I am on the job market!

A brief bio

• 2018-current: PhD student, EECS, MIT, advised by Prof. Devavrat Shah, Prof. Gregory Wornell, and Prof. Alberto Abadie
• Summer 2021: Research internship, Google Research, hosted by Johannes Ballé, Lucas Theis, and Peter Kairouz
• Summer 2020: Research internship, IBM Research, hosted by Kush Varshney
• 2014-2018: B.Tech, EE, IIT Bombay, advised by Prof. Nikhil Karamchandani
• Summer 2017: Research internship, EPFL, hosted by Prof. Michael Gastpar
• Research Interests: Causal Inference, Statistical Inference, Algorithmic Fairness

For a detailed bio, please see the Bio tab.

News

• February 2024: Paper on Doubly Robust Inference in Causal Latent Factor Models available on arXiv
• January 2024: Received the best presentation award, Laboratory of Information & Decision Systems (LIDS) student conference, MIT
• September 2023: Paper on front-door adjustment beyond Markov equivalence with limited graph knowledge accepted at NeurIPS
• June 2023: Papers on front-door adjustment beyond Markov equivalence with limited graph knowledge and group fairness with uncertainty in sensitive attributes accepted at ICML Workshop on Spurious Correlations, Invariance, and Stability
• October 2022: Paper on counterfactual inference with unobserved confounding accepted at NeurIPS Workshop on Causality for Real-world Impact
• July 2022: Research on fair selective regression covered by MIT News
• July 2022: Selected as an outstanding reviewer (top 10%) at ICML (list)
• May 2022: Paper on fair selective regression accepeted at ICML
• February 2022: Selected as a top reviewer (top 10%) at AISTATS (list)
• January 2022: Papers on finding back-door sets under unobserved confounding with minimal DAG knowledge and compressing differentially private algorithms accepted at AISTATS

 

 

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