AWS Credit Grants – Cornell’s Center for Data Science for Enterprise and Society
Finalist, 2023 INFORMS DMDA Workshop Best Paper Competition – Theoretical Track
Winner, 2021 INFORMS Pierskalla Best Paper Award
Winner, 2021 CHOW Best Student Paper in OR/MS
Finalist, 2019 INFORMS IBM Service Science Best Student Paper Award
Tata Consultancy Services Fellowship, Tepper School of Business, CMU, 2020
Ann Kirsten Pokora Prize, Department of Mathematics, Smith College, 2017
Background
Assistant Professor in the School of Operations Research and Information Engineering and Cornell Tech at Cornell University
Field member of ORIE, Center for Applied Mathematics (CAM), Statistics, ECE, and CS
Affiliated with WCM Institute of AI for Digital Health
Aims to develop a robust, end-to-end framework for evidence-based personalized healthcare strategies that are statistically sound and practically feasible
Research emphasizes rigor, practical feasibility, efficiency, and interpretability
Motivated by high-stakes decision-making, limited sample sizes, and minimal yet defensible statistical assumptions in healthcare
Research includes causal discovery from observational data, design of adaptive clinical trials (e.g., MRTs, N-of-1), and robust inference methods for non-adaptive, adaptive, and federated data
Translates research into practice through collaborations with clinicians on heart failure care, interpretable clinical LLMs, and diffusion models for single-cell genomics