Billy Jin



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I will be joining the Quantitative Methods group in the Daniels School of Business at Purdue University as an Assistant Professor starting in 2025. I am currently a postdoctoral Principal Researcher at the University of Chicago Booth School of Business, working with Professor Baris Ata. I completed my Ph.D. in Operations Research and Information Engineering at Cornell University, where I was fortunate to be advised by David Williamson. I received my undergraduate degree from the University of Waterloo in 2018, majoring in Computer Science and Combinatorics & Optimization.

My research interests lie in the union of online decision-making, stochastic optimization, and approximation algorithms. A focus of my recent research has been on advice-augmented algorithms, which use some advice or prediction (e.g. from historical data, forecasts, or expert advice), whose quality is unknown. I aim to design algorithms that perform well when the quality is high, yet remain robust in their performance even when the quality is low.

My research has been recognized with several awards, including an NSERC graduate fellowship, the 2023 Student Paper Prize awarded by the INFORMS Decision Analysis Society, and runner-up in the 2023 Student Paper Prize awarded by the INFORMS Optimization Society. Additionally, I was awarded the Best Flash Talk at the 2019 YinzOR Student Conference.

Previously, I have been a quantitative trading intern at Jane Street Capital, and a software engineering intern at Wish.

Email bzj3 at cornell dot edu
Address Rhodes Hall 269
Cornell University
Ithaca, NY 14850
USA

Journal Papers Published

In all of my papers, the author ordering has been alphabetical.

A 4/3-Approximation Algorithm for Half-Integral Cycle Cut Instances of the TSP
Billy Jin, Nathan Klein, David P. Williamson.
• Mathematical Programming, 2025.
• A preliminary version appeared in Integer Programming and Combinatorial Optimization (IPCO), 2023.

The Two-Stripe Symmetric Circulant TSP is in P
Samuel C. Gutekunst, Billy Jin, David P. Williamson.
• Mathematical Programming, 2025.
• A preliminary version appeared in Integer Programming and Combinatorial Optimization (IPCO), 2022.

Sample Complexity Analysis for Adaptive Optimization Algorithms with Stochastic Oracles
Billy Jin, Katya Scheinberg, Miaolan Xie.
• Second Place for 2023 Student Paper Prize of INFORMS Optimization Society
• Mathematical Programmming, 2024.

High Probability Complexity Bounds for Adaptive Step Search Based on Stochastic Oracles
Billy Jin, Katya Scheinberg, Miaolan Xie.
• SIAM Journal on Optimization, 2024.
• A preliminary version appeared in Neural Information Processing Systems (NeurIPS), 2021.

Fluid Approximations for Revenue Management under High-Variance Demand: Good and Bad Formulations
Yicheng Bai, Omar El Housni, Billy Jin, Paat Rusmevichientong, Huseyin Topaloglu, David P. Williamson.
• Management Science, 2023.

A Combinatorial Cut-Toggling Algorithm for Solving Laplacian Linear Systems
Monika Henzinger, Billy Jin, Richard Peng, and David P. Williamson.
• Algorithmica, 2023.
• A preliminary version appeared in Innovations of Theoretical Computer Science (ITCS), 2023.

Journal Papers under Review

Online Bipartite Matching with Advice: Tight Robustness-Consistency Tradeoffs for the Two-Stage Model
Billy Jin, Will Ma.
• Winner of 2023 Student Paper Prize of INFORMS Decision Analysis Society
• Reject and resubmit, Management Science.
• A preliminary version appeared in Neural Information Processing Systems (NeurIPS) 2022.

A Lower Bound for the Max Entropy Algorithm for TSP
Billy Jin, Nathan Klein, David P. Williamson.
• Major revision, Mathematical Programming.
• A preliminary version appeared in Integer Programming and Combinatorial Optimization (IPCO), 2024.

Conference Papers

Sample Complexity of Posted Pricing for a Single Item
Billy Jin, Thomas Kesselheim, Will Ma, Sahil Singla.
• Neural Information Processing Systems (NeurIPS), 2024.

The Online Submodular Assignment Problem
Daniel Hathcock, Billy Jin, Kalen Patton, Sherry Sarkar, Michael Zlatin.
• IEEE Symposium on Foundations of Computer Science (FOCS), 2024.

Proportionally Fair Online Allocation of Public Goods with Predictions
Siddhartha Banerjee, Vasilis Gkatzelis, Safwan Hossain, Billy Jin, Evi Micha, Nisarg Shah.
• Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2023.

Online Nash Social Welfare Maximization with Predictions
Siddhartha Banerjee, Vasilis Gkatzelis, Artur Gorokh, Billy Jin.
• ACM-SIAM Symposium on Discrete Algorithms (SODA), 2022.

Improved Analysis of Ranking for Online Vertex-Weighted Bipartite Matching in the Random-Order Model
Billy Jin, David P. Williamson.
• Conference on Web and Internet Economics (WINE), 2021.

High Probability Step Size Lower Bound for Adaptive Stochastic Optimization
Billy Jin, Katya Scheinberg, Miaolan Xie.
• NeurIPS OPT Workshop, 2021.

Working Papers

An Approximation Algorithm for Network Revenue Management under Markov-Modulated Demand
Billy Jin, Huseyin Topaloglu, David P. Williamson.

Cut-Toggling and Cycle-Toggling for Electrical Flow and Other p-Norm Flows
Monika Henzinger, Billy Jin, Richard Peng, David P. Williamson.

Talks

Advice-Augmented Algorithms for Online Matching and Resource Allocation

Online Bipartite Matching with Advice: Tight Robustness-Consistency Tradeoffs for the Two-Stage Model

A Combinatorial Cut-Toggling Algorithm for Solving Laplacian Linear Systems

Online Nash Social Welfare Maximization with Predictions

A 4/3-Approximation Algorithm for Half-Integral Cycle Cut Instances of the TSP

The Two-Stripe Symmetric Circulant TSP is in P

Improved Analysis of Ranking for Online Vertex-Weighted Bipartite Matching in the Random-Order Model

Teaching and Service

Teaching Assistant

Academic Service