasibul Haque Moon, Md Mahmudur Rahman, Chowdhury Farhan Ahmed, Carson Kai-Sang Leung: Mining weighted sequential patterns in incremental uncertain databases. Information Sciences 582: 865-896 (January 2022)

Highlights

An efficient algorithm named FUWS, to mine weighted uncertain sequences.
The uWSInc and uWSInc+ to mine uncertain sequences in incremental databases.
Upper bounds: wgtcap, expSupcap, & wExpSupcap to maintain the anti-monotone property.
A hierarchical index structure, USeq-Trie to maintain weighted uncertain sequences.
First known methods to work for weighted sequences in incremental uncertain database.

Tracking and Preventing Diseases with Artificial Intelligence (2022)

Mayuri Mehta, Philippe Fournier-Viger, Maulika Patel, Jerry Chun-Wei Lin:

Preface.

Tracking and Preventing Diseases with Artificial Intelligence:

v-vii (2022)

In Chap. 5, Sarumi and Leung proposed an adaptive Naive Bayes-based machine learning algorithm for efficient prediction of genes in the genome of eukaryotic organisms. The adaptive Naive Bayes algorithm provided a sensitivity, specificity, and accuracy of 81.52%, 94.01%, and 96.02%, respectively, on discovering the protein-coding genes from the human genome chromosome GRCh37.

Olawoyin's & Pazdor's Teaching

1. Anifat Olawoyin, a PhD student in our lab, teaches:
  - COMP 3380 (Database concepts and usage) in Winter 2022 on every Tuesday and Thursday at 10:00am-11:15am via on-line study from January 25 to April 21, 2022.
  - COMP 1012 A01 (Computer Programming for Scientists and Engineers) in Fall 2022 on every Tuesday and Thursday at 8:30am-9:45am in Wallace 223 from September 08 to December 08, 2022.
  - By the end of Fall 2022, Olawoyin has taught a total of 2 sections of two distinct courses at two undergraduate year-levels.
2. Adam G. Pazdor, a PhD student in our lab, teaches:
  - COMP 4380 A01 (Database implementation) in Winter 2022 on every Tuesday and Thursday at 2:30pm-3:45pm via on-line study from January 25 to April 21, 2022.
  - COMP 4380 A01 (Database implementation) in Winter 2022 on every Tuesday and Thursday at 2:30pm-3:45pm via on-line study from January 25 to April 21, 2022.
  - COMP 1012 in Summer 2022 on every Wednesday at 7:00pm-9:45pm in Armes 208 from May 11 to August 10, 2022.
  - COMP 4710 (A01 and A03) in Fall 2022 on every Tuesday and Thursday at 8:30am-9:45am in E2-350 EITC from September 08 to December 08, 2022.

By the end of Fall 2022, Pazdor has taught a total of 21 sections of six distinct courses at all four undergraduate year-levels (COMP 1012 in Summer 2016, Winter/Summer/Fall 2017, Fall 2018 & Winter 2019, Summer 2021/2022; COMP 1020 in Winter 2020; COMP 2130 in Summer 2018; COMP 3380 in Fall 2016/2017/2019/2020/2021; COMP 4380 in Winter 2018/2020/2021/2022; COMP 4710 in Fall 2022).

IEEE Access 9 (Nov 15 2021)

Example of filtering out high-priority potential noise identified by k-nearest neighbors. The proposed algorithm finds exact clusters from a similarity graph in which the influence of noise points is minimized by filtering out the high-priority potential noise.

IEEE DSCI/CIT 2021

Dr. Carson K. Leung serves as a General Chair for the Fourth International Conference on Data Science and Computational Intelligence (DSCI 2021). It is held, in conjunction with IUCC, CIT and SmartCNS 2021, in London, UK, on 20-22 December 2021. Due to current COVID-19 situation and associated travel restrictions, the conference is held virtually (mostly 08h30-16h30 GMT, i.e., 02h30-10h30 CST (UTC-6)) in an asynchrus-synchrous mode with pre-recorded videos on slack and live Q&A on Zoom.

cit2021conference.slack.com

# cit-2021 (https://cit2021conference.slack.com/archives/C02R3M3TFGC)

Yongchao Zhang

140 - Privacy Prservation of COVID-19 Contract Tracing Data.pptx (https://slack-files.com/T02RR4FUMEC-F02R7FHDXRS-9c7315b6f5)

Carson Kai-Sang Leung, Aniello Castiglione, Jiye Liang: Message from the DSCI 2021 General Chairs. IUCC/CIT/DSCI/SmartCNS 2021: xxi

Message from the DSCI 2021 General Chairs

IUCC/CIT/DSCI/SmartCNS 2021

Welcome to the 4th International Conference on Data Science and Computational Intelligence (DSCI2021), London (Online), UK, in December 20-22, 2021.

The goal of this conference is to identify the challenging problems faced by the development of innovative knowledge and information systems, and to shape future research directions through the publication of high quality, theoretical and applied research outcomes. DSCI-2021 highlights the advances in frontiers and applications of general areas such as big data, artificial intelligence, social computing, data mining, information retrieval, and machine learning. DSCI is uniquely placed to deliver fresh perspectives on data science and computational intelligence.

We would like to give our special thanks to the Program Chairs, Prof. Fei Hao (University of Exeter, UK/Shaanxi Normal University, China), Prof. Aziz Nasridinov, (Chungbuk National University, Korea), and Zhiyuan Tan (Edinburgh Napier University, UK) have put enormous efforts in attracting high-quality papers and creating the technical program during the difficult times of pandemic. We also would like to express our cordial gratitude to all the members of the Organizing Committee and Program Committee for their efforts and support.

It was our great honour and pleasure to accept the responsibilities and challenges of Conference General Chairs. We trust that you will enjoy the academic program within DSCI-2021.

Carson Kai-Sang Leung, University of Manitoba, Canada
Aniello Castiglione, University of Naples Parthenope, Italy
Jiye Liang, Shanxi University, China
DSCI 2021 General Chairs

Wang Miao, Jing Li, Po Yang, Jin Wang: Message from the CIT 2021 Program Chairs. IUCC/CIT/DSCI/SmartCNS 2021: xx

Message from the DSCI 2021 Program Chairs

IUCC/CIT/DSCI/SmartCNS 2021

It is our great pleasure to welcome you to the 4th International Conference on Data Science and Computational Intelligence (DSCI-2021). The DSCI conference is well established in its 4th edition as a highly reputed conference in the field of Data Science and Computational Intelligence.

DSCI-2021 has attracted a number of high-quality papers in the following disciplines: Data Science Theory, Algorithms and Architectures, Data Science Applications, Data Mining and Applications. All manuscripts submitted to DSCI-2021 are carefully peer-reviewed and ranked according to their original contribution, quality, presentation and relevance to the themes of the conference. Finally, 23 papers were selected for presenting at the conference as well as inclusion in the conference proceedings. We would like to extend our thanks to the program committee members who contributed their precious time and expertise to provide professional reviews and very interesting feedback to authors in a tight time schedule.

We would like to give our special thanks to the General Chairs Prof. Carson Kai-Sang Leung (University of Manitoba, Canada), Prof. Aniello Castiglione (University of Naples Parthenope, Italy), and Prof. Jiye Liang (Shanxi University, China) for a successful DSCI-2021 and for the success of the final program. We sincerely appreciate their timely unlimited support and guidance. It was a great pleasure to work with such an excellent team. Also, we would like to express our gratitude to the local team for managing the program information in the conference website, and their efficient assistances on the conference.

We expect this conference to be a highly stimulating event to foster interesting discussions as well as useful interaction between researchers, and to provide an excellent forum for exchanging and developing new ideas in the field of data science and computational intelligence technology.

Fei Hao, University of Exeter, UK & Shaanxi Normal University, China
Aziz Nasridinov, Chungbuk National University, Korea
Zhiyuan Tan, Edinburgh Napier University, UK
DSCI 2021 Program Chairs

IEEE DSS/SmartCity 2021

Dr. Carson K. Leung serves as a General Chair for the Seventh IEEE International Conference on Data Science and Systems (DSS 2021). It is held, in conjunction with IEEE HPCC, SmartCity, DependSys, GPC and DIKW 2021, in Haikou, Hianan (海南海口), China, on 17-19 December 2021. Due to local covid pandemic policy change, it is postponed to 20-22 December 2021 at Novotel Haikou Xinbudao (海口新埠岛诺富特酒店). It is held (mostly 08h-21h55 China Standard Time (UTC+8), i.e., 18h (-1d)-07h55 Central Standard Time (UTC-6)) in an synchrous mode with (1) keynote on Zoom, (2) physical presentation on Tencent meeting, and (3) live online presentation and Q&A on Zoom.

Laurence T. Yang, Jinjun Chen: Message from the DSS 2021 steering chairs. IEEE HPCC-DSS-SmartCity-DependSys 2021: lxvi

Message from the DSS 2021 Steering Chairs

Welcome to the 7th IEEE International Conference on Data Science and Systems (DSS 2021) planned to be held in Haikou, December 20-22, 2021. Given the COVID-19 pandemic and associated travel restrictions, as the safety of people is of the highest priority, the conference will be held hybridly on December 20-22, 2021. On behalf of the DSS steering committee and DSS 2021 organizing committee, we would like to extend our sincere welcome and high respect to all participants.

