Yifeng (Ethan) Xiao  萧屹楓

EECS Ph.D. @ UC Berkeley  ·  Neurosymbolic AI

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Hi there! It’s Yifeng (Ethan). I am an EECS Ph.D. candidate at the University of California, Berkeley, advised by Prof. Pierluigi Nuzzo.

🤖 My research is on neurosymbolic AI: combining formal methods, machine learning, and game theory to design, verify, and synthesize systems that act in the world, from hardware design and cyber-physical systems (such as smart grids and robotics) to AI agents. I lead the development of CHASE, an open-source contract-based design toolkit that is the symbolic backbone of this work. Alongside my research, I co-founded a stealth startup that brings these ideas to production AI agents.

I received my B.E. in Microelectronic Science and Engineering from Fudan University (復旦大學), where I worked with Prof. Jianli Chen and Prof. Bei Yu on machine learning for electronic design automation (EDA).

💬 I enjoy connecting with researchers, engineers, and founders working on related problems, and I am open to collaborations and new opportunities. Feel free to reach out, or book 30 minutes with a quick note on what you’d like to discuss.

News

Oct 29, 2026 Gave a virtual presentation of ACIES at the REALM 2026 workshop at EMNLP 2026. The paper is now available in the ACL Anthology! 🎤
Oct 09, 2026 Presented our paper on contract-based consistency and availability analysis for distributed cyber-physical systems at MEMOCODE 2026, part of ESWEEK 2026 in Barcelona, Spain! 🎤
Sep 08, 2026 Paper “ACIES: A Self-Evolving Agentic Contract-Based Framework for Cyber-Physical System Control Synthesis” accepted at the REALM 2026 workshop, co-located with EMNLP 2026 in Budapest, Hungary! 🎉

Selected Publications

  1. DATE
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    Efficient Exploration of Cyber-Physical System Architectures Using Contracts and Subgraph Isomorphism
    Yifeng Xiao, Chanwook Oh, Michele Lora, and 1 more author
    In IEEE Design, Automation & Test in Europe Conference & Exhibition (DATE), 2024
  1. arXiv
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    Symbolic Temporal Supervision of LLM Agents Using Contracts
    Yifeng Xiao and Pierluigi Nuzzo
    arXiv preprint arXiv:2609.18128, Sep 2026
  2. CDC
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    Incentive Design for Safe Nash Equilibrium Learning in Large Populations via Control Barrier Functions
    Yifeng Xiao, Jair Certorio, Nuno C. Martins, and 2 more authors
    In IEEE Conference on Decision and Control (CDC), 2025

Honors and Awards

  • Best Paper Award , Design Automation and Test Conference in Europe 2024 (Top 0.4% of submissions) 2024
  • DAC Young Fellowship , Design Automation Conference 2023
  • Outstanding Graduates of Shanghai , Shanghai Municipal Government (Top 2%) 2020
  • National IC Design Competition - First Prize for Undergraduate Group , National IC Design Competition 2019
  • Undergraduate Excellence Scholarship of FDU , Fudan University 2018
  • SCSK Corporation Scholarship , SCSK Corporation (Top 1%) 2018