I am a PhD student at the department of industrial engineering, Tsinghua University. Currently, I’m visiting Prof. Huiwen Jia's lab at UC Berkeley. I received my B.E. in industrial engineering from Tsinghua University in 2023.

I study decision-making with an ambition to connect normative theories with descriptive models. Current investigations include:

• Sequential Decision Algorithms for learning and decision-making under incomplete information
• Behavioral Models of human decision-making under risk and uncertainty
• Expert Elicitation Methods for knowledge extraction and aggregation

Papers

Normative and Prescriptive Decision Models

Hong, Y., Qin, S., Wang, C. (2026). LAMDA: Large Language Model as Decision Analyst. Accepted to Decision Analysis.

Hong, Y., Jia, H., & Wang, C. (2026). Learning for Irreversible Subset Expansion: Objective Degeneracy and Thompson Sampling under Information Dilution. Available at SSRN 7496998.

Descriptive Decision Models

Hong, Y., Fan, H., & Wang, C. (2026). Decision-Making under Combinatorial Risk. arXiv preprint arXiv:2606.10092.

Hong, Y., Wang, C., & Zhao, B. (2025). State Sensitivity in an Additive Discovery Game. Proceedings of the Annual Meeting of the Cognitive Science Society, 47.

Hong, Y., Wang, C. (2025). A Rational Model of Dimension-reduced Human Categorization. Proceedings of the Annual Meeting of the Cognitive Science Society, 47.

Talks

Decision-Making as Categorization, Oral presentation at 2023 INFORMS Annual Meeting

LAMDA: Large Language Model as Decision Analyst, Oral presentation at 2025 INFORMS Annual Meeting

Decision under Combinatorial Risk, PhD incubator talk at 2026 INFORMS Advances in Decision Analysis Conference

Online Irreversible Subset Expansion under Active-Set Market Feedback, Oral presentation at 2026 INFORMS Revenue Management and Pricing Section Conference

Service

• Reviewer, Annual Meeting of the Cognitive Science Society (CogSci) 2026
• Reviewer, Decision Analysis