Jiayi Wu (jyah-yee/jiā-yì)

Hello:)

Hi! I'm an undergrad studying Mathematics (A.B.) and Computer Science (Sc.B.) at Brown University, advised by Suresh Venkatasubramanian and Isabel Vogt.

I hope to build the formal and empirical infrastructure for trustworthy machine learning across two complementary dimensions:

AI for mathematics and automated reasoning: Formal theorem proving [1] [2] and program synthesis [3] are fully specified, unambiguous, machine-checkable substrates for studying models' reasoning processes. Concretely, I'm interested in designing model architectures that leverage various learning paradigms (reinforcement learning and neurosymbolic programming in particular) to enable more robust and interpretable reasoning.
Principled evaluation, auditing, and guarantees: Evaluating trustworthiness requires pipelines that adapt to different systems at different stages of model design, development, and deployment. I'm interested in enabling these pipelines to reason about security [4], alignment [5], and accountability [6] across these stages and throughout the full model lifecycle and supply chain.

My Work

Below are selected projects and publications; a more comprehensive list is available in my academic CV.

Interoperability for Formal Mathematics: Automating Proof Translation Across Interactive Theorem Provers, Summer Undergraduate Research Fellowships (SURF) project advised by Anima Anandkumar, in collaboration with Robert Joseph George.
Formalizing and Benchmarking Overton Pluralism in LLMs, advised by Michiel Bakker, in collaboration with Elinor Poole-Dayan.
Elinor Poole-Dayan, Jiayi Wu, Taylor Sorensen, Jiaxin Pei, Michiel A. Bakker. Benchmarking Overton Pluralism in LLMs. ICLR 2026. Previously in NeurIPS 2025 Workshop on Evaluating the Evolving LLM Lifecycle. [arXiv] [GitHub] [HuggingFace]
Pattern Mining and Automated Tactic Discovery in Formal Theorem Proving, advised by Robert Lewis and Stephen Bach, in collaboration with Gavin Zhao, Zekai Li, and Ilija Ivanov.
Motif of Thoughts (MoT): Reusable Abstractions for Compositional Neurosymbolic Reasoning, in collaboration with Chance Jiajie Li.
Chance Jiajie Li*, Jiayi Wu*, Zhenze Mo, Ao Qu, Yuhan Tang, Kaiya Ivy Zhao, Yulu Gan, Jie Fan, Jiangbo Yu, Jinhua Zhao, Paul Pu Liang, Luis Alberto Alonso Pastor, Kent Larson. Simulating Society Requires Simulating Thought. NeurIPS 2025 Position Paper Track (5.7%). [arXiv]

Chance Jiajie Li, Zhenze Mo, Yuhan Tang, Ao Qu, Jiayi Wu, Kaiya Ivy Zhao, Yulu Gan, Jie Fan, Jiangbo Yu, Hang Jiang, Paul Pu Liang, Jinhua Zhao, Luis Alberto Alonso Pastor, Kent Larson. HugAgent: Evaluating LLMs in Simulating Individual-Level Human Reasoning on Open-Ended Tasks. NeurIPS 2025 Workshop on Bridging Language, Agent, and World Models for Reasoning and Planning (Spotlight). Also in NeurIPS 2025 Workshop on PersonaLLM (Oral) and NeurIPS 2025 Workshop on Socially Responsible and Trustworthy Foundation Models. [arXiv] [GitHub]
Neurosymbolic Synthesis of Regular Stream Types, Undergraduate Teaching and Research Awards (UTRA) project advised by Nikos Vasilakis, in collaboration with Lukas Lazarek, Zekai Li, and Evangelos Lamprou.
AI Governance, AI Safety, and Algorithmic Fairness Primer at Socially Responsible Computing (SRC) Handbook [Handbook], advised by Suresh Venkatasubramanian, Julia Netter, and Serena Booth.

Misc

Outside of research, I help organize communities at Brown that connect technology with governance and public-interest perspectives. I’m co-president of Brown’s AI and Robotics Ethics Society (AIRES) and an undergraduate teaching assistant at CSCI 1952B Responsible Computer Science in Practice; I also co-directed the AI Governance Panel at Brown China Summit 2025; more updates are available here!

In my spare time, I enjoy cold brew, taking on plank challenges (≥7min), and roaming around the neighborhoods and community spaces I'm involved in 🏘️🌳 -- if I'm not in CIT or the the Rock's basement stacks^;