Chenyue (Jim) Li

Chenyue (Jim) Li

PhD Student at HKUST

About Me

My name is Chenyue (Jim) Li. I’m an incoming PhD student in the Department of Computer Science and Engineering at HKUST, under the supervision of Prof Binhang YUAN. My research interest primarily focuses on large language model and AI system. Additionally, I am also interested in cybersecurity, operating system and full stack development.

Education

  • Hong Kong University of Science and Technology (HKUST) (2024 - ongoing)
    • PhD student in the Department of Computer Science and Engineering
  • University of Toronto - St. George (2019 - 2024)
    • Honours Bachelor of Science with High Distinction
    • Computer Science Specialist | AI focus
    • Dean’s List Scholar

Experience

  • Voithos Labs (Sep 2023 - April 2024)
    • Software Engineer · Part-time
    • Developed alpha and beta versions for VNOTE, a super-contextual note-taking application with intelligent assistants. Reference: https://www.voithoslabs.com/.
  • Huawei Technologies Canada Co., Ltd. (May 2022 - Sep 2023)
    • Distributed AI System Engineer (R&D) · Co-op
    • Contributed to the development and optimization of MindSpore Pandas. Reference: https://www.mindspore.cn/en.
    • Contributed to the distributed computing engine in Jiutian (Huawei Analytics AI Engine) and GaussDB by researching and enhancing BSP and MPP execution modes in C++.
  • Meonc Studio (Nov 2016 - Aug 2021)
    • Studio Founder · Freelance

Publications

  • Chenyue Li, Wen Deng, Mengqian Lu, Binhang Yuan. “AtmosSci-Bench: Evaluating the Recent Advance of Large Language Model for Atmospheric Science.”

  • He, Guangxin, Zonghong Dai, Jiangcheng Zhu, Binqiang Zhao, Qicheng Hu, Chenyue Li, You Peng, Chen Wang, and Binhang Yuan. “Zero-Indexing Internet Search Augmented Generation for Large Language Models.”

  • Zhang, Lujia, Yurong Song, Hanzhe Cui, Mengqian Lu, Chenyue Li, Binhang Yuan, Bin Wang, Upmanu Lall, and Jing Yang. “Foundation models as assistive tools in hydrometeorology: Opportunities, challenges, and perspectives.” Water Resources Research 61, no. 4 (2025): e2024WR039553.

  • David Anugraha, Genta Indra Winata, Chenyue Li, Patrick Amadeus Irawan, En-Shiun Annie Lee. “ProxyLM: Predicting Language Model Performance on Multilingual Tasks via Proxy Models.” To appear in Findings of NAACL 2025.

Intersted Field

  • Machine Learning (ML)
  • Natural Language Processing (NLP)
  • Distributed Systems
  • High Performance Computing (HPC)
  • Cybersecurity
  • Full Stack Development
  • Operating Systems