The essence of data science is to derive valuable insights from data. It is emerging to meet the challenges of processing very large datasets, i.e. Big Data, with the explosion of new data continuously generated from various channels, such as smart devices, web, mobile and social media. With this continuing data explosion, it is necessary to store and process data efficiently by utilizing enormous computing power. The importance of data-intensive systems has been raising and will continue to be the foremost field of research. Innovative programming models, high-performance scalable computing platforms, efficient storage systems and expression of data requirements are in immediate need. The DSS 2021 is the 7th event following the success in 2015 (DSDIS 2015), 2016 (DSS 2016), 2017 (DSS 2017), 2018 (DSS 2018), 2019 (DSS 2019) and 2020 (DSS 2020). It aims to provide a prime international forum for researchers, industry practitioners and domain experts to exchange the latest advances in Data Science and Data Systems as well as their synergy.

An international conference can be organized by supports and great voluntary efforts of many people and organizations. Our main responsibility is to coordinate various tasks carried out with willingness and by talented volunteers. We would like to thank the General Chairs Francisco Herrera (University of Granada, Spain), Carson K. Leung (University of Manitoba, Canada), and Arnaud Martin (University of Rennes and IRISA Lab, France) for the very successful organization of DSS-2021. We would like to express our special thanks to the Program Chairs Shirui Pan (Monash University, Australia), Xiao Shen (Hainan University, China), and Farookh Khadeer Hussain (University of Technology Sydney, Australia) for making an excellent technical program with a strict review process. We would like to greatly appreciate the Program Vice-Chairs Yiru Zhang (St. Francis Xavier University, Canada), Hua Li (Hainan University, China), and Wei Lu (University of Electronic Science and Technology of China, China) for their great supports. We would like to express our appreciation for the excellent work of the publicity chairs for advertising and promoting our conference, as well as the web chairs and the conference organization team for excellent arrangement of the conference.

Finally, we would also like to take this opportunity to thank all the members of the organizing committee and the program committee, as well as all authors who submitted papers and reviewers who reviewed the submitted manuscripts.

Laurence T. Yang, St. Francis Xavier University, Canada
Jinjun Chen, Swinburne University of Technology, Australia
DSS 2021 Steering Chairs

Francisco Herrera, Carson K. Leung, Arnaud Martin: Message from the DSS 2021 general chairs. IEEE HPCC-DSS-SmartCity-DependSys 2021: lxvii

Message from the DSS 2021 General Chairs

Welcome to the 7th IEEE International Conference on Data Science and Systems (DSS 2021). Given the COVID-19 pandemic and associated travel restrictions, as the safety of people is of the highest priority, the conference will be held hybridly on December 20-22, 2021. On behalf of the Organizing Committee of DSS 2021, we would like to express our sincere and warm welcome to all of participants!

The IEEE DSS 2021 Conference, the 7th event in the series, is a prime international forum for researchers, industry practitioners and domain experts to exchange the latest advances in Data Science and Data Systems as well as their synergy. DSS 2021 is sponsored by IEEE, IEEE Computer Society, and IEEE Technical Committee on Scalable Computing (TCSC).

DSS 2021 consists of the main conference with 14 regular and 9 short paper presentations out of 52 submissions from more than 10 countries or regions. For the successful initialization and organization of this international conference with this size and diversity, we counted on the great support of many people and organizations. First of all, we would like to sincerely thank Laurence T. Yang (St. Francis Xavier University, Canada) and Jinjun Chen (Swinburne University of Technology, Australia), the Steering Chairs of DSS, for giving us the opportunity to organize the conference and for their support and guidance. We would like to express our special thanks to the Program Chairs Shirui Pan (Monash University, Australia), Xiao Shen (Hainan University, China), and Farookh Khadeer Hussain (University of Technology Sydney, Australia) for their excellent work and tremendous efforts in organizing an excellent program committee, conducting a rigorous review, selecting high-quality papers from a large number of submissions, and preparing an excellent conference. We are grateful to the Program Vice-Chairs Yiru Zhang (St. Francis Xavier University, Canada), Hua Li (Hainan University, China), and Wei Lu (University of Electronic Science and Technology of China, China), as well as other chairs and members for their great supports. We thank all the reviewers for their hard work in reviewing the manuscript, providing constructive feedback to the authors and making the paper well selected. Most importantly, we are grateful to all the authors for the high quality of the papers submitted to the main DSS 2021 conference. Last but not least, we would like to thank the DSS 2021 web and Conference organizing team for the excellent arrangements of the conference.

Thank you to everyone who attended DSS 2021, we hope the conference will be exciting and interesting for your research and professional activities, and that IEEE DSS will be one of the best conferences in the field!

Francisco Herrera, University of Granada, Spain
Carson K. Leung, University of Manitoba, Canada
Arnaud Martin, University of Rennes and IRISA Lab, France
DSS 2021 General Chairs

Shirui Pan, Xiao Shen, Farookh Khadeer Hussain: Message from the DSS 2021 program chairs. IEEE HPCC-DSS-SmartCity-DependSys 2021: lxviii

Message from the DSS 2021 Program Chairs

It is our great pleasure to welcome you to DSS 2021, the 7th IEEE International Conference on Data Science and Systems, held hybridly on December 20-22 due to the COVID-19 pandemic. The DSS 2021 conference is sponsored by IEEE, IEEE Computer Society, and IEEE Technical Committee on Scalable Computing (TCSC).

The essence of data science is to derive valuable insights from data. It is emerging to meet the challenges of processing very large datasets, i.e. Big Data, with the explosion of new data continuously generated from various channels, such as smart devices, web, mobile and social media. With this continuing data explosion, it is necessary to store and process data efficiently by utilizing enormous computing power. The importance of data-intensive systems has been raising and will continue to be the foremost field of research. This raise brings up many research issues, in forms of capturing and accessing data effectively and fast, processing it while still achieving high performance and high throughput, and storing it efficiently for future use. Innovative programming models, high-performance scalable computing platforms, efficient storage systems and expression of data requirements are in immediate need. The DSS 2021 is aiming to offer a prime international forum for researchers, industry practitioners and domain experts to exchange the latest advances in Data Science and Data Systems as well as their synergy.

The technical program of DSS 2021 consists of 14 regular and 9 short papers, selected by the program committee from 52 full submissions in response to the call for papers. This year, the acceptance rate of main conference regular papers is 27%. All submissions were reviewed by the program committee members. These high-quality submissions cover many hot research topics, including data science, data processing technology, data systems, data applications, to name a few. First, we would like to thank all the program committee members for their hard work in reviewing all submitted papers. Next, we would like to extend our special thanks to the DSS General Chairs (Francisco Herrera, Carson K. Leung, and Arnaud Martin) and the Steering Committee Chairs (Laurence T. Yang and Jinjun Chen) for their consistent leadership and guidance. We also would like to thank the Program Vice-Chairs (Yiru Zhang, Hua Li, and Wei Lu), and the Publicity Chairs (Zhenchao Ma and Jing Yang), for their hard work in making DSS 2021 a success. Furthermore, we would like to thank all the authors for submitting and presenting their exciting ideas and solutions at the conference.

Shirui Pan, Monash University, Australia
Xiao Shen, Hainan University, China
Farookh Khadeer Hussain, University of Technology Sydney, Australia
DSS 2021 Program Chairs

IEEE BigData 2021

The IEEE International Conference on Big Data (BigData 2021) was scheduled to be held December 15-18, 2021, in Orlando, FL, USA. Due to COVID-19, it is taking place virtually as an online event (mostly 09h-22h EST (UTC-5), i.e., 08h-21h CST (UTC-6)) in an asynchrus-synchrous mode with pre-recorded videos and live Q&A on Zoom via Underline.

IEEE BIGDATA 2021 / SESSIONS / MACHINE LEARNING ON BIG DATA (MLBD 2021)

Open Data Lake to Support Machine Learning on Arctic Big Data

IEEE BIGDATA 2021 / SESSIONS / SPECIAL SESSION: PRIVACY AND SECURITY OF BIG DATA (PSBD 2021)

Privacy-Preserving Publishing and Visualization of Spatial-Temporal Information

IEEE WI-IAT 2021

The 20th IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2021) is held 14-17 December 2021 in Deakin Downtown, Melbourne, Australia, with a theme of "artificial intelligence in the connected world". Due to COVID-19, it is held as a hybrid conference with both online and offline modes (mostly 08h45-22h AEDT (UTC+11), i.e., 15h45 (-1d)-05h CST (UTC-6)) in an asynchrus-synchrous mode with (pre-recorded or) live videos and live Q&A on Zoom. The recording was used as a backup plan when the live presentation was experiencing technical issues such as unstable internet connection. Key events are live streamed from Zoom to YouTube and on Tencent.

IEEE BIBM 2021

The IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2021) was scheduled to be held December 09-12, 2021, in Houston, TX, USA. Due to the current COVID-19 situation and the restriction of the international travel, it transforms the in-person component into an all-digital conference experience. It is held virtually as an online event (mostly 09h-18h30 EST (UTC-5), i.e., 08h-17h30 CST (UTC-6)) in an asynchrus-synchrous mode with pre-recorded videos and live Q&A on Zoom via Underline.

IEEE BIBM 2021 / SESSIONS / SESSION 13: DATA MINING, MACHINE LEARNING, AND ARTIFICIAL INTELLIGENCE FOR HEALTH INFORMATICS (3)

Health Analytics on Big COVID-19 Data

Carson Leung

IEEE ICDM 2021

The IEEE International Conference on Data Mining (ICDM) has established itself as the world's premier research conference in data mining. The 21st IEEE ICDM 2021 was scheduled to be held December 07-10, 2021, in Auckland, New Zealand. Due to the ongoing COVID-19 circumstances around the world, it is held as a virtual conference (mostly 14h-21h NZDT (UTC+13), i.e., 19h (-1d)-02h CST (UTC-6)) in an asynchrus-synchrous mode with pre-recorded videos and live Q&A on Zoom via EventsAIR.

