LabCompass

Billy Jin

Computer Science · Purdue University West Lafayette

Early career · publishing since 2020

Publications

38

Citations

120

Est. group size

Recurring co-author estimate

Active years

7

Publishing since 2020

Research summary
AI-generated

Billy Jin works in theoretical computer science and operations research, focusing on the design and analysis of algorithms for combinatorial optimization problems such as the Traveling Salesman Problem (TSP), online matching, and resource allocation. Much of this work involves proving mathematical guarantees on how close approximation algorithms come to optimal solutions, as well as designing algorithms that make good decisions under uncertainty (e.g., online settings where inputs arrive over time, or when using predictions to guide decisions). This research is largely mathematical and theoretical, aimed at understanding the fundamental limits and capabilities of efficient algorithms.

Approximation algorithms for TSPOnline and combinatorial optimizationAlgorithmic game theory and market designLearning-augmented algorithmsGraph algorithms and network optimization

Publication output grew from none a decade ago to a steady pace of roughly 6-9 papers per year since 2022, indicating consistent and active recent research activity.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence
Publications per year over the last 10 years — averaging 5.8/year recently
1718192020: 5 publications202021: 4 publications212022: 9 publications9222023: 6 publications232024: 8 publications242025: 3 publications252026: 3 publications26
Publishes in
  • arXiv (Cornell University)×21
  • Lecture notes in computer science×4
  • Mathematical Programming×3
  • Management Science×1
  • SIAM Journal on Optimization×1
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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 20, 2026.

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