Hi! I am a research associate on the Google Brain team in Montreal and a graduate student in Computer Science at Mila and Université de Montréal co-advised by Laurent Charlin and Hugo Larochelle. I am also the initiator and co-organizer of the Algorithmic Fairness through the lens... workshop series at NeurIPS (afciworkshop.org)
My research interest is at the intersection of machine learning and causality with a focus on improving fairness, interpretability and reliability properties of ML models and treatment effect estimation methods.
Excited to organize a 3rd edition of our workshop on Algorithmic Fairness at NeurIPS 2022 (details at Algorithmic Fairness through the lens of Causality and Privacy)!
I am Program Chair for the Montreal AI Symposium 2022. Looking forward to helping organize this great conference!
Honoured to be invited to participate in the Interpretable Machine Learning program at the Simons Institute for the Theory of Computing, UC Berkeley this summer.
The proceedings at PMLR for the Algorithmic Fairness through the lens of Causality and Robustness workshop is out!
New review paper on transportability of causal effects using RCT and observational data!
Excited to co-organize a second edition of the AFCI workshop at NeurIPS 2021. This year's edition will highlight work at the intersection of fairness with causality and robustness. More information at afciworkshop.org/afcr2021
Joined the SAMSI (Statistical and Applied Mathematical Sciences Institute) working group on Causal Inference and Missing Data!!
I am co-organizing a workshop on "Algorithmic Fairness through the lens of Causality and Interpretability " at NeurIPS 2020. Check afciworkshop.org for more details.
I am happy to share my "Path to Google" interview with the Google blog.
Joined the first cohort of AI residents in the Google Brain team in Accra, Ghana!