Workshop 007 - UDML: Utility Driven Mining and Learning
2:00pm - 4:30pm NZDT

Session Information:
2:50pm-4:20pm (NZ) Presentations
DM368: Mining High Utility Subgraphs
Presenters: Md. Tanvir Alam, Amit Roy, Chowdhury Farhan Ahmed, Md. Ashraful Islam, and Carson Leung

Handouts:
Prof. Carson Leung
Professor
University of Manitoba

01. Abstract
ICDM-UDML2021_DM368_abstract.docx - 11.9 KB

IEEE ICKG 2021

The 12th IEEE International Conference on Big Knowledge (ICBK 2021) is held in Auckland, New Zealand, on December 07-08, 2021. Due to the situation of COVID-19, it is held online (mostly 09h-17h10 China Standard Time/HKT (UTC+8), i.e., 19h (-1d)-03h10 Central Stanard Time (UTC-6)) in an asynchrus-synchrous mode with pre-recorded videos and live Q&A on Zoom.

ArcticNet ASM 2021

Dr. Carson K. Leung serves as a Session Chair for DTM49 on "collecting, storing and disseminating Arctic data – new solutions to chronic problems" in the ArcticNet Virtual Annual Scientific Meeting (ASM 2021), which is a hub for Arctic research in Canada. It is held December 06-10, 2021 entirely online (mostly 09h30-20h30 EST (UTC-5), i.e., 08h30-19h30 CST (UTC-6)) in an asynchrus-synchrous mode with pre-recorded videos and live Q&A on EventMobi.

IEEE Cybermatics 2021

The Seventh IEEE International Conference on Smart Data (SmartData 2021) is held, in conjunction with IEEE Blockchain, CPSCom, iThings, and GreenCom 2021 as part of IEEE Cybermatics Congress 2021, on 06-08 December 2021. It was scheduled to be held in Deakin Downtown, Melbourne, Vic, Australia. Due to to the low number of registrations of physical attendance and the new Omicron COVID-19 variant, IEEE Cybermatics Congress 2021 is held online/virtual (mostly 08h-20h AEDT (UTC+11), i.e., 15h (-1d)-03h CST (UTC-6)) in a synchrous mode with live presentation and Q&A on Zoom.

BigDAS 2021

Dr. Carson K. Leung serves as a Program Chair for the Ninth International Conference on Big Data Applications and Services (BigDAS 2021). It is held Novermber 25-27, 2021, in Grabel Hotel, Jeju Island (濟州島), South Korea. It is held mostly 10h-17h50 KST (UTC+9), i.e., 19h (-1d)-02h50 CST (UTC-6).
Dr. Carson K. Leung gives a keynote speech I at BigDAS 2021 at 13h-13h50 KST (UTC+9), i.e., 22h (-1d)-22h50 (-1d) CST (UTC-6).

Carson K. LeungUniversity of Manitoba, Canada

Lecture Title: Big data analytics of COVID-19 epidemiological dataLecture Date: November 25, 2021, 13:00

BIGDAS Conference @bigdasconf · Nov 21

For BIGDAS2021, we invited three outstanding keynote speakers: Carson K. Leung (University of Manitoba, Canada), Hong-Gee Kim (Seoul National University), Morris Fan (National Taipei University of Technology, Taiwan) #BIGDAS2021 #BIGDATA

IEEE Access 9

Jeong-Hun Kim, Jong-Hyeok Choi, Young-Ho Park, Carson Kai-Sang Leung, and Aziz Nasridinov: KNN-SC: novel spectral clustering algorithm using k-nearest neighbors. IEEE Access 9:152616 - 152627 (2021)

Graphical abstract:

IEEE ASONAM 2021

International Symposium on Foundations and Applications of Big Data Analytics (FAB) 2021 is held in conjunction with the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2021) and HI-BI-BI 2021. It was scheduled to be held on 08-11 November 2021 in The Hague, Netherlands. Due to COVID-19, it is held as a virtual event on Zoom (mostly 13h30-20h CET (UTC+1), i.e., 06h30-13h CST (UTC-6)) in a synchronous mode, with live presentation and Q&A on Zoom.

EUSPN 2021

The 12th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2021) is scheduled to be held November 01-04, 2021 in Park Inn Radisson, Leuven, Belgium.

IEEE CyberSciTech 2021

Dr. Carson K. Leung serves as a Program Chair for the Seventh IEEE International Conference on Cloud and Big Data Computing (CBDCom 2021). It was scheduled to be held, in conjunction with IEEE PICom and DASC, as part of CyberSciTech 2021, on October 25-28, 2021, in Calgary, AB, Canada. Due to COVID-19, it is held online (mostly 07h-10h and 16h-21h MDT (UTC-6), i.e., 08h-11h and 17h-22h CDT (UTC-5)) in a hybrid mode (both onsite and online) a synchronous mode, with live presentation and Q&A on Zoom via Whova. Zoom session recordings are available on Whova.

WS 2C: Special Session on Intelligent Computing in Cyber-Physical-Social Systems 2

Wed. Oct 27, 2021 9:00 AM - 10:00 AM MDT (10:00 AM - 11:00 AM CDT)

Analyzing COVID-19 Epidemographic Data (Paper ID 1570760742)

Anna Kobusinska, Rachid Benlamri, Carson Kai-Sang Leung, Gautam Srivastava: Message from the CBDCom 2021 Program Chairs and General Chairs. DASC/PiCom/CBDCom/CyberSciTech 2021: xxxiv

Message from the CBDCom 2021 Program Chairs and General Chairs

DASC/PiCom/CBDCom/CyberSciTech 2021

The 7th IEEE International Conference on Cloud and Big Data Computing (CBDCom 2021) is a premier forum for the exchange and dissemination of the latest advances in cloud computing and big data systems and applications among researchers, practitioners, developers, and users who are interested in exploring new ideas, techniques, tools, and in identifying emerging research topics. CBDCom 2021 is continuing the tradition of the CBDCom conference series that started in 2015 in Beijing and has been held annually.

The conference is co-located with IEEE PICom 2021, IEEE CyberSciTech, and IEEE DASC 2021, within the IEEE Joint Cyber Science and Technology Congress. With much disappointment, we had to move the IEEE CBDCom 2021 and co-located conferences to a virtual mode for another year. We missed you in 2020 and worked diligently to find creative ways to host you in Calgary, Canada, in 2021. Unfortunately, many pandemic-induced uncertainties forced us to resign from organising the in-person meeting that enables authors the research interaction at the conference venue. On a positive note, the virtual version of IEEE CBDCom and IEEE Joint Cyber Science and Technology Congress will give the participants a chance to download papers and view video presentations. It will also provide an excellent keynote presentation by distinguished researchers: Prof. Helen Karatza, Prof. Paulo Pires, Prof. Yi Qian, and Prof. Qun Jin.

The successful organisation of IEEE CBDCom has required dedication and time. We want to take this opportunity to thank all the members of the organising and steering committee, especially the Steering Chairs, Prof. Jianhua Ma and Prof. Laurence Yang, for their outstanding support and guidance in the preparation of the conference. We extend our thanks to the entire local committee members, including General Executive Chair Prof. Oscar Lin. Also, we thank the Track Chairs, Technical Program Committee and all reviewers for their valuable time and effort in reviewing the papers. Last but not least, we thank all of the authors for their creative and worthwhile contributions, which make the high quality of IEEE CBDCom 2021.

It was our great honour and pleasure to accept the responsibilities and challenges of Conference General and Program Chairs. We trust that you will enjoy the first virtual IEEE CBDCom conference!

Anna Kobusinska, Poznan University of Technology, PolandRachid Benlamri, Lakehead University, CanadaCBDCom 2021 General Chairs

Carson Kai-Sang Leung, University of Manitoba, CanadaGautam Srivastava, Brandon University, CanadaCBDCom 2021 Program Chairs

IEEE BIBE 2021

The 21st IEEE International Conference on BioInformatics and BioEngineering (BIBE 2021) is held October 25-27, 2021, in Kragujevac, Serbia. Due to COVID-19, it is held (mostly 08h30-23h CEST (UTC+2), i.e., 01h30-16h CDT (UTC-5)) as a hybrid conference with the combination of in-person attendees and virtual attendees, with live presentation and Q&A, on BigBlueButton.

IEEE DataCom 2021

The Sixth IEEE International Conference on Big Data Intelligence and Computing (DataCom 2021) is held, in conjunction with IEEE SAGC (Space-Air-Ground Computing) 2021, in Kande International Hotel (惠州康帝国际酒店), Huizhou, Guangdong (广东惠州), China, on October 23-25, 2021. Due to COVID-19, it is held (mostly 09h-19h20 China Standard Time (UTC+8), i.e., 20h (-1d)-06h20 Central Daylight Time (UTC-5)) in a hybrid mode (both onsite and online). Online sessions are held in a synchronous mode, with live presentation and Q&A on Zoom.

IEEE TrustCom-BigDataSE-CSE-EUC-iSCI 2021

The 15th IEEE International Conference on Big Data Science and Engineering (BigDataSE 2021) was scheduled to be held in Shenyang (沈阳), China, on August 18-20, 2021, and postponed to October 20-22, 2021. Due to the uncertain COVID-19 cases in Mainland China, it is held (mostly 08h30-20h China Standard Time (UTC+8), i.e., 19h30 (-1d)-07h Central Daylight Time (UTC-5)) in a hybrid mode with overseas authors presenting their works online (by either recording videos or real-time online accress) and live Q&A on Zoom while Mainland Chinese authors presenting their works on site at Huaqiang Novlion Hotel (华强诺华廷酒店).

