Aug '21: I have been selected as one of the 2021 MIT EECS Rising Stars.
Aug '21: I have a guest lecture at the RBCDSAI Bootcamp at the Indian Institute of Technology, Madras on Explainability in Healthcare: From application oriented approaches to ethics of deployment.
Jul '21: I gave an invited talk on the Ethics of developing ML in healthcare at the ICML Workshop on Challenges in deploying and monitoring Machine Learning systems.
Apr '21: Guest lecture on Causality Primer and Applications in ML in the Probabilistic Graphical Modeling graduate course at UIUC.
Mar '21: Guest lecture on learning robust recourses in the graduate course on Topics in Machine Learning: Interpretability and Explainability at Harvard.
Mar '21: Presented a tutorial at FAccT with colleagues Chirag Agarwal and Himabindu Lakkaraju on limitations of explainability methods in ML. Slides are here
Oct '20: Paper on active feature acquisition for causal effect estimation accepted to ML4H2020 NeurIPS Proceedings
Oct '20: Moved to Harvard as a CRCS Postdoctoral Fellow
Sep '20: Paper on feature attribution in time-series is accepted to NeurIPS 2020
Jul '20: Invited talk on Ethics for ML in Healthcare at Data Science Africa 2020
Mar '20: Guest Lecture on Fairness, Explainability in ML, AI and Society Class, McMaster University
Jan '20: Guest Lecture on Causal Inference in ML for Health Graduate Class UofT CS
Dec '19: Co-chairing the Fair ML for Health workshop @ NeurIPS 2020
Nov '19: Guest Lecture on AI and Ethics: Mathematical Foundations and Algorithms UofT CS
Nov '19: Invited talk on Ethics for ML in Health to The 99 AI Challenge cohort with University of Toronto Libraries
Nov ‘19: Invited talk CSI Departmental Seminar, Emory University, Atlanta, Georgia
Oct ‘19: Invited talk Data & Society Meeting at NYU on Evaluating Fairness for ML in Health
Aug ‘19: Invited talk at the inaugration of the Schwartz Reisman Institute for Technology and Society (SRIT&S)