Computational & Quantitative Social Sciences
DSI@UTSC

The DSI at the University of Toronto Scarborough, DSI@UTSC, is leading a tri-campus initiative to encourage research activity in Computational and Quantitative Social Sciences (CQSS) that includes community-building, seed funding, and training in CQSS.

The social sciences are undergoing a data sciences revolution spurred on by new statistical and algorithmic techniques, rapid advances in high-performance computing, and the proliferation of large, complex, and heterogeneous data structures (e.g., spatial, relational, temporal, and textual). These developments present exciting opportunities as well as new challenges for social scientists.

Join us for talks, workshops, and other events that explore the impact of the data sciences revolution on the social sciences across U of T and beyond.

News & Events

AI for Qualitative Research Workshop
November 20, 2025

learn more & register

Computational & Quantitative Social Sciences Grant
Seed funding for cutting-edge, high-impact research in the area of computational and/or quantitative social science.
Learn more and apply

Blitz Workshops
Researchers present lightning round of talks with opportunities for discussion and networking.

Social Sciences Methods Training Day
CQSS Methods Training Days consist of focused workshops designed to improve and innovate research practices in the social sciences, humanities, and related fields.

CQSS awards

Deficits of migration in the age of Covid-19: A new approach to studying changing migration patterns.
Monica Alexander (Department of Statistical Sciences, Faculty of Arts and Science, University of Toronto)

New Money in the New Economy: The Shift to Stock-Based Compensation and Wealth Inequality.
Angelina Grigoryeva (Department of Sociology, University of Toronto Scarborough, University of Toronto)

What Do Fake News and Biased News Look Like? A Text-Analysis and Machine-Learning Approach.
Spike W. S. Lee (Joseph L. Rotman School of Management, University of Toronto)

Deep Learning in Archaeology and Paleoethnobotany: Imaging Phytolith Training Data.
Monica Ramsey (Department of Anthropology, University of Toronto Mississauga, University of Toronto)

Social and Behavioural Determinants of Health in Prognostic Machine Learning Models for Patient Outcome Prediction.
Zahra Shakeri (Institute of Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto)