Zaifeng Pan

prof_pic.jpeg

Hi there! I’ve been a Ph.D. student at UC San Diego since fall 2024. I’m part of the PICASSO Lab, where I’m fortunate to be advised by Prof. Yufei Ding. My current research interests lie in machine learning systems, with a particular focus on making large language models (LLMs) more efficient from the perspectives of systems, compilers, and kernels, covering both inference and training. Recently, I have been focusing on systems optimization for LLM agents.

Before starting my Ph.D., I earned my master’s degree at Renmin University of China, where I was advised by Prof. Feng Zhang and worked closely with Dr. Zhen Zheng. My master’s research focused on compiler optimizations for GPU workloads, particularly industrial recommendation models. In retrospect, this work explored ideas now commonly associated with MegaKernels.

My Chinese name is 潘再峰. I also like being called 小再. If you’re interested in my research or just want to connect as a friend, feel free to email me at zapan@ucsd.edu.

Also, a shout-out to my roommate, who is an expert in computer architecture—check out his homepage and research!

Education

  • University of California, San Diego (UCSD), 2024 - Present
    Ph.D. student in Computer Science & Engineering
    Advisor: Prof. Yufei Ding

  • Renmin University of China (RUC), 2021 - 2024
    M.S. in Computer Software and Theory
    Advisor: Prof. Feng Zhang

  • Shanghai Jiao Tong University (SJTU), 2017 - 2021
    B.E. in Mechanical Engineering

Work Experience

  • NVIDIA, DL Training Performance Intern, 2026
    Mentor: Dr. Abhinav Goel

  • Amazon Web Services, Applied Scientist Intern, 2025
    Mentors: Dr. Aninda Manocha and Dr. Zhuang Wang

  • Microsoft, Research Intern, 2023 - 2024
    Mentor: Dr. Zhen Zheng

  • Alibaba PAI, Research Intern, 2021 - 2023
    Mentor: Dr. Zhen Zheng

Selected Publications

  1. arXiv
    HiState: Hierarchical Prefix Cache Management for Hybrid LLM Serving in Agentic Workloads
    Zaifeng Pan*, Lucas Wang*, Xinwei Qiang, Yanbo Zhou, Chang Chen, Zhengding Hu, Yue Guan, and Yufei Ding
    arXiv preprint arXiv:2610.41508, 2026
  2. arXiv
    LeanSparse: Memory-Efficient Serving for Native Sparse-Attention LLMs
    Zaifeng Pan*, Chris Wu*, Xinwei Qiang, Zhengding Hu, Zhongkai Yu, and Yufei Ding
    arXiv preprint arXiv:2611.04671, 2026
  3. arXiv
    RR-Evict: Fine-Grained Prefix Cache Eviction beyond LRU for Agentic LLM Serving
    Zaifeng Pan*, Chris Wu*, Zhengding Hu, Xinwei Qiang, Zhongkai Yu, and Yufei Ding
    arXiv preprint arXiv:2609.32278, 2026
  4. arXiv
    SmoothAgent: Efficient Long-Horizon LLM-Based Agent Serving with Lookahead Context Engineering
    Zaifeng Pan, Qianxu Wang, Zhengding Hu, Chang Chen, Yue Guan, Yanbo Zhou, Steven Swanson, and Yufei Ding
    arXiv preprint arXiv:2607.00151, 2026
  5. ICML’26
    ScaleSim: Serving Large-Scale Multi-Agent Simulation with Invocation Distance-Based Memory Management
    Zaifeng Pan*, Yipeng Shen*, Zhengding Hu, Zhuang Wang, Aninda Manocha, Zheng Wang, Zhongkai Yu, Yue Guan, and Yufei Ding
    In Proceedings of the 43rd International Conference on Machine Learning, 2026
  6. NeurIPS’25
    KVFlow: Efficient Prefix Caching for Accelerating LLM-Based Multi-Agent Workflows
    Zaifeng Pan, Ajjkumar Patel, Yipeng Shen, Zhengding Hu, Yue Guan, Wan-Lu Li, Lianhui Qin, Yida Wang, and Yufei Ding
    In The Thirty-ninth Annual Conference on Neural Information Processing Systems, 2025
  7. MLSys’25
    FastTree: Optimizing Attention Kernel and Runtime for Tree-Structured LLM Inference
    Zaifeng Pan, Yitong Ding, Yue Guan, Zheng Wang, Zhongkai Yu, Xulong Tang, Yida Wang, and Yufei Ding
    In Proceedings of Machine Learning and Systems, 2025
  8. SC’24
    RecFlex: Enabling Feature Heterogeneity-Aware Optimization for Deep Recommendation Models with Flexible Schedules
    Zaifeng Pan, Zhen Zheng, Feng Zhang, Bing Xie, Ruofan Wu, Shaden Smith, Chuanjie Liu, Olatunji Ruwase, Xiaoyong Du, and Yufei Ding
    In International Conference for High Performance Computing, Networking, Storage and Analysis, 2024
  9. ASPLOS’23
    RECom: A Compiler Approach to Accelerating Recommendation Model Inference with Massive Embedding Columns
    Zaifeng Pan, Zhen Zheng, Feng Zhang, Ruofan Wu, Hao Liang, Dalin Wang, Xiafei Qiu, Junjie Bai, Wei Lin, and Xiaoyong Du
    In Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 4, 2023
    🏆  Distinguished Artifact Award (presented at ASPLOS’24)