CV
Awards, talks, experience, and service. Positions, education, and research interests are on the home page; papers are on the publications page.
Honors and Awards
Top Reviewer Award, NeurIPS
2025
Community in Curriculum Award, Daniels School of Business, Purdue University
2025
Finalist, INFORMS Data Mining Best Paper Competition (General Track)
2022
Joe Newton Best Poster Award, Conference on Advances in Data Science: Theory, Methods and Computation
2022
Travel grants: Sustainable Horizons Institute (SIAM CSE21 and BE program); PGSG (INFORMS 2020, NeurIPS 2020)
2020–2021
Other Experience
Graduate Research Assistant, School of Industrial Engineering, Purdue University
Variational inference for stochastic programming; large deviations analysis of sample average approximation
2017–2020
Assistant Manager, Engineering & Projects, Bharat Petroleum Corporation Ltd., India
2012–2016
Research Assistant, Centre for Advanced Composites Manufacturing, University of Auckland, New Zealand
2011
Invited Talks
“Bayesian methodologies for data-driven decision-making,” Department of Industrial and Systems Engineering, University of Tennessee, Knoxville
Apr 2024
“Bayesian methodologies for data-driven decision-making,” Industrial & Systems Engineering Program, University of Cincinnati
Dec 2023
“Bayesian methodologies for data-driven decision-making,” Department of Statistics, Indiana University, Bloomington
Dec 2023
“Variational Bayesian method for stochastically constrained system design problem,” Young European Queueing Theorists Workshop, EURANDOM, TU Eindhoven
Oct 2019
“Variational Bayes for data-driven newsvendor problem,” Conference on Data Science for Business and Economics, Purdue University
May 2018
Conference Presentations
“Learning when to trust in observational data: deconfounded transfer for online decision-making”
INFORMS Annual Meeting (Nov 2026); INFORMS Healthcare Conference (Jul 2026); POMS Annual Conference (May 2026)
2026
“Generalized regret analysis of Thompson Sampling using fractional posteriors”
Conference on Advances in Data Science (Oct 2022); INFORMS Annual Meeting (Oct 2022); TTIC Summer Workshop on Online Decision Making (Jul 2022)
2022
“Statistical inference for approximate Bayesian optimal design,” Winter Simulation Conference
Dec 2020
“Variational inference for Bayes optimal design,” INFORMS Annual Meeting
Nov 2020
“Variational inference for risk-sensitive decision-making,” NeurIPS Workshop on Safety and Robustness in Decision Making
Dec 2019
“Variational Bayesian method for stochastically constrained system design problem,” INFORMS Annual Meeting
Oct 2019
Service
Search Committee, Clinical Assistant/Associate Professors, Daniels School of Business
2025
Reviewer, journals: Journal of Machine Learning Research; Journal of the American Statistical Association; IISE Transactions; Stochastic Systems; Optimization Letters
Reviewer, conferences: NeurIPS; ICML; AISTATS; AAAI; UAI
Member: INFORMS; Production and Operations Management Society (POMS)