Dacheng Li

I am a first-year CS PhD at EECS, UC Berkeley, fortunately advised by Prof. Ion Stoica and Prof. Joseph Gonzalez in lmsys, Sky and BAIR. I obtained my master in Machine Learning at CMU with Prof. Eric Xing and Prof. Hao Zhang . I obtained my undergraduate with double majors in Computer Science and Mathematics at UC San Diego with Prof. Zhuowen Tu . I also work closely with Prof. Song Han (MIT).

I study Machine Learning, in the context of modeling performance, scaling, system efficiency, framework usability, and theoratical support. My goal is to develop, support performant models at scale, and provide easily usable framework for people, to faciliate intelligence deployment in the real world. I am currently working on algorithms and systems around LLMs and diffusion models.

Also check out my girlfriend's webpage . She is a great CS PhD at UW.

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• 2024-06 Joined Nvidia as a research intern.
• 2024-05 Chatbot Arena is accepted to ICML 2024.
• 2024-03 VTC is accepted to OSDI 2024.
• 2024-02 S-lora and MCBench are accepted to MLsys 2024.
• 2023-10 Released a long-context distributed training kernel LightSeq .
• 2023-09 The official paper of Vicuna (LLM-as-a-judge) is accepted to Neurips 2024.
• 2023-08 Joined Google as a student researcher, working on LLMs evaluation.
• 2023-06 Released a series of long-context models and evaluation toolkits LongChat.
• 2023-04 Released a compact open-sourced chatbot FastChat-T5.
• 2023-01 MPCFormer is accepted at ICLR 2023 as spotlight.
• 2022-12 A secure LLMs serving proposal is accepted at Amazon Research Awards.
• 2022-10 AMP is accepeted at NeruIPS 2022.
• 2021-03 DC-VAE is accepted at CVPR 2021.