Research Interests
- Big Data Analytics and Machine Learning,
- Responsible Data Science and AI
- Data-Driven Systems and Stream Processing
- Web Search, Graph Data and Knowledgebases
- Data Quality and Data Integration
“The world’s most valuable resource is no longer oil, but data.” –The Economist, Leaders Section
Future Students
Data Science Lab is hiring again.
We are looking for talented graduate students in the broad areas of Big Data Analytics / Machine Learning / Data Science. Please, send an e-mail if you are interested in applying.
Awards
- Research Enhanced Faculty within Connected Minds: Neural and Machine Systems for a Healthy, Just Society (2023)
- Appointed till 2030 with $100K research startup support and an additional $25K per year of research allowance
- Supported by the Canada First Research Excellence Fund (CFREF) and 50+ industry, hospital, and community partners
- IBM CAS Faculty of the Year (2023)
- Best Paper Honourable Mention at the ACM CIKM conference (2022)
- BLUTune: Query-informed Multi-stage IBM Db2 Tuning via ML
- STU CLARK Distinguished Speaker Series Asper School of Business (2022)
- Runner-up IBM CAS Project-of-the-Year (2021)
- Dean’s Award for Academic Excellence (2019)
- IBM CAS Faculty Fellow (2017)
- IBM CAS Research Student-of-the-Year (2013)
- CeBIT Business Award for Innovation (2007)
- OCEAN GenRap Tool (ERP Optima)
Current and Past Collaborators
- Divesh Srivastava (AT&T Lab-Research)
- Vincent Corvinelli, Wenbin Ma, Piotr Mierzejewski, and Calisto Zuzarte (IBM Lab)
- Lukasz Golab and Ihab Ilyas (University of Waterloo)
- Fei Chiang (McMasters)
- Michael Böhlen (University of Zurich)
- Renée Miller (University of Toronto)
- Aijun An, Parke Godfrey and Jarek Gryz (York University)
- Ebrahim Bagheri, Mehdi Kargar, and Morteza Zihayat (Toronto Metropolitan University)
- Amirali Abari and Ken Pu (Ontario Tech University)