Zaifeng Pan

Hi there! I’m a Ph.D. student at UC San Diego, starting from 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.

Before my Ph.D., I earned my Master’s degree at Renmin University of China, advised by Prof. Feng Zhang and working closely with Dr. Zhen Zheng. My Master’s research focused on ML compilers for optimizing workloads on GPUs, with an emphasis on industrial recommendation models (see my publications at ASPLOS’23 and SC’24).

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, 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

Amazon Web Service, Applied Scientist Intern, 2025
Mentor: 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

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

Bib PDF Code

@inproceedings{pan2025fasttree,
  title = {FastTree: Optimizing Attention Kernel and Runtime for Tree-Structured LLM Inference},
  author = {Pan, Zaifeng and Ding, Yitong and Guan, Yue and Wang, Zheng and Yu, Zhongkai and Tang, Xulong and Wang, Yida and Ding, Yufei},
  booktitle = {Proceedings of Machine Learning and Systems},
  year = {2025}
}

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

Bib PDF Code

@inproceedings{pan2024recflex,
  title = {RecFlex: Enabling Feature Heterogeneity-Aware Optimization for Deep Recommendation Models with Flexible Schedules},
  author = {Pan, Zaifeng and Zheng, Zhen and Zhang, Feng and Xie, Bing and Wu, Ruofan and Smith, Shaden and Liu, Chuanjie and Ruwase, Olatunji and Du, Xiaoyong and Ding, Yufei},
  booktitle = {International Conference for High Performance Computing, Networking, Storage and Analysis},
  pages = {1--15},
  year = {2024},
  organization = {IEEE}
}

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)

Bib PDF Code

@inproceedings{pan2023recom,
  title = {RECom: A Compiler Approach to Accelerating Recommendation Model Inference with Massive Embedding Columns},
  author = {Pan, Zaifeng and Zheng, Zhen and Zhang, Feng and Wu, Ruofan and Liang, Hao and Wang, Dalin and Qiu, Xiafei and Bai, Junjie and Lin, Wei and Du, Xiaoyong},
  booktitle = {Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 4},
  pages = {268--286},
  year = {2023}
}