I am currently work at Huawei Technolgies as an AI engineer in Shanghai, China. My work focuses on the intelligent automated evaluation of Large Language Models (LLMs). I will become a PhD candidate at School of Software and Microelectronics, Peking University (北京大学软件与微电子学院) in the fall semester of 2025. My research interest includes LLMs, multimodality learning, representation learning, and transferability.

I graduated from the University of Chinese Academy of Sciences (中国科学院大学) with a Master’s degree in Computer Technology, advised by Yunpeng Cai. I earned my bachelor’s degree at College of Electronics and Information Engineering, Shenzhen University.

As the first or co-first author, I have published four articles in top-tier journals or JCR Q1-ranked journals with total . I have also presented a conference paper and published an invention patent.

🔥 News

• 2025.02:  🎉🎉 My paper A Transferability-guided Protein-ligand Interaction Prediction Method is accepted by Methods.
• 2025.01:  🎉🎉 I have been admitted as a PhD student to the School of Software and Microelectronics, Peking University .

📖 Educations

• 2025.09 -: PhD Candidate, School of Software and Microelectronics, Peking University .
• 2021.09 - 2024.06: Master, Shenzhen Institutes of Advanced Technology (SIAT), University of Chinese Academy of Sciences .
• 2017.07 - 2021.06: Bachelor, College of Electronics and Information Engineering, Shenzhen University .

📝 Publications

Advanced Science

A Multimodal Protein Representation Framework for Quantifying Transferability Across Biochemical Downstream Tasks

Fan Hu¹, Yishen Hu¹, Weihong Zhang¹, Huazhen Huang, Yi Pan, and Peng Yin

¹: These authors contributed equally to this work (the same hereafter).

Project |

• A SOTA multimodal deep learning framework for incorporating ≈1 million protein sequence, structure, and functional annotation (MASSA).
• Academic Impact: This work is promoted by DrugAI.

IEEE JBHI

A Transferability-Based Method for Evaluating the Protein Representation Learning

Fan Hu¹, Weihong Zhang¹, Huazhen Huang, Wang Li, Yang Li, Peng Yin

Project |

• A novel quantitative approach for estimating the performance of transferring multi-task pre-trained protein representations to downstream tasks.

Methods

Does Protein Pretrained Language Model Facilitate the Prediction of Protein–ligand Interaction?

Weihong Zhang, Fan Hu, Wang Li, Peng Yin

Project |

• An approach that quantitatively evaluates the impact of protein pretrained language model (PLM) in protein–ligand interaction (PLI) predictions, which allows us to select the optimal PLM for a given downstream task without exhaustively testing each PLM, thus avoiding the costly computational expense. The mechanisms underlying the influence of protein PLMs on PLI tasks are explored.

Methods

A Transferability-guided Protein-ligand Interaction Prediction Method

Weihong Zhang, Fan Hu, Peng Yin, Yunpeng Cai

Project |

• A novel transferability-guided PLI prediction method that maximizes knowledge transfer by deeply integrating protein and ligand representations through a cross-attention mechanism and incorporating transferability metrics to guide fine-tuning.

• ISBRA 2024 A Transferability-guided Protein-ligand Interaction Prediction Method
  Weihong Zhang, Fan Hu, Peng Yin, Yunpeng Cai
  The 20th International Symposium on Bioinformatics Research and Application, 2024 (CCF-C)
  Page PDF Code

• Invention Pattern An Evaluation Method and System for Protein Representation Learning Based on Quantitative Transferability (一种基于可迁移性定量的蛋白质表示学习评估方法及系统)
  Fan Hu, Weihong Zhang, Peng Yin
  China Invention Pattern, CN117637034A, 2024
  Page

🗣 Conferences

• 2024.07: The 20th International Symposium on Bioinformatics Research and Application (ISBRA 2024), Oral, Kunming, China.

💻 Internships

• 2024.07 - present: AI Engineer, Huawei Technologies Co., Ltd., Shanghai, China.
• 2021.06 - 2021.08: Research Intern, SIAT, Chinese Academy of Sciences, Shenzhen, China.

🎖 Honors and Awards

• 2024.07: Merit Student of University of Chinese Academy of Sciences.
• 2024.04: Outstanding Communist Youth League Member of Chinese Academy of Sciences (Guangzhou).
• 2024.01: SIAT President’s Scholarship - Excellence Award.
• 2023.02: Outstanding Student at the BIT Center, SIAT, Chinese Academy of Sciences.
• 2021.06: Outstanding Graduate of the School of Electronic and Information Engineering, Shenzhen University.
• 2020.12: Shenzhen University Academic Star Scholarship.
• 2020.10: National Endeavor Scholarship.
• 2020.07: Outstanding Communist Youth League Member of Shenzhen University.
• 2019.12: Shenzhen University Public Service Star Scholarship.
• 2019.06: Outstanding Volunteer Officer of Shenzhen University.
• 2018.12: Shenzhen University Public Service Star Scholarship.
• 2018.10: National Endeavor Scholarship.