Principal Investigator

Nidhi Hegde
Associate Professor, Computing Science
Canada CIFAR AI chair and Fellow at Amii

Postdoctoral Researcher

Bingshan Hu
Bingshan works on the theoretical side of machine learning, particularly, Thompson Sampling-based learning algorithms for sequential decision making problems. Her research interests include Multi-armed bandits and Reinforcement Learning theory, Differentially private online learning algorithms.

Research Assistant

Kirby Banman

Graduate Students

Deep Gandhi (MSc, 2022 – )
Deep has worked on debiasing language models using the FineDeb approach to finetune large language models and mitigating biases for demographics such as gender, race, and religion. His research interests lie in the areas of Fairness in ML and Natural Language Processing.

Amir Bahmani (MSc, 2022 – )

Aniket Sharma(MSc, 2022 – )
Evaluation of fairness metrics in the outcome of machine learning for education and learning.

Undergraduate Students

Abeer Waheed (BSc, 2021 – )

David Parise (BSc, Summer 2023)

Collaborators

Gisele Arevalo (2022—2023, supervised by Carrie Demmans Epp)
Literature Review on Ethics in AI and Education.

Alumni

Liam Peet-Pare (MSc, 2020—2022, co-supervised by Nidhi Hegde and Alona Fyshe)
Currently at Peter A. Allard School of Law at UBC

Fatemeh Tavakoli (MSc, 2021 – 2023)
Currently at Vector Institute
Federated Learning on non-disjoint Graphs

Mira Patel (Undergraduate, Summer 2022)
Games to learn about fairness in ML.

Ronan Sandoval (Undergraduate, Summer 2022)
Games to learn about fairness in ML.