Computer Science and Information Technology, RMIT University
School of Computing and Information Systems, University of Melbourne
Contact: firstname dot lastname AT either of the above two affiliations
I am looking for PhD/master students to work with me on demanding Urban Data Analytics projects under my civil computing team. If you are a highly motivated student and interested in doing big data research, please contact me (see prospective students).
I obtained my PhD in computer science from National University of Singapore (NUS), and was the winner of the Best PhD Thesis Award. I hold an honorary fellow position at University of Melbourne and a senior lecturer position at RMIT. I am the Head of the Big Data and Database Group at the RMIT Center of Information Discovery and Data Analytics.
I am also the director of RMIT master of data science program, aiming to use Data Science to serve demanding data analysis needs from different sectors of RMIT and industry partners, with the goal of making our students Ready To Work.
My research is supported by Google (Two-time Google Research Award recipient), Australasian Research Council and Data61. I am generally interested in big data management, data visualization, information retrieval, and applied machine learning to each of the aforementioned topics. In particular, I propose the topic of Civil Computing and has made contributions in developing interactive visualized data exploration frameworks to bring big data back to a human scale, to make big data empower everyone for optimal decision making.
March: We are grateful to a new Google Research Award. Thanks Google!
- Sep: Our paper "Trajectory-driven Influential Billboard Placement" is selected as one of the Best Papers of SIGKDD 2018.
our paper "Trajectory-driven Influential Billboard Placement" has been accepted as a full paper for long presentation in ACM SIGKDD18 research track (acceptance rate: 10.8%, 107 out of 983) [Video] [paper] [tech report]
- April: Three ACM SIGMOD 2018 demo papers accepted
DITA: A Distributed In-Memory Trajectory Analytics System
POISam: An Efficient Object Selection System for Interactive and Visualized Exploration of Geospatial Data (online demo)
- Two Tier-A* ACM WSDM 2018 papers accepted
S. Wang, Z. Bao, S. Huang, R. Zhang. A Unified Processing Paradigm for Interactive Location-based Web Search. WSDM 2018.
- Two Tier-A* ACM SIGMOD 2018 papers accepted!
Z. Shang, G. Li, Z. Bao. DITA: Distributed In-Memory Trajectory Analytics. SIGMOD 2018.
I am highly interested in how to make data usable to data consumers, and make the implementation of such usability module as efficient and generalized as possible. In particular, I have been playing actively in:
- Data Visualization & Visualized Data Exploration
- Trajectory Data Mangement
- Geo-located Data Integration and Cleaning
- Spatio-Textual query processing
Google Faculty Award 2015
Singapore Infocomm Development Authority Medal 2011
Best PhD Thesis Award of Class of 2011 (The only winner)
School of Science PhD Supervision Award 2017
Teaching Excellence Award of RMIT College of SEH, 2017
ADC 2017 Best Paper Award
DASFAA 2017 Best Student Paper Runnerup Award
ADC 2016 Best Student Paper Award
ADC 2016 Best Demo Paper Award
Best Paper Nomination:
The 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018)
The 23rd ACM International Conference on Information and Knowledge Management (CIKM 2014)
The 33rd International Conference on Conceptual Modeling (ER 2014) - Best Student Paper Award Nomination
The 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
Selected Professional Services (more)
ER 2018 (Demo Track)
ADMA 2017 (Demo Track)
DASFAA 2017 (Workshop Track)
APWeb 2016 (demo track)
ADMA 2016 (Best Paper Award Committee)
Program Committee of recent Tier-A* International Conferences:
2019 - ICDE, EDBT
2018 - SIGMOD, VLDB, ICDE, SIGIR, CIKM