Hi! I’m a master’s student at MIT, advised by Michiel Bakker. Before MIT, I received my B.S. in Mathematics and Physics from Tsinghua University in 2025.
My research draws on ideas from mathematical logic, cognitive science, and statistical physics to study how intelligence arises. I’m currently exploring this through self-referential AI and multi-agent systems.
Feel free to reach out at xycao [at] mit [dot] edu.
Research Interests
Self-Referential AI. Hofstadter’s strange loops argue that a mind is what happens when a system models itself. Schmidhuber’s Gödel Machine gave this intuition a computational form. I see the same principle at work in self-reward, self-play, self-distillation, and recursive self-improvement. They look like separate techniques. I think they share a root: a model that reasons over its own outputs to reshape itself.
Multi-Agent Emergence. My starting point is Anderson’s “more is different”: at scale, new phenomena emerge that you can’t predict from the parts. Wolfram’s A New Kind of Science makes the same case computationally. Simple rules, iterated, produce genuinely complex behavior. I want to study this in multi-agent AI, where agent swarms, social intelligence, and game theory give rise to collective phenomena that no single agent could produce.
Publications
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RE-PO: Robust Enhanced Policy Optimization as a General Framework for LLM Alignment
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Pareto Control Barrier Function for Inner Safe Set Maximization Under Input Constraints
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Virtual Nodes Improve Long-term Traffic Prediction
News
- RE-PO, our framework for robust LLM alignment, was accepted at ICLR 2026.
- Started my M.S. at MIT.
- Admitted to MIT for Fall 2025.
- Our paper on Pareto Control Barrier Functions was accepted at ACC 2025.
- Our paper on virtual nodes for traffic prediction was accepted at TRB 2025.
Education
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2025–2027
Massachusetts Institute of Technology Dual M.S., Computational Science & Engineering and Technology & Policy · expected May 2027
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2024
University of California, Berkeley Exchange student, Jan–Aug 2024 · GPA 3.93 / 4.00
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2021–2025
Tsinghua University B.S. in Mathematics and Physics · GPA 3.95 / 4.00, ranked 3 / 60