IEEE Smart World Congress 2021

The 21st IEEE International Conference on Scalable Computing and Communications (ScalCom 2021) and the Fifth IEEE International Conference on Smart City Innovations (SCI 2021), as parts of the 2021 IEEE Smart World Congress (SmartWorld 2021) together with ATC 2021, IoP 2021 and UIC 2021, were scheduled to be held October 18-21, 2021 in Atlantia, GA, USA. Due to COVID-19, it is held (mostly 08h15-19h15 EDT (UTC-4) = 07h15-18h15 CDT (UTC-5)) in an asynchronous mode with pre-recorded presentation videos of all accepted papers played by the conference organizers on Zoom for the authors during the technical sessions (because the authors are from different time zones). Keynote talks are live on Zoom.

IEEE/ACM/ASA/CCF DSAA 2021

Eighth IEEE International Conference on Data Science and Advanced Analytics (DSAA) was scheduled to be held October 06-09, 2021 in Porto, Portugal. Due to COVID-19, it is held as an online event (08h30-18h15 WEST (UTC+1) = 02h30-12h15 CDT (UTC-5)) with presentation choices like (1) present the contribution live and have the recorded video as a backup on Whova and (2) play back the recorded video and live Q&A on Zoom via Whova. Recorded video presentation and poster are also available on Whova.

Explainable artificial intelligence for data science on customer churn

Thu. Oct 7, 2021 3:30 PM - 3:45 PM WEST (9:30 AM - 9:45 AM CDT)

[video: 3 - 236.mkv (30.8 MB) on INESC TEC Drive]

Speaker: Carson Leung, University of Manitoba, Canada

Cover PhotoPoster [doc_issci_202012_1633497709432.pdf]

DEXA / DaWaK 2021

The 32rd International Conference on Big Data Analytics and Knowledge Discovery (DaWaK2021) was originally planned for Linz, Austria on September 27-30, 2021. Due to COVID-19, it is held as a virtual conference (mostly 09h00-17h45 CEST (UTC+2) = 02h00-10h45 CDT (UTC-5)) in a synchronous mode, with live presentation and Q&A on Zoom.

UofM SSA Science Welcome Day 2021

On Tuesday, September 07, 2021, Dr. Carson Leung represented Computer Science in the Science Welcome Day Panel Discussion.

IEEE Services / ICDH 2021

2021 IEEE International Conference on Digitial Health (ICDH), which is a part of 2021 IEEE World Congress on Services (SERVICES), was scheduled to be held September 05-11, 2021 in Chicago, IL, USA. Due to COVID-19, it is held as an all-online virtual event 24/7 in a synchronous mode, with live presentations and Q&A on Zoom. Prerecorded video presentation submitted to Underline is for backup. Zoom session recordings are available on Underline.

Short bio: Carson Leung is currently a Professor at the University of Manitoba, Canada. He has contributed more than 280 refereed publications on the topics of big data, bioinformatics, computational intelligence, cognitive computing, data analytics, data mining, data science, distributed computing, fuzzy systems, high-performance computing, machine learning, social network analysis, and visual analytics. He has also served on the Organizing Committee of the ACM CIKM, ACM SIGMOD, IEEE DSAA, IEEE ICDM, and other conferences.

PDF of slides

video pre-recording

06 September CHD3: ICDH Regular Papers Session 3 18:10-19:30 UTC IEEE SERVICES 2021 / SESSIONS / CDH3: ICDH REGULAR PAPERS SESSION 3 A Digital Health System for Disease Analytics

Guide2Research (Updated)

Carson K. Leung

University of Manitoba

Canada

G2R World Ranking 4298th

G2R Canada Ranking 226th → 193rd

H-Index & Metrics

Google H-index 43 → 48

Number of Google Citations 6,925 → 7,628

Number of Articles on DBLP 212

External Links

Google Scholar Profile

Personal Website for Carson K. Leung

List of Publications on DBLP

Profile was last updated at August 2, 2021, 6:18 pm

Guide2Research Ranking is based on Google Scholar H-Index.

INCoS 2021

1. Dr. Carson K. Leung serves as a Track Chair for the 13th International Conference on Intelligent Networking and Collaborative Systems (INCoS 2021) held September 01-03, 2021 in Taichung (臺中), Taiwan. He oversees the Data Mining, Machine Learning and Collective Intelligence track.
2. INCoS-2021 is held in conjunction with NiBS-2021 on September 01-03, 2021. It was scheduled to be held in Taichung (臺中), Taiwan. Due to COVID-19, it takes place online (mostly 09h-17h TWT (UTC+8), i.e., 10h-18h JST (UTC+9), i.e., 20h (-1d)-04h CDT (UTC-5)) in a synchronous mode, with with presentations and Q&A on Zoom.

APWeb-WAIM 2021

APWeb and WAIM are two separated leading international conferences on research, development and applications of Web technologies and database systems. Starting in 2017, the two conference committees have agreed to launch a joint conference. APWeb-WAIM 2021 was scheduled to be held August 23-25, 2021, in Guangzhou (广州), China. Due to the situation of COVID-19 globally, it becomes a fully virtual conference (mostly 08h30-17h China Standard Time (UTC+8), i.e., 19h30 (-1d)-04h Central Daylight Time (UTC-5)) in a combined synchronous-asynchronous mode, with prerecorded video presentation and live Q&A on Tencent Meeting.

FoS 3MT 2021

UM Today News

Cheer on the Faculty of Science 3MT 2021 Competitors

AUGUST 6, 2021—On August 10 and 11, 2021, students will be challenged to showcase their research to a general audience in a three-minute or less in a 3MT competition. Part of the Faculty of Science, Student Undergraduate Summer Research Experience Program.

There will be two competitions that will air live on the Faculty of Science YouTube channel.

Life Sciences
Tuesday, August 10, at 1 PM: Watch online: https://youtu.be/SNNuIyD3KVY
Physical Science and Computational & Data Sciences
Wednesday, August 11, at 1 PM: Watch online: https://youtu.be/8jOZRoIlQfs

Listing of undergraduate student 3MT competitors and topics:

Physical, Computational, Mathematical & Statistical Sciences
3MT Competition
Wednesday, August 11, 2021 at 1:00 pm
Watch online: https://youtu.be/8jOZRoIlQfs

Representing Information In a Smaller Way
Connor Hryhoruk
Supervisor: Dr. Carson Leung, Department of Computer Science

Merit Award 2020

1. Dr. Carson Leung won a 2020 Merit Award in the Research, Scholarly Work and Creative Activities category.
2. UM Today News

Congratulations to the Merit Award winners for 2020

AUGUST 4, 2021 — Merit Awards at the University of Manitoba recognize faculty members for their outstanding teaching, research, scholarly work and creative activities, and service in three categories: Social Sciences, Humanities and Fine Arts; Life Sciences, Natural Sciences and Engineering; and Promoting Indigenous Achievement. Annual applications and nominations are invited for the previous calendar year and awarded by two Joint Committees on Merit Awards.

The recipients of the 2020 Merit Awards are listed below and receive $3,000 each. Congratulations to all.

Merit Award Winners for 2020 Calendar Year

LIFE SCIENCES, NATURAL SCIENCES AND ENGINEERING

Research, Scholarly Work and Creative Activities:

Carson Leung, Department of Computer Science, Faculty of Science

Wawatay Summer Orientation Research Talk 2021

On Monday, July 26, 2021, Dr. Leung gave a 20-min presentation on "data mining" and chatted with students over lunch at UofM FoS Wawatay Program Summer Orientation Research Talk.

Wawatay (an Anishinaabe word for the "Northern lights") is a new initiative starting Summer 2021 to focus on Indigenous student success in Science. Wawatay is a program that seeks to develop closer ties to indigenous communities, dramatically grow the number of indigenous science graduates, and infuse Indigenous perspectives into Science education. Students who complete a Bachelor of Science degree as a Wawatay Scholar will have a strong connection to their indigenous community, access to a network of support and future contacts, and professional skills and knowledge of how to apply that degree to a given career. Before Wawatay Scholars begin their first semester at the University of Manitoba, they will participate in a mandatory six-week summer orientation, which will be held on campus (July 12-August 20, 2021, following COVID-safe protocols). Orientation is designed to ease the transition into University 1 and help students adjust to life away from home. Participating in research is an essential part of the Wawatay experience; therefore, students are introduced to research happening in the faculty of science. During orientation, in-person/remote talks are held from 12-1:30 PM, where faculty members are invited to share their research interests with students. Faculty are asked to deliver a brief (approximately 20 minute) presentation and chat with students over lunch. Because of Dr. Leung's outstanding research contributions, Wawatay students are felt to be benefit from hearing about his program.

IJCNN 2021

The annual International Joint Conference on Neural Networks (IJCNN) is the flagship conference of the IEEE Computational Intelligence Society and the International Neural Network Society. IJCNN 2021 was scheduled to be held July 18-22, 2021, in Shenzhen (深圳), China. Due to COVID-19 restrictions, it is held July 18-23, 2021, as a virtual event (mostly 08h-18h BST (UTC+1), i.e., 02h-12h CDT (UTC-5)) in a combined synchronous-asynchronous mode, with prerecorded video presentation on the Confflux platform and live Q&A on Zoom.

Session S15

Advanced Algorithms of Machine Learning and Artificial Intelligence Applied for Biomedical Data Processing I

Jul 18, 09:15am CDT to Jul 18, 11:15am CDT (Jul 18, 03:15pm BST to Jul 18, 05:15pm BST (UTC+1))

Oral Presentations

ID 1991

Predictive Analytics of COVID-19 with Neural Networks

Jul 18, 09:55am CDT to Jul 18, 10:15am CDT

[video https://confcats-event-sessions.s3.amazonaws.com/ijcnn21/videos/1991.mp4]

1.1. PRESENTER(S)

Carson Leung

University of Manitoba

Canada

Author, Speaker, Attendee

Biography

Carson Leung is currently a Professor at the University of Manitoba, Canada. He has contributed more than 280 refereed publications on the topics of big data, computational intelligence, cognitive computing, data analytics, data mining, data science, fuzzy systems, machine learning, social network analysis, and visual analytics. He has also served on the Organizing Committee of the ACM CIKM, ACM SIGMOD, IEEE DSAA, IEEE ICDM, and other conferences.

