2022.07.25: Talk on necessity of causal inference for out-of-distribution generalization in prediction and decision-making at the Technion, Israel. [Slides]
2021.12.02: Talk on Causal Inference for Machine Learning: Generalization, Explanation and Fairness; at the UK Office for National Statistics. [Slides]
Data tells stories. My research aims to tell the causal story.
As machine learning systems move into societally critical domains such as healthcare, education, finance and criminal justice, questions on their impact gain fundamental importance. The key insight in my work is to consider modern algorithms as interventions, just like a medical treatment or an economic policy. Unlike typical interventions studied in social and biomedical sciences, however, algorithmic interventions can be arbitrarily complex. I work on developing methods to estimate causal impact of such systems and build algorithms that optimize the causal effect. I am also passionate about designing new interventions for societal impact, especially in healthcare.
If you are interested in working with me at MSR India, drop me an email. We hire interns throughout the year. There are also postdoctoral positions available. Additionally, if you are an undergraduate or a masters student, our lab runs an excellent pre-doctoral Research Fellowship program.
PhD in Computer Science, 2015
B.Tech. in Computer Science, 2010