Projects
- Provincial (British Columbia) Surveillance of Healthcare Associated Infections
PICNet, in collaboration with the six BC health authorities, conducts provincial surveillance of three healthcare-associated infections: Clostridioides difficile infection (CDI), Carbapenemase-producing organisms (CPO), and Methicillin-resistant Staphylococcus aureus (MRSA). We also produce provincial reports on hand hygiene compliance (HCC). Reports are published quarterly in our website.
I supported the team by analyzing incidence and trends, and developing an interactive dashboard for in-house use. The dashboard is helpful in visualizing KPIs from varying fiscal years, and regions. I used R-shiny app to create the dashboard.
- Visualization of Provincial (British Columbia) Child-Emergency-Department-visits with suspected Viral Respiratory Illness (VRI) Symptoms
I developed an R Shiny app to interactively visualize counts and proportions of Child-Emergency-Department-visits with suspected Viral Respiratory Illness (VRI) Symptoms, of province of British Columbia. This app is developed within the virtual machine of PANDA (Platform for Analytics & Data) platform native to Provincial Health Services Authority (PHSA). It is a unique solution where real-time data is extracted from the provincial Covid-19 data nested in a Microsoft Azure (cloud-based) SQL-based platform, and required indicators are presented interactively by Surveillance Seasons, Epidemiological Weeks, Health Authorities, Individual Facilities, and Age groups.
The aim of the dashboard is to assist the PICNet (Provincial Infection Control Network of British Columbia) Surveillance team to track, monitor and report VRI Child-Emergency-Department-visits more efficiently.
This is a 6-credit-Capstone-project with the team of Population Health Surveillance and Epidemiology, Office of the Provincial Health Officer, Province of British Columbia, as a requirement for graduation of Master of Data Science (MDS) Program of UBC, Vancouver.
MDS Team member:
Jessie Wong, MDS Candidate
Jennifer Hoang, MDS Candidate
Shengting (Irene) Yan, MDS Candidate
Daniel Chen, MDS Faculty (Mentor)
Team-members from the stakeholder team (Population Health Surveillance and Epidemiology, Office of the Provincial Health Officer, Province of British Columbia) :
Henry Ngo, Data and Analytics Lead
Kayla McLean, Data Scientist
Fernanda Ewerling, Epidemiologist
Xibiao Ye, Director of Epidemiology
The project is completed and delivered on June 2022.
Data analysis project, as a deliverable for a course in the Master of Data Science program at the University of British Columbia. This is a group project with:
Dongxiao Li, MDS Candidate
Kyle Maj, MDS Candidate
Develop a python package which takes in twitter data, cleans, analyzes and plots findings relating to hashtags, sentiments and word counts. This team-work is in it's draft shape and a work-under-progress, as we refine it according to requirements of our Master of Data Science course at UBC, Vancouver. This is a group project with:
Mahsa Sarafrazi, MDS Candidate
Shiva Shankar Jena, MDS Candidate
Amir Abbas Shojakhani, MDS Candidate
Develop an R package which takes in twitter data, cleans, analyzes and plots findings relating to hashtags, sentiments and word counts. This team-work is in it's draft shape and a work-under-progress, as we refine it according to requirements of our Master of Data Science course at UBC, Vancouver. This is a group project with:
Mahsa Sarafrazi, MDS Candidate
Shiva Shankar Jena, MDS Candidate
Amir Abbas Shojakhani, MDS Candidate
Develop a dashboard using dash and R, using kaggle dataset which visualizes North American and global sales and sales-related data, such as top publishers and top genres based on sales and market share based on sales by year. This is a deliverable for a course in the Master of Data Science program at the University of British Columbia. This is a group project with:
Alex Yinan Guo, MDS Candidate
Amelia Tang, MDS Candidate
Maeve Shi, MDS Candidate
Develop a dashboard using dash and python, using kaggle dataset which visualizes North American and global sales and sales-related data, such as top publishers and top genres based on sales and market share based on sales by year. This is a deliverable for a course in the Master of Data Science program at the University of British Columbia. This is a group project with:
Alex Yinan Guo, MDS Candidate
Amelia Tang, MDS Candidate
Maeve Shi, MDS Candidate
- Prevalence of confirmed Covid 19 cases, deaths and recoveries in Bangladesh, Egypt, Pakistan, and Indonesia: A snapshot of Bangladesh and inter-country comparison (Link)
A snapshot of the current burden of Covid-19 cases in Bangladesh. And a comparative cross-sectional analysis of Covid-19 (Daily confirmed cases, overall case-burden). between Bangladesh Egypt, Indonesia and Pakistan. This is an independent initiative. The project is not relevant to the authors' current professional attachments.