1.2. ABSTRACT

Neural networks (NNs) have been applied in numerous real-life applications and services. These include the applications in disease and healthcare analytics, such as identification and predictive analytics of coronavirus disease 2019 (COVID-19). However, many existing NN-based solutions train the models based on data (e.g., computed tomography (CT) scan images, viral/molecular test results) that can be expensive to produce and/or not easily accessible. They also require large volumes of these data for training. However, partially due to privacy concerns and other factors, the volume of available COVID-19 data can be limited. Hence, in this paper, we present a solution for predictive analytics of COVID-19 with NNs. Our solution consists of three algorithms, which make good use of autoencoder and few-shot learning, to train the prediction model with only a few samples of more accessible and less expensive types of data (e.g., serology/antibody test results from blood samples). Evaluation results on a real-life Brazilian COVID-19 dataset demonstrate the effectiveness of our solution in predictive analytics of COVD-19 with NNs.

2. PAPER

Predictive Analytics of COVID-19 with Neural Networks (application/pdf)

Download [https://confcats-event-sessions.s3.amazonaws.com/ijcnn21/papers/N-1991.pdf]

Author(s)

Daryl Fung, University of Manitoba

Calvin Hoi, University of Manitoba

Carson Leung, University of Manitoba

Christine Zhang, University of Manitoba

3. SLIDES

Predictive Analytics of COVID-19 with Neural Networks (application/pdf)

Download [https://confcats-event-sessions.s3.amazonaws.com/ijcnn21/slides/1991.pdf]

IDEAS 2021

25th International Database Engineering & Applications Symposium (IDEAS 2021) was scheduled to be held July 14-16, 2021, in Montreal, Canada. Due to continued concern with COVID, this 25th anniversary of IDEAS is held online virtually (mostly 08h30-16h30 EDT, i.e., 07h30-15h30 CDT) in a synchronous mode, with live presentation and Q&A on Zoom. Slides are available on ConfSys. A commemorative hard copy version of the proceedings, to mark the silver anniversary of IDEAS, is mailed to the registered conference participants.

IEEE COMPSAC 2021

IEEE Annual Computers, Software, and Applications Conference (COMPSAC) was designated the IEEE Computer Society signature conference on computers, software and applications in 2006. As its 45th anniversary conference, COMPSAC 2021—in honor of the Computer Society's 75th anniversary—was scheduled to be held July 12-16, 2021, in Madrid, Spain. Due to the ongoing COVID-19 situation, it transforms the in-person component of COMPSAC 2021 into an all-digital conference experience. It takes place virtually as an online event (running mostly 08h-17h PDT (UTC-7), i.e., 10h-19h CDT (UTC-5)) in an asynchronous mode, with videos of most sessions (except live keynote & panel sessions) for asynchronous watching, on Underline. The theme of COMPSAC 2021 is "intelligent and resilient computing for a collaborative world".

12 July

Workshop 13 - DADA: Deep Analysis of Data-Driven Applications 12:00-13:30 PDT

2021 IEEE COMPSAC / SESSIONS / WORKSHOP 13 - DADA: DEEP ANALYSIS OF DATA-DRIVEN APPLICATIONS

307. A Data Analytic Solution for Measuring the Impact of COVID-19 on IT-Related Job Opportunities

Carson Leung

Workshop 15 - DBDM: Distributed Big Data Management 12:00-13:30 PDT

2021 IEEE COMPSAC / SESSIONS / WORKSHOP 15 - DBDM: DISTRIBUTED BIG DATA MANAGEMENT

461. Distributed Big Data Management

Carson Leung

[video 25107-distributed-big-data-management]

13 July

DSAT – Data Sciences, Analytics & Technologies 14:00-15:00 PDT

2021 IEEE COMPSAC / SESSIONS / DSAT – DATA SCIENCES, ANALYTICS & TECHNOLOGIES

277. Bayesian Based Predictive Analytics for Transportation Analytic Application via Machine Learning

Carson Leung

[video 25002-bayesian-based-predictive-analytics--for-transportation-analytic-application--via-machine-learning]

Short bio:

Carson Leung is currently a Professor at the University of Manitoba, Canada. He has contributed more than 280 refereed publications on the topics of big data, bioinformatics, computational intelligence, cognitive computing, data analytics, data mining, data science, distributed computing, fuzzy systems, high-performance computing, machine learning, social network analysis, and visual analytics. He has also served on the Organizing Committee of the ACM CIKM, ACM SIGMOD, IEEE DSAA, IEEE ICDM, and other conferences.

IV 2021

25th International Conference Information Visualisation (IV 2021) was scheduled to be held 05-09 July 2021 at University of Technology Sydney (UTS), Australia. Due to COVID-19, it—together with 18th International Conference Computer Graphics, Imaging and Visualization (CGiV 2021)—takes place online (mostly 07h-15h CEST (UTC+2) = 15h-23h AEST (UTC+10), i.e., 00h-08h CDT (UTC-5)) in a synchronous mode, with live presentations Q&A on Zoom. Prerecorded video presentation on ConfTool is for backup. Zoom session recordings are available on Google Drive.

Brief bio: Carson Leung is currently a Professor at the University of Manitoba, Canada. He has contributed more than 280 refereed publications on the topics of big data, bioinformatics, computational intelligence, data analytics, data mining, data science, distributed computing, high-performance computing, information visualization, machine learning, social network analysis, and visual analytics. He has served on the Organizing Committee of the ACM CIKM, ACM SIGMOD, IEEE DSAA, IEEE ICDM, and other conferences. He has also served as an Associate Editor of journals like Springer's NetMAHIB and SNAM.

CSEB 2021

1. Canadian Society for Epidemiology and Biostatistics (CSEB) 2021 Virtual Conference (with a theme of "meeting the demand of a rapidly changing world") is held June 01-03, 2021 (mostly 11h-16h15 EDT (UTC-4) = 10h-15h15 CDT (UTC-5) in a synchronous mode with concurrent sessions.
2. Electronic poster presentation

ID: 13

Preprocessing methods to prepare unstructured text data for natural language processing: A scoping review

Marcello Nesca, University of Manitoba

Primary Area of Focus: Machine Learning & Artificial Intelligence Methods (Neural Networks, Deep Learning, Natural Language Processing, Unstructured Data)

Secondary Area of Focus: Epidemiologic Methods (Study Designs, Ethics, Data Quality, Record Linkage, Cohort Studies)

Please select which type of submission best describes your abstract: Works Completed or in Progress

Objectives: Our objective was to describe practices to preprocess UTD for applications of NLP methods.

Methods: We conducted a scoping review based on the Arksey and O’Malley framework. Our search strategy included the terms data quality, NLP, data preprocessing, and synonyms. The review included published empirical studies and review articles from 2000 to 2019 from Scopus, Web of Science, EBSCOhost, and ProQuest databases. The extracted information included characteristics of the article, features of the text data, preprocessing methods, data quality topics, and software.

Results or Preliminary Results: The search resulted in 1082 articles for title and abstract screening; 39 articles were selected for data extraction. Almost 90% of articles reported empirical research, and 59% were from computer science and engineering domains. Preprocessing of electronic medical records was reported in 20.5% of the articles. The most common preprocessing methods were those used to restructure and reorganize UTD, including tagging parts of speech such as nouns and verbs (46.2%), eliminating stop words with no inherent meaning (38.5%), and tokenizing sentences into individual words (28.2%). Less than one-quarter of the articles used an external dataset to validate the features of UTD.

Conclusion or Next Steps: Restructuring and reorganizing methods are commonly used to address UTD quality issues, but there appears to be little consensus about the choice of methods to apply to a dataset. The development of measures of UTD quality may be a useful step to guide the selection of preprocessing methods.

AuthorNames: Marcello Nesca, University of Manitoba; Lisa Lix, University of Manitoba; Carson Leung, University of Manitoba

First Name: Marcello

Last Name: Nesca

Organization: University of Manitoba

1. Rapid fire presentation

ID: 121

The Effect of Disease Co-occurrence Measurement on Multimorbidity Networks

Barret Monchka, University of Manitoba

Primary Area of Focus: Biostatistics (Statistical Methods, Modeling, Data Systems & Computer Software)

Secondary Area of Focus: Multimorbidity (Definitions of Multimorbidity, Complex Patients, Comorbidity)

Please select which type of submission best describes your abstract: Works Completed or in Progress

Objectives: Multimorbidity, the co-occurrence of two or more chronic diseases, is a complex phenomenon. Network analysis, a technique for describing relationships, is a potentially useful tool for multimorbidity analyses. Our objective was to compare chronic disease networks constructed using different measures of disease co-occurrence.

Methods: A retrospective cohort study was conducted using four years of Manitoba hospital and physician administrative records (2015/16 – 2018/19, 1.5 million individuals). Chronic disease diagnosis codes were grouped into 184 categories. Disease networks were constructed using seven co-occurrence measures: joint prevalence, relative risk (RR), phi (φ), lift, cosine, Jaccard, Kulczynski. Each network was limited to the 200 strongest associations. Disease importance was measured using degree centrality and limited to the top 20. Community detection, a technique for detecting highly-connected nodes (i.e., diseases), was used to identify clusters and similarity between networks was measured using the adjusted Rand index (ARI), with higher values indicating greater similarity. Network edges (i.e., relationships) were described using disease prevalence categories: low (<3%), moderate (3% to <13%), and high (≥13%).

