Sijun Tan (谭嗣俊)

I am a third-year CS PhD student at UC Berkeley, advised by Raluca Ada Popa. I am affiliated to Berkeley’s Sky Computing Lab.

Previously, I graduated from University of Virginia with a Bachelor’s degree in Computer Science and Mathematics, where I was advised by David Wu and Yuan Tian. I also worked with Professors Haifeng Xu and Xiaohui Bei. I interned at Facebook AI Research (FAIR) and worked at Ant Group as a senior algorithm engineer.

My work spans machine learning, computer security, and applied cryptography. Currently, I am focused on advancing security, safety, and alignment of Generative AI.

I am looking for highly motivated undergrads to work with! If you are interested in research opportunities, please send me an email.

news

Oct 16, 2024 We are excited to release JudgeBench: a challenging benchmark to evaluate LLM-based judges. Checkout our leaderboard and code.
Mar 21, 2024 Our paper Flock: A Framework for Deploying On-Demand Distributed Trust is accepted to appear at OSDI 2024.
May 22, 2023 Our paper MPCAuth: Multi-factor Authentication for Distributed-trust Systems is accepted to appear at IEEE S&P 2023.
Jul 14, 2021 I give a talk on my research work CryptGPU at Stanford Security Lunch.

selected publications

  1. Preprint
    JudgeBench: A Benchmark for Evaluating LLM-based Judges
    Sijun Tan*, Siyuan Zhuang*, Kyle Montgomery*, Willian Y. Tang, Alejandro Cuadron, Chenguang Wang, Raluca Ada Popa, and Ion Stoica
    2024
  2. EMNLP
    LLoCO: Learning Long Contexts Offline
    Sijun Tan*, Xiuyu Li*, Shishir Patil, Ziyang Wu, Tianjun Zhang, Kurt Keutzer, Joseph E. Gonzalez, and Raluca Ada Popa
    Empirical Methods in Natural Language Processing (EMNLP), 2024
  3. OSDI
    Flock: A Framework for Deploying On-Demand Distributed Trust
    Darya Kaviani*, Sijun Tan*, Pravein Govindan Kannan, and Raluca Ada Popa
    Operating Systems Design and Implementation (OSDI), 2024
  4. IEEE S&P
    MPCAuth: Multi-factor Authentication for Distributed-trust Systems
    Sijun Tan, Weikeng Chen, Ryan Deng, and Raluca Ada Popa
    IEEE Symposium on Security and Privacy (Oakland), 2023
  5. IEEE S&P
    CryptGPU: Fast Privacy Preserving Machine Learning on the GPU
    Sijun Tan, Brian Knott, Yuan Tian, and David J Wu
    IEEE Symposium on Security and Privacy (Oakland), 2021