About Me

My name is Chenyue (Jim) Li. I’m a 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 AI for Science(AI4S), aiming to boost the scientific discovery by leveraging the power of AI. Additionally, I also have complementary background in database， distributed Systems, cybersecurity 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
  • 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)
  • Assistant Engineer in Distributed Data Storage and Management Lab (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 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.” To Appear in The Thirty-Ninth Annual Conference on Neural Information Processing Systems. (NeurIPS 2025)

• 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.” In 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics. (NAACL 2025 Findings)

Background & Interests

• AI for Science (AI4S)
• Large Language Model (LLM) & Machine Learning (ML) & Natural Language Processing (NLP)
• Database & Distributed Systems
• Cybersecurity
• Full Stack Development
• Computer Graphics