talks
invited talks and keynotes
Here’s a short bio that can be used for talks. There’s also a longer, academic one for workshops and organizing committees.
Amit Sharma is a Principal Researcher at Microsoft Research India, focusing on integrating causal inference with machine learning to enhance AI systems’ generalization, explainability, and reasoning abilities. He developed the DiCE algorithm for counterfactual explanation and automated refutation methods for evaluating causal estimates, which have received over a thousand citations. The related open-source libraries, DiCE and DoWhy, have been downloaded millions of times and are widely used in both academia and industry. Amit is also the co-founder of PyWhy, an open-source ecosystem advancing scalable causal ML tools. His work has received numerous awards, including the NASSCOM AI GameChangers award, Yahoo! Key Scientific Challenges award, and the Honda Young Engineer and Scientist award.
Long Bio
Amit Sharma is a Principal Researcher at Microsoft Research India, focusing on integrating causal inference with machine learning to enhance AI systems’ generalization, explainability, and reasoning abilities. He developed the DiCE algorithm for counterfactual explanation and refutation methods for evaluating causal estimates, which have received over a thousand citations and are widely adopted in both academia and industry. The related open-source libraries, DoWhy for causal inference and DiCE for counterfactual explanations, have been downloaded by millions of users and are used to impact government policy, health outcomes, and business decisions globally. Amit is also the co-founder of PyWhy, an open source ecosystem that brings together a global team of researchers and practitioners towards the dream of building scalable, end-to-end causal machine learning tools (and more ambitiously, a “causal assistant” of the future). His work has received many awards including the 2023 NASSCOM AI GameChangers award, Best Paper Award at ACM CHI 2021 conference and Best Paper Honorable Mention at ACM CSCW 2019 and 2016 conferences. He has also received the 2012 Yahoo! Key Scientific Challenges Award and the 2009 Honda Young Engineer and Scientist Award. Beyond his research, Amit plays a significant role in the machine learning community, serving as an Associate Editor for IEEE TPAMI journal, Area Chair for premiere ML conferences such as NeurIPS and ICML, and Action Editor for the TMLR journal.| Date | Talk Title | Event | Venue | Links |
|---|---|---|---|---|
| Dec 2024 | Teaching causal reasoning to language models | Invited talk: NeurIPS Workshop on Causality+LLMs | Vancouver, Canada | Slides |
| Sep 2023 | Causality and large language models: A new frontier | Keynote: AI, Causality and Personalised Medicine Symposium | Hannover, Germany | Slides |
| Sep 2020 | Causal inference in recommender systems | Invited talk: ACM RecSys Workshop on Bandit and RL from User Interactions | Online | Slides |
| Sep 2019 | The impact of computing systems | Causal inference in practice | Invited lecture: Expanding the horizons of HCAI Summer School | New Delhi, India | Slides |