Results or Preliminary Results: RR and lift disproportionately detected relationships between pairs of low prevalence diseases, while the majority of relationships identified using the other co-occurrence measures included moderate to high prevalence diseases. Networks had a median 50% agreement (Q1-Q3: 20%-70%) in their selection of the top 20 most central diseases, ranging from 95% agreement between Cosine and Jaccard to 0% between joint prevalence and lift. Disease clusters differed between networks with a median ARI of 0.08 (Q1-Q3: 0.06-0.26) and the number of clusters varied from 1 (joint prevalence) to 17 (phi).

Conclusion or Next Steps: Disease co-occurrence measures have a considerable effect on the structure of multimorbidity networks, including which diseases are considered influential and how disease clusters are defined. Co-occurrence measures should be selected considering research objectives and the prevalence relationships of greatest interest.

AuthorNames: Barret Monchka, University of Manitoba; Carson Leung, University of Manitoba; Lisa Lix, University of Manitoba

First Name: Barret

Last Name: Monchka

Organization: University of Manitoba

AINA 2021

35th International Conference on Advanced Information Networking and Applications (AINA-2021) was scheduled to be held May 12-14, 2021, in Toronto, Canada. Because of COVID-19 situation, it takes place online in a synchronous mode, with presentations and Q&A on Zoom. Day 1 (May 12) runs 10h-18h EDT (UTC-4), i.e., 09h-17h CDT (UTC-5). Day 3 (May 14) runs 06h30-15h30 CEST (UTC+2) = 13h30-22h30 JST (UTC+9), i.e., 23h30 (-1d)-08h30 CDT.

PAKDD 2021

25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2021) was scheduled to be held May 11-14, 2021, in Delhi, India. In response to the ongoing COVID-19 pandemic, it takes place in an online mode (mostly 08h30-19h IST (UTC+530, i.e., 22h (-1d)-08h30 CDT (UTC-5)) in a combined synchronous-asynchronous mode, with prerecorded video presentation on Webcon Events and live Q&A on Zoom Webinar via Webcon Events.

XAI for Predictive Analytics on Customer Turnover (2021)

Moamar Sayed-Mouchaweh: Prologue: introduction to explainable artificial intelligence. Explainable Artificial Intelligence within the context of Digital Transformation and Cyber Physical Systems: ch. 1 (1-8) (2021)

1.2.3 Chapter 4: Explainable Artificial Intelligence for Predictive Analytics on Customer Turnover

This chapter presents an interactive explainable artificial intelligence web interface that integrates and enhances the state-of-the-art techniques in order to produce more understandable and practical explanations to nontechnical end users. It is applied for the prediction of a financial institution’s customer churn rate. The Churn is the rate of customers who stopped using a service or product in a given time frame. It is used in business sector such as banking, retail, telecommunications, and education. The proposed explainable web interface combines visualization and verbalization. The visual screens display local and global features importance in order to provide users with the relevance of each feature to the decision made on a certain instance or on the global model. The verbalization is used as an alternative explanation other than the one provided by the visual screens. In addition, it is used as a recommendation to what to do in order to prevent a customer from leaving the company. The proposed explanation web interface is evaluated and compared with some well-known similar explanation tools, such as GAMUT, TELEGAM, and XAI Clinical Diagnostic Tool, using the following criteria: global explanation, local explanation, interactive (contrastive), search table, target instance capability, and the targeted audience.

Joglas Souza, Carson K. Leung: Explainable intelligence for predictive analytics on customer turnover. Explainable Artificial Intelligence within the context of Digital Transformation and Cyber Physical Systems: ch. 4 (47-67) (2021)

Abstract

Nowadays, machine learning techniques have become critical for decision-making mechanisms in numerous real-life applications in areas like healthcare, justice, transportation, and finance. However, recommendations made by machine learning techniques, as well as their logical reasoning behind these recommendation decisions, are often not easy to be comprehended by humans. In this chapter, we present an explainable artificial intelligence web interface that integrates and enhances the state-of-the-art techniques to produce more understandable and practical explanations to end users. To assure the practicality and usefulness of our explainable artificial intelligence web interface, we conduct a case study on applying the explanations to a random forest customer churn predictive model. Results showed that our solution delivers a satisfying number of functionalities when compared to similar approaches.

Keywords

Explainable artificial intelligence, Predictive analytics, Customer turnover, Customer churn, Interpretability, Machine learning

Frontiers' Big Data Networks AE

Dr. Carson K. Leung serves as an Associate Editor in the Board of Big Data Networks (specialty section of Frontiers in ICT, Frontiers in Digital Humanities, Frontiers in Big Data and Frontiers in Computer Science).

IEEE HITC

Dr. Carson K. Leung joined the TC Technical Board of IEEE Hyper-Intelligence Technical Committee

SNAM AE

Dr. Carson K. Leung serves as an Associate Editor in the Editorial Board of Social Network Analysis and Mining (SNAM) published by Springer.

USRA 2021

Several lab members won undergraduate student research awards:

- Each of the following students won a Faculty of Science Undergraduate Student Research Award (USRA) to conduct a full-time 16-week research project in the area of data mining under the academic supervision of Dr. Carson K. Leung:
  - - Third-year transit student Ms. Chenru Zhao, who is enrolled in B.C.Sc.(Hons.) program;
    - Third-year undergraduate student Mr. Nguyen Duy Thong (Jason) Tran, who is enrolled in B.C.Sc.(Hons.) program.
    - Third-year second-degree student Mr. Hao Zheng, who is enrolled in B.Sc.(Maj.) program. He won a FoS USRA last summer (2020) and conducted research in our lab.
- Graduating fourth-year student Mr. Connor Clark James Hryhoruk, who is enrolled in B.C.Sc.(Hons.) program, won a Philip Hultin Pedagogy Award to conduct a full-time 16-week development of pedagogy tools and curriculum development under the academic supervision of Dr. Carson K. Leung.
- Each of the following students won an UofM Vice-President (Research and International) Undergraduate Research Award (URA) to conduct a full-time 16-week research project under the academic supervision of Dr. Carson K. Leung. Among ~25,000 undergraduate students across the campus and ~400 applicants, they were two of 170 UM VP(RI)/UMSU URA winners:

- - Second-year undergraduate student Mr. Thanh Huy (Daniel) Mai, who is enrolled in B.C.Sc.(Hons.) program with major in CS and minor in Statistics.
  - Fourth-year undergraduate student Ms. Yan Wen, who is enrolled in B.Sc.(Maj.) program with double major in CS and Chemistry, and minor in Math. She won this award last summer (2020) and conducted research in our lab.

- Graduating Fourth-year undergraduate student Mr. Renz Marion Cabusas, who is enrolled in B.Sc.(Maj.) co-op program in CS, won an NSERC USRA to conduct a full-time 16-week research project on "A data science solution for big data mining and analytics" under the academic supervision of Dr. Carson K. Leung.
- Each of the following students was selected as a winner of a MITACS Globalink Internship awards:
  - - Third-year undergraduate student, Mr. Wenxuan Guo (郭文轩), who is enrolled in a B.S. program major in Computer Science and Technology from Beijing Institute of Technology (北京理工大学), China, was selected for the project on "Big data science and data analytics for useful information". He participated in the NCSU summer research program during Summer 2020.
    - Sixth-year undergraduate student, Mr. Jaime Solis-Soto, who is enrolled in a B.S. program in Computer Science and Technology from Instituto Tecnológico y de Estudios Superiores de Monterrey - Campus Chihuahua (TEC, Monterrey Institute of Technology and Higher Education (ITESM)), Mexico, was selected for the project on "Big data science and data analytics for useful information". He was an exchange student to The University of Texas at Austin during Winter 2020.

Research Manitoba Studentship

Congratulations to lab member, Daryl Fung (co-supervised by Dr. Carson K. Leung and Dr. Pingzhao Hu), on receiving a Research Manitoba Studentship.

UofM FoS Nexus 2021

1. UofM FoS Nexus 2021 Student Challenge Info Session
  1. On his Apr 28 UofM FoS Nexus 2021 Student Challenge Info Session, Dave Fulawka mentioned at 13:58-14:19 that
  2. "First of all, blessed to be a part of this [Student Challenge] ... Great to see some familiar faces. Carson Leung, hello. It's been a while since I've actually seen you face to face. And, so, we're excited to be part of this whole program. We're excited to be part of the conference, and excited to be in directly involved in the Student Data Challenge."
2. Lab members (MSc student Qi WEN, 3rd yr undergrad student Jason Tran, and 2nd yr undergrad student Daniel Mai) won first place in the UofM Data Science NEXUS Challenge sponsored by Bison Transport.
  1. - This week in the Faculty of Science May 24, 2021
      - Data Science Nexus Student Challenge Winners!
      - Over 50 students participated in this 2-week data science event, during which they had to provide a solution to a real-world challenge developed by one of our sponsors. In particular, congratulations to the teams that placed first for each challenge:
        Bison Transport: Qi Wen, Jason Tran, and Daniel Mai.
        Won $250 for their entry of "Addressing transportation network imbalances and improving profitability"
    - Congratulations to all the winners and all the participants!
    - On May 27 2021, University of Manitoba Faculty of Science wrote on Facebook (https://www.facebook.com/umanitobasci/photos/a.273275382709304/3953312838038855/) and LinkedIn (https://www.linkedin.com/posts/faculty-of-science-university-of-manitoba_umanitobasci-nexus2021-datascience-activity-6803681341125746688-kBfe/):
      - Congratulations to the winners of the Nexus Student Challenge! Over 50 students participated in this 2-week data science event, during which they had to provide a solution to a real-world challenge developed by one of our sponsors. In particular, congratulations to the teams that placed first for each challenge:
      - Bison Transport: Qi Wen, Jason Tran, and Daniel Mai.
      - Thank you to everyone who participated!
    - #umanitobasci #NEXUS2021 #datascience

Inha-BMSE

Dr. Carson Leung gave an invited talk about "big data analytics on COVID-19 epidemiological data" on Thu, April 15, 2021, at 10:30-11:30 KST (Wed, April 14, 2021, at 20:30-21:30 CST) as a part of 2021-1 Biomedical Science and Engineering Seminar I (맞춤형 헬스케어 융합세미나 Ⅰ) hosted by Inha University.