Education
Mila - Quebec Artificial Intelligence Institute, Montreal, Quebec, July 17 – 21, 2023
Incorporating Ethical AI in Machine Learning Development : Margaret Mitchell
Introduction to Neural Networks : Sarath Chandar
Markov Decision Process and Planning | Intro to RL: From Planning to Learning : Doina Precup
Deep learning for Visual Perception : Christopher Pal
Introduction to Optimization : Gauthier Gidel
Policy Search : Nicolas Le Roux
Model-based RL : Erin Talvitie
Deep Learning for NLP : Wenhu Chen
Intro to Ethics | Responsible AI : Golnoosh Farnadi
Machine Learning for Scientific Discovery : Yoshua Bengio
Causality : Dhanya Sridhar
Deep RL : David Meger
Exploration-Exploitation/Bandits : Audrey Durand
Intro to GNNs : Petar Veličković
AI for Health : Marzyeh Ghassemi
Better experiments/methods in RL (Empirical aspects of RL) : Marlos Machado
Recent advances in Generative Models and vision : Su Wang
Robustness & safety in RL : Marek Petrik
Robot Learning (embodied AI) : Glen Berseth
Multi-agent and Social RL : Marc Lanctot
AI in Quantum Physics : Stefanie Czischek
Multimodal AI : Paul Liang
- Master of Data Science, Department of Statistics and Department of Computer Science, University of British Columbia, Vancouver, BC. 2022
DSCI 521 : Computing Platforms for Data Science
DSCI 511 : Programming for Data Science
DSCI 523 : Programming for Data Manipulation
DSCI 551 : Descriptive Statistics and Probability for Data Science
DSCI 571 : Supervised Learning I
DSCI 531 : Data Visualization I
DSCI 552 : Statistical Inference and Computation I
DSCI 512 : Algorithms and Data Structures
DSCI 561 : Regression I
DSCI 573 : Feature and Model Selection
DSCI 522 : Data Science Workflows
DSCI 513 : Databases and Data Retrieval
DSCI 572 : Supervised Learning II
DSCI 562 : Regression II
DSCI 542 : Communication and Argumentation
DSCI 524 : Collaborative Software Development
DSCI 553 : Statistical Inference and Computation II
DSCI 532 : Data Visualization II
DSCI 563 : Unsupervised Learning
DSCI 574 : Spatial and Temporal Models
DSCI 575 : Advanced Machine Learning
DSCI 541 : Privacy, Ethics and Security
DSCI 525 : Web and Cloud Computing
DSCI 554 : Experimentation and Causal Inference
DSCI 591 : Capstone project
BC Chronic Disease Visualization and Trend Analysis with R Shiny
- Undergraduate Non-Degree credited courses, Department of Computer Science and Department of Mathematics, Independent University, Bangladesh, Dhaka, Bangladesh: 2021
CSC101 and CSC101L : Introduction to Computer Programming and Lab
MAT104 : Calculus and analytical geometry
MAT203 : Linear Algebra - vectors and matrices
Affiliations
International Statistical Institute: Regular member
American Statistical Association: Regular member
Data Visualization Society: Basic member
The Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM) : Member
Association for the Advancement of Artificial Intelligence (AAAI): Member
UBC Data Science and Health: Cluster member
Workshops and Certifications
18 January 2022
Data Science and Health 2021: Impact and Lessons Learned From the Covid-19 Pandemic
UBC Data Science and Health 2021
Credits: 9
Continuing Professional Development Conference at Vancouver, BC
Interactive, three-part Continuing Professional Development (CPD) program addressing the intersection of health and data science, designed to enable engagement and collaboration with data scientists and provide a practical roadmap for applying data science and analytics in understanding and adapting to the recent unprecedented changes in health care research and delivery.