Zhuohao Li

I am a second-year Ph.D. student at UCLA EECS, advised by Prof. Yuan Tian.

Previously, I obtained my Bachelor's degree from Shanghai Jiao Tong University. During my undergraduate, I spent a great junior year with Prof. Jingwen Leng at SJTU EPCC Lab. I was a visiting researcher at UT Austin with Prof. Calvin Lin. I also spent a wonderful undergrad exchange time at HKUST with Prof. Wei Wang.

During my career, I am fortunate to work and intern at NVIDIA, AWS AI Lab, Alibaba Cloud, and Shanghai AI Laboratory. My research is supported by Samueli Fellowship during my Ph.D..

My research interests lie in efficient large language models (LLMs), machine learning systems, and trustworthy AI.

Linkedin  /  CV  /  Google Scholar  /  𝕏  /  GitHub

profile photo
zhuohaol [at] ucla [dot] edu Office: Engineering VI 63-205

I am always interested in potential collaboration in efficient and trustworthy ML. I am also happy to mentor highly-motivated undergrads/masters in EECS. If you want to discuss ideas and research opportunies, please feel free to shoot me an email. If you are a UCLA student and would like an office hour, please book an appointment with me.

News

[6/2024] 🎉 I join AWS AI Lab as an Applied Scientist Intern, see you in New York!
[4/2024] I am visiting Duke in April, see you in Duram!
[3/2024] I am in NDSS 2024 this week, see you in San Diego!
[3/2024] I will give a talk at UCI, see you in Irvine!
[2/2024] I am in the vLLM meetup, see you in Bay Area!
[12/2023] I am in ICCV 2023 and visiting École polytechnique telecom this winter, see you in Paris!
[5/2023] 🎉 My thesis was elected as the Merit Honor at SJTU!
[3/2023] 🎉 I join Shanghai AI Lab as an Research Scientist Intern this summer!
[12/2023] I will exchange at HKUST CSE this fall, see you in Hong Kong!
[6/2022] 🎉 I join NVIDIA as a SWE Intern, see you in Bay Area!
[4/2022] I am visiting UT Austin this summer, see you in Austin!

Research Interests

I am focusing on building confidential while efficient algorithms and systems for various scaled machine learning tasks. I am currently working on efficient large language models and trustworthy machine learning. I would like to acceralete AGI in all ways. My dream is build interactive, human-friendly, fault-tolerant, and low-cost end-to-end frameworks from models to infrastructure to help enpower AGIs.

In my past years of research experience, I have also explored these research directions:

  • ML Computing Paradigms: How to enable efficient management of emerging new workloads in heterogeneous datacenters and constructing systems for new computing paradigms on the cloud.
  • SW-HW Co-design: The way how hardware, software, compiler, and data interact with each other to get optimized in specified tasks. ML tasks get either specifically or generally optimzied on emerging hardware.
  • LLM Agents: How to apply, retreive, fine-tune general models with other domain specific usages, such as vulnerability extraction, security, and privacy.

    • Publications
    Lazarus: Resilient and Elastic Training of Mixture-of-Experts Models with Adaptive Expert Placement
    Yongji Wu, Wenjie Qu, Tianyang Tao, Zhuang Wang, Wei Bai, Zhuohao Li, Yuan Tian, Jiaheng Zhang, Matthew Lentz,
    (under review), 2025
    code / project page / arXiv / Poster
    FaaSwap: SLO-Aware, GPU-Efficient Serverless Inference via Model Swapping
    Minchen Yu, Ao Wang, Dong Chen, Haoxuan Yu, Xiaonan Luo, Zhuohao Li, Wei Wang, Ruichuan Chen, Dapeng Nie, Haoran Yang
    (under review), 2024
    code / project page / arXiv / Poster
    RealNet: Combining Optimized Object Detection with Information Fusion Depth Estimation on IoT Devices
    Zhuohao Li, Leqi Ding, Yuanhang Zhang, etc.
    arXiv preprint, 2022
    code / project page / arXiv / Poster
    Experience
    AWS logo
    Amazon Web Services, New York, NY, USA
    Applied Scientist Intern at AWS AI Lab, mentor: Hengzhi Pei, Leonard Lausen, Yida Wang.
    Jun 2024 ~ Sep 2024
    NVIDIA logo
    NVIDIA, Santa Clara, CA, USA
    CUDA Software Engineering Intern, mentor: Leong Ho and Eko Lau
    Jun 2022 ~ Dec 2022
    Alicloud logo
    Alibaba Cloud, China
    Software Engineering Intern
    Jun 2021 ~ Dec 2021
    Highlighted Honor
    Samueli School of Engineering Fellowship, UCLA, 2024
    Shanghai Outstanding Graduates, SJTU, 2023
    Cockrell School of Engineering Fellowship, UT Austin, 2023
    SenseTime Scholarship , SenseTime, 2022
    Stanford Irving T Ho Fellowship , Irving T Ho Foundation, 2022
    Dean List, SJTU, 2020 - 2022
    Google Cup Google, 2020
    Misc.

    I love snowboarding and racing fomula. You can find me on 小红书 and instagram. I was a participant of Mathematics Olympiad in high school.