CFI 2021

1. UM Today News

https://news.umanitoba.ca/two-monumental-projects-to-impact-our-understanding-of-who-and-where-we-are/

Two monumental projects to impact our understanding of who, and where, we are

Canada Foundation for Innovation support will enable a new way to access information on Residential Schools, and for UM to take lead in international effort to better understand dark matter

MARCH 3, 2021—Researchers at the University of Manitoba are receiving a combined $4.7 million in funding for two projects that will fundamentally alter our understanding of our place in the world—one focuses on our history, the other, on trying to finally understand what our universe is mostly made of.

The Right Honourable Prime Minister Justin Trudeau today announced more than $518 million to support the infrastructure needs of universities and research institutions across the country, from the Canada Foundation for Innovation.

The UM projects involve national and international teams, one team led by Raymond Frogner, head of archives at the National Centre for Truth and Reconciliation (NCTR), and the other team led by professors Michael Gericke and Juliette Mammei (physics and astronomy).

"As the Member of Parliament for Winnipeg South, I am pleased that our federal government recognizes the world class talent and research being conducted at the University of Manitoba," said Terry Duguid. "Our investment today will support the National Centre for Truth and Reconciliation, as they work to construct a digital architecture for their archives, allowing for better access to the stories of Residential School Survivors. Federal funding will also support a second project which explores groundbreaking research on the universe and interactions between electrons in space. I am proud that our federal government is able to support these two important projects, which will have a profound impact on our community and our country."

Frogner and the extensive group of partners on the project will construct a ground-breaking digital architecture for the material held at NCTR that will put Survivor stories at the fore, allowing researchers, among other things, to identify the children lost at residential schools. Building on the work of the Truth and Reconciliation Commission, this project aims to create a new model of decolonizing archives to promote healing, learning and relationship building. ...

"The University of Manitoba is honoured to support the work of the National Centre for Truth and Reconciliation," says Digvir Jayas, vice-president (research and international) and Distinguished Professor. "The materials held within NCTR is of primary importance to Canada’s future and I commend NCTR on their efforts to reimagine how their archives can better serve all Canadians. Their project is a paradigm shift, envisioning new ways to decolonize information."

He continues: "... All Manitobans should feel an immense pride in their university for taking a lead on these two herculean projects."

The two team projects are:

Raymond Frogner received $2,411,773 for the project: "NCTR Digital Architecture."

This project implements the NCTR’s digital architecture. It will enable advanced discovery and access of digital archival records to promote innovative research meaningful to Indigenous communities and Survivors.

This CFI grant will allow for the construction of digital architecture for the NCTR archival holdings to build a decolonizing archive. The new IT Architecture will allow archivists to design a new records order, one based on the student’s and not the administrator’s office or function. The IT Architecture is moving research from the grand colonial metanarratives of statist social engineering, to the personal narratives of Survivors, their families and communities. This work will uniquely provide researchers materials to theorize oppression and disrupt the colonial relationships between academic researchers and Indigenous communities.

This digital infrastructure promotes reconciliation through acknowledgement. It is a recognition that we are now only what we choose to remember, but we are also what we choose to forget.

The project team members include:

1. 1. - Jonathan Dewar (First Nations Information Governance Centre)
    - Alan Katz (Manitoba Centre for Health Policy, UM)

- - - Carson Leung (Computer Science, UM)
    - Tricia Logan (Residential School History and Dialogue Centre, UBC)
    - Mary Jane McCallum (History, UWinnipeg)
    - Cary Miller (Native Studies, UM)
    - Ian Mosby (History, RyersonU)
    - Niigaan Sinclair (Native Studies, UM)

1. UM Today News

https://news.umanitoba.ca/nctr-reimagines-what-its-archives-can-be-do/?preview_id=144978

NCTR reimagines what its archives can be, do Will create a new international benchmark for making archives an agent of social change

MARCH 3, 2021 — The National Centre for Truth and Reconciliation (NCTR) is reimaging what its archives can be, and do, as it undertakes an ambitious project to restructure and decolonize its data, thanks to funding from the Canada Foundation for Innovation’s Innovation Fund.

Raymond Frogner, head archivist at NCTR, has received $2,411,773 for the national project team he will lead to rebuild the Centre’s digital architecture. The funding was announced on March 3, 2021, by the Honourable François-Philippe Champagne, Minister of Innovation, Science and Industry.

“The materials held within the National Centre for Truth and Reconciliation are of primary importance to Canada’s future and I commend the NCTR on their efforts to reimagine how their archives can better serve all Canadians. Their project is a paradigm shift,” says Catherine Cook, vice-president (Indigenous) at UM. “The University of Manitoba is honoured to support the work of the NCTR.”

Currently, NCTR has access to roughly 5 million documents, siloed in various bureaucracies of government and church offices. The information was originally gathered by these institutions to meet their colonial needs and there was never a need or desire to connect the data points in meaningful ways. This new project will take on the herculean task of finding the narrative held within these documents. It will shift the focus away from the institutions and onto the individuals: future archive users, for instance, will be able to follow one student from school, to hospital, to school, and anywhere else they were shuttled about by settlers.

“Residential schools were a social engineering project of the federal government to basically erase Indigenous cultures from the Canadian landscape,” says Frogner. “In one sense, the records held by NCTR are very much the institutional, administrative records of the colonial operation of these residential schools…. But these records are more than the administration records of schools. They record of some of the most profoundly important events in a child’s life, and to bring Indigenous voices to them, is to decolonize them.”

This project will take four years to complete and it will maintain ongoing engagement with Indigenous communities as the projects evolve. It includes many team members from multiple institutions including the University of Manitoba, the First Nations Information Governance Centre, the University of British Columbia, the University of Winnipeg, and Ryerson University, and the National Film Board of Canada.

Another example of how the information will be decolonized involves photographs. Many teachers took photographs from within the Residential Schools and the information attached to them comes only from the teacher. This new project will allow Survivors to explain the context of these images from their perspective, greatly expanding on our understanding of what took place.

“There was a time when we Survivors did not speak of our experience at Residential School,” says Levinia Brown, NCTR Survivor Circle Member. “Things are starting to change and we must honour those voices that were brave enough to share their pain. The work to be done through this grant is so important, not only because it preserves our words, but it will make them more available to all, including future generations. It is one crucial step we must take towards ensuring this history is not repeated.”

The open-source system to be developed will allow many other partners to access the data in meaningful ways.

Enter the Manitoba Centre for Health Policy (MCHP) in the Rady Faculty of Health Sciences, which has a decades-long track record of using anonymized health data to spotlight community health issues. As the NCTR organizes records around individual students, a single virtual case file will be created. MCHP will be able to use these new files to look at the contemporary downstream health and welfare legacies of the childhood trauma that was experienced in schools. This will be the largest such study ever undertaken (the Netherlands did similar work on the effects of WWII, but not to the extent this project entails).

NCTR will also hold training sessions to empower communities to statistically analyze the data held in this new format so that they can glean their own insights, enabling them to work with source material directly rather than asking for an academic to assist.

“Communities, survivors and family members still have so many unanswered questions about both what happened in residential schools as well as the intergenerational legacies of the residential school system,” says Ian Mosby, project team member and assistant professor of history at Ryerson University. “Even now, though, the archives where they might find answers are almost totally inaccessible to ordinary people. By making the data and archival materials held by the NCTR accessible to communities and community-affiliated researchers, then, we’re enabling communities and individuals alike to take control of their own history in a way that’s simply impossible right now.”

The project will create a new international benchmark in cultural heritage policy, Indigenous rights management, Indigenous research and education methodologies, and Indigenous perspectives on IT development.

“It recognizes that, like human rights and public memory, archives are socially constructed,” says Frogner. “This recognition carries responsibility for archives to reposition themselves as agents of social change.”

NCTR is also preserving its vast stores of audio-visual recordings—over 7,000 items—with the help of the project collaborator, the National Film Board of Canada, so that all recordings made by the Truth and Reconciliation Commission will be available for generations.

1. https://www.innovation.ca/about/press-release/major-investment-innovative-world-class-research-benefit-all-canadians

Archives to support reconciliation. We are what we choose to remember; but we are also what we choose to forget. A groundbreaking initiative led by the University of Manitoba will establish the digital architecture for the National Centre for Truth and Reconciliation’s archive of unique records. This digital archive will allow researchers to, among other things; identify the children lost at residential schools, which builds on the work of the Truth and Reconciliation Commission. It aims to create a new model of decolonizing archives to promote healing, learning and relationship building.

New digital archive will be a record of Canada’s residential school history

Archiving millions of documents to catalogue part of this country’s history and serve as a profound tool for understanding its legacy for Indigenous people

1. https://www.innovation.ca/story/new-digital-archive-will-be-record-canadas-residential-school-history

According to Raymond Frogner, “We are what we choose to remember. We are also what we choose to forget.”

That is the driving force behind a University of Manitoba project to build the digital architecture for the National Centre for Truth and Reconciliation. The centre is the archival repository for material collected by the Truth and Reconciliation Commission of Canada. It was created to compile the complete history and legacy of the country’s residential school system.

That amounts to more than five million documents — from different sources, in different formats and in different states of completeness. Using CFI-funded open-source relational database software and multiple servers for storage, Frogner and his team will build a content management system to provide access to these internationally unique records.

