The Data-Driven Censored Newsvendor Problem
Management Science (2026)
Accepted to Durham Early Career Scholars Workshop (2025)
ContactD237 Northwestern University Technological Institute |
Sean Sinclair is an Assistant Professor at Northwestern University in the Industrial Engineering and Management Sciences department. Previously he was a postdoctoral associate under Devavrat Shah and Ali Jadbabaie at Massachusetts Institute of Technology. Sean completed his PhD at Cornell University coadvised by Christina Lee Yu and Siddhartha Banerjee. His research focuses on developing algorithms for data-driven sequential decision making in societal applications. He bridges algorithmic techniques in reinforcement learning to an operations management perspective with an emphasis on models, data uncertainty, and objectives. Recent contributions include instance-specific optimal regret guarantees for nonparametric reinforcement learning, Pareto-optimal fair resource allocation, and data-efficient algorithms for cloud compute allocations. Complementing this, he also designs open-source code instrumentation and methodology to empirically analyze the multi-criteria performance of algorithms on these problems.
He graduated with a B.S. in Honours Mathematics and Computer Science from McGill University where he worked on a project with Tony Humphries. Before returning to graduate school he spent two and a half years teaching mathematics, science, and English in a small community in rural Ghana with the Peace Corps, and after worked at National Life as a financial analyst. Prospective Students: I am actively looking for Ph.D. students. However, Ph.D. admissions to Northwestern IEMS are handled at a department level and not by me individually. Prospective students with undergraduate backgrounds in applied mathematics, computer science, economics, or statistics are encouraged to contact me by email after reading here. See here for my advising commitments and expectations. |
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News
- Our paper "Offline-Online Reinforcement Learning for Linear Mixture MDPs" was accepted to NeurIPS 2026!
- New preprint of our paper "Sequential Fair Allocation and Routing in Nonprofit Operations" is available on arXiv.
- Our paper on "Sequential Fair Allocation With Replenishments: A Little Envy Goes An Exponentially Long Way" won the SIGMETRICS Best Paper Award!
- New preprint of our paper "Offline-Online Reinforcement Learning for Linear Mixture MDPs" is available on arXiv.
- New preprint of our paper "Non-Stationary Inventory Control with Lead Times" is available on arXiv.
- New paper on "Is Pure Exploitation Sufficient in Exogenous MDPs with Linear Function Approximation?" was accepted to ICLR 2026 and is available on arXiv.
- New preprint of our paper "Network and Risk Analysis of Surety Bonds" is available on arXiv.
- Our paper "Reinforcement Learning in MDPs with Information-Ordered Policies" with Zhongjun Zhang was selected as a finalist for the INFORMS George Nicholson Student Paper Competition.
- New preprint of our paper "Sequential Fair Allocation With Replenishments: A Little Envy Goes An Exponentially Long Way" is available on arXiv, and has since been accepted at SIGMETRICS (2026).
- New preprint of our paper "Reinforcement Learning in MDPs with Information-Ordered Policies" is available on arXiv.
- New preprint of our paper "The Data-Driven Censored Newsvendor Problem" is available on arXiv.
- New preprint of our paper "Multi-Objective LQR with Linear Scalarization" is available on arXiv.
- Started my position at Northwestern University in IEMS. Please reach out if you are in the area!
- New preprint of our paper "Online Fair Allocation of Perishable Resources" is on SSRN!
- Awarded a finalist for the George Dantzig PhD Dissertation award!
- Started my postdoc position at MIT in LIDS advised by Devavrat Shah and Ali Jadbabaie. Please reach out if you are in the Boston area and want to talk!
- My paper, "Hindsight Learning in MDPs with Exogenous Inputs" was accepted in ICML 2023!
- My paper, "Online Fair Allocation of Perishable Resources" was accepted in SIGMETRICS 2023!
- Accepted a postdoc position at MIT in LIDS advised by Devavrat Shah and Ali Jadbabaie!
- Accepted a position at Northwestern University in the Industrial Engineering and Management Science department as an assistant professor starting Fall 2024!
- My papers "Sequential Fair Allocation: Achieving the Optimal Envy-Efficiency Tradeoff Curve" and "Adaptive Discretization in Online Reinforcement Learning" were accepted to Operations Research!
- My paper, "Sequential Fair Allocation: Achieving the Optimal Envy-Efficiency Tradeoff Curve" is a finalist for the 2022 INFORMS DEI Best Student Paper Award!
- On August 23 I will be speaking at the Data Driven Decision Processes Bootcamp on Online Reinforcement Learning and Regret.
- In August 15-18 I will be speaking at the Summer Bootcamp at Kellogg on RL in Operations.
- This Fall I'll be a visiting graduate student at Simons Institute for the Data-Driven Decision Processes program.
- In June I'll be speaking at the Workshop on Algorithms for Learning and Economics and participating in a panel on Socially Responsible ML.
Selected Publications
Hindsight Learning in MDPs with Exogenous Inputs
ICML (2023)
Sequential Fair Allocation: Achieving the Optimal Envy-Efficiency Tradeoff Curve
Operations Research (2022)
Finalist for the 2022 INFORMS Diversity, Equity, and Inclusion Best Student Paper Award
Presented at ACM FORC (2022)