Daksh Mittal
Google Scholar CV LinkedIn Mail
Embedded Files
I am a fourth-year PhD student in the Decision, Risk and Operations Division at Columbia Business School where I am fortunate to be advised by Prof. Hongseok Namkoong and Prof. Jing Dong. My research lies at the intersection of AI and Operations, with a focus on developing methodologies for large-scale operational problems. In particular, I work on uncertainty quantification and reinforcement learning, aiming to develop agents capable of efficient exploration and adaptive decision-making. Prior to joining Columbia, I was a Research Associate at Tata Institute of Fundamental Research Mumbai, where I had the privilege of being advised by Prof. Sandeep Juneja.
Before pursuing research, I worked at Ministry of Skill Development and Entrepreneurship (Government of India) as an Assistant Director in the Indian Skill Development Services (selected through UPSC Engineering Services Examination), implementing programs under the Skill India Mission aimed at building vocational training ecosystems for students from economically disadvantaged backgrounds. Before that, I worked at Indian Oil Corporation Limited as an Operations and Maintenance Engineer, where I optimized pipeline scheduling to meet fuel demand across distribution stations in the Northeast India. I hold a B.Tech in Mechanical Engineering from Indian Institute of Technology, Delhi.
Publications & Preprints
Daksh Mittal, Shunri Zheng, Jing Dong and Hongseok Namkoong
★ Finalist, Service Science Best Student Paper Award, 2025
📖 Journal version submitted
📓 Preliminary version accepted at NeurIPS, 2025 MLxOR Workshop
Tommaso Castellani*, Naimeng Ye*, Daksh Mittal*, Thomson Yen*, Hongseok Namkoong
Under Submission
Daksh Mittal*, Leon Li*, Thomson Yen*, Daniel Guetta and Hongseok Namkoong
📓 Accepted at NeurIPS, 2025
Mike Li, Daksh Mittal, Hongseok Namkoong, Shangzhou Xia
📖 Major Revision in Mathematics of Operations Research
Daksh Mittal*, Yuanzhe Ma*, Shalmali Joshi and Hongseok Namkoong
📖 Journal version submitted
📓 Conference version accepted at NeurIPS, 2024
Daksh Mittal, Sandeep Juneja, Shubhada Agrawal
📖 Journal version submitted
📓 Accepted as an extended abstract in ACM SIGMETRICS Performance Evaluation Review, 2023
📓 Accepted for oral presentation at Workshop on Autonomous Agents for Social Good (AASG), 2023
Sandeep Juneja, Daksh Mittal
📓 Accepted at Winter Simulation Conference, 2022
Working Papers
Sequence models for Bayesian Adaptive MDPs
Daksh Mittal, Eric Chen, Hongseok Namkoong and Assaf Zeevi
Smoothed-pathwise gradient for Markov Chains
Daksh Mittal, Ethan Che, Peter Glynn and Hongseok Namkoong
Strategic AI Deployment in the Workplace: A Signaling Game Approach
Daksh Mittal*, Naimeng Ye*, Rachel Cummings
Under Review
Technical Reports
Prahladh Harsha, Sandeep Juneja, Daksh Mittal, Ramprasad Saptharishi
Sandeep Juneja, Daksh Mittal
Sandeep Juneja, Daksh Mittal
Achintya Eeshan, Sandeep Juneja, Daksh Mittal, Amey Noolkar, Ramprasad Saptharishi, Piyush Srivastava
Page updated
Google Sites
Report abuse