As the head of archives for the National Centre for Truth and Reconciliation at the University of Manitoba, Frogner’s goal is to promote a full acknowledgement of residential school history. It’s also to foster more informed dialogue of how Canada’s relationship with Indigenous peoples can be rebuilt on “principles of equality, human dignity and respect.”

Archival data can provide insight into the legacy of residential schools on the health and wellbeing of Indigenous people

Among other things, the digital architecture will allow researchers to identify the unmarked gravesites of children who died at residential schools. It will also let them create a statistical analysis of the health and welfare legacy of these schools.

Frogner, for example, is working with researchers at the Manitoba Centre for Health Policy to examine the effects of childhood trauma across generations. Such insights can then inform health, education and cultural heritage programs.

Frogner is particularly eager see researchers make use of the more than 7,000 witness testimonies from residential school survivors: “Nowhere else in the world is there a set of records at once so unique, meaningful and profound.”

“We are working with Indigenous communities to promote an understanding of these records,” says Frogner. “Hopefully to disrupt the colonial relationship between university researchers, academic institutions and Indigenous communities.”

Mitacs Accelerate 2021

Data analytics on city 311 information requests

https://www.mitacs.ca/en/projects/data-analytics-city-311-information-requests

In the current era of big data, huge volumes of a wide variety of data are generated and collected at a rapid rate. Embedded in these big data is implicit, previously unknown and potentially useful knowledge and information. This calls for data science—which use techniques like data mining, machine learning, etc.—for social good. With popularity of the initiates of open data, more data are made openly accessible to citizens. An example of these open big data is data collected at the 311 contract centre in the City of Winnipeg for the 311 information requests. In this research, we analyze and mine this dataset to find characteristics associated with the callers and the information requests. Knowledge on these characteristics helps users (e.g., decision makers at the City) to get a better understanding of the requests (e.g., why residents request information through 311 instead of other online options). In a longer term, the discovered knowledge and the understanding of the data helps improve the 311 and other online services. Along this direction, this research will add to the growing body of knowledge for all Canadian cities and communities.

Intern: Adam Pazdor

Faculty Supervisor: Carson Leung

Province: Manitoba

University: University of Manitoba

Partner: City of Winnipeg

Sector: Other services (except public administration)

Discipline: Computer science

Program: Accelerate

Decentralized services for sharing and searching user generated data

https://www.mitacs.ca/en/projects/decentralized-services-sharing-and-searching-user-generated-data

The existing model for applications and services on the internet is a centralized client server model where user information is under the control of the service provider. As such as centralized model, albeit cost-efficient and easy to maintain, has created dire consequences for humanity. Hence, for the proposed research project, we aim to provide tools and algorithms for a decentralized and location-aware experience on the Internet. Individuals, businesses, and institutions will make and qualify connections between one another by considering their trust for each other and the "network-trust" by way of vouching for others within the network. This new paradigm requires further research and development in areas including search, database, performance, and security, all within a decentralized environment to maximize our commercial and social impact.

Intern: Qi Wen

Faculty Supervisor: Carson Leung; Cuneyt Gurcan Akcora

Province: Manitoba

University: University of Manitoba

Partner: Protegra

Sector: Professional, scientific and technical services

Discipline: Computer science

Program: Accelerate

IEEE BigComp 2021

1. Dr. Carson K. Leung serves as a Publication Chair and on the Best Paper Award Committee for the 2021 IEEE International Conference on Big Data and Smart Computing (BigComp 2021), which was scheduled to held January 17-20, 2021, in Bangkok, Thailand. Due to COVID-19, it is relocated to Jeju Island (濟州島), South Korea, and held (mostly 08h30-19h KST (UTC+9), i.e., 17h (-1d)-04h CST (UTC-6)) as the hybrid of offline and online events. It takes place in a synchronous mode, with prerecorded video presentation and live Q&A on Zoom.
2. Dr. Carson K. Leung also serves the Chair/moderator and a panelist for a panel on "big data lakes: models, frameworks, and techniques".

IMCOM 2021

International Conference on Ubitquitous Information Management and Communications (IMCOM 2021) was scheduled to be held January 04-06, 2021, in Seoul, South Korea. Due to COVID-19, it is held (mostly 09h-13h45 KST (UTC+9), i.e., 18h-22h45 CST (UTC-6)) as a fully online conference in a combined synchronous-asynchronous mode, with prerecorded video presentation on Whova and live Q&A on Zoom via Whova. Lightning session is held with prerecorded video presentation and offline Q&A on Whova.

Census Data Analytics for Detecting Home Language Shifts

Wed. Jan 6, 2021 1:10 PM - 1:45 PM KST (Tue. Jan 5, 2021 10:10 PM - 10:45 PM CST)

Speaker

Carson Leung

Professor

University of Manitoba, Canada

In this video, we focus on census data analytics. Specifically, we analyze census microdata by exploring machine learning and data mining techniques---such as decision tree induction, random forest, and categorical naive Bayes---to study the influence of various social and economic factors on the probability that allophones adopt official languages as their language spoken at home. This study is a showcase where natural sciences and engineering (NSE) meet social sciences, in which NSE solutions (e.g., census data analytics) are applicable for the study of social science related phenomena (e.g., successful detection of shifts in home languages).

EOKAT (2021)

1. Table of contents by volume. Encyclopedia of Organizational Knowledge, Administration, and Technology (2020) ISBN 978-1-7998-3473-1
  - Volume IV
  - Section 11: Knowledge Management
2. Preface. Encyclopedia of Organizational Knowledge, Administration, and Technology: lvi-lxvi (2020) ISBN 978-1-7998-3473-1

SECTION 11: KNOWLEDGE MANAGEMENT

This section provides extensive chapters on knowledge harvesting, sharing and transfer. ... A closing chapter, "Big Data Analytics and Mining for Knowledge Discovery," authored by Prof. Carson Leung from the University of Manitoba, Canada, focuses on the discovery of organizational knowledge by mining through large collections of data, as well as discussing various methods that would assist in achieving this task.

1. Carson K. Leung: Big data analytics and mining for knowledge discovery Encyclopedia of Organizational Knowledge, Administration, and Technology (Vol. IV): 1817-1830 (ch. 125) (2021) ISBN 978-1-79983-473-1
2. Key Terms in this Chapter
  - Anti-Monotonic Constraint: A constraint C such that, if an itemset S satisfying C, then any subset of S also satisfies C.
  - Frequent Pattern (Or Frequent Itemset): An itemset or a pattern with its actual support (or expected support) exceeds or equals the user-specified minimum support threshold.:
  - Frequent Pattern Mining: A search and analy: - of huge volumes of valuable data for implicit, previously unknown, and potentially useful patterns consisting of frequently co-occurring events or objects. It helps discover frequently co-located trade fairs and frequently purchased bundles of merchandise items.
  - Big Data: High-velocity, valuable, and/or multi-variety data with volumes beyond the ability of commonly-used software to capture, manage, and process within a tolerable elapsed time. These Big data necessitate new forms of processing to deliver high veracity (& low vulnerability) and to enable enhanced decision making, insight, knowledge discovery, and process optimization.
  - Data Mining: Non-trivial extraction of implicit, previously unknown and potentially useful information from data.
  - MapReduce: A high-level programming model, which uses the "map" and "reduce" functions, for processing huge volumes of data.
  - Itemset: A set of items.
  - Succinct Constraint: A constraint C such that all itemsets satisfying C can be expressed in terms of powersets of a fixed number of succinct sets using the set union and/or set difference operators. A succinct set is an itemset, in which items are selected from the domain using the usual Structured Query Language (SQL) selection operator. In simple terms, a constraint C is succinct meaning that all and only those itemsets satisfying C can be explicitly and precisely generated using some precise "formula".
3. Index. Encyclopedia of Organizational Knowledge, Administration, and Technology: lxxii-civ (2020) ISBN 978-1-7998-3473-1
  - Banking; Big-Data; Business Analytics; Clustering; Competitive Advantage;
  - Data Analysis; Data Analytics; Decision Making; Events; Frequent Pattern Mining;
  - Graph; Healthcare; Human Resources (HR); JavaScript; Knowledge Discovery;
  - Knowledge Management (KM); MapReduce; Mining; Optimization; Shopping;
  - Tourism; Unstructured Data

Hoi's & Pazdor's Teaching

1. Calvin Hoi, an MSc alumnus from our lab, teaches COMP 4380 A02 (Database Implementation) in Winter 2021 on every Tuesday and Thursday at 2:30pm-3:45pm via on-line study from January 19 to April 15, 2021. By the end of Winter 2021, Hoi has taught COMP 4380 twice (in Winter 2020/2021).
2. Adam G. Pazdor, a graduate student in our lab, teaches:
  - COMP 4380 A01 in Winter 2021 on every Tuesday and Thursday at 4:00pm-5:15pm via on-line study from January 19 to April 15, 2021.
  - COMP 1012 in Summer 2021 on every Wednesday at 7:00pm-9:45pm via remote learning from May 12 to June 16, and continue from July 07 to August 11, 2021.
  - COMP 3380 in Fall 2021 on every Tuesday and Thursday at 4:00pm-5:15pm via on-line study from September 09 to December 09, 2021.

By the end of Fall 2021, Pazdor has taught a total of 17 sections of five distinct courses at all four undergraduate year-levels (COMP 1012 seven times in Summer 2016, Winter/Summer/Fall 2017, Fall 2018 & Winter 2019, Summer 2021; COMP 1020 in Winter 2020; COMP 2130 in Summer 2018; COMP 3380 in every Fall 2016/2017/2019/2020/2021; and COMP 4380 in Winter 2018/2020/2021).