Yuquan Li

Yuquan Li

Special-term Professor

I have long worked on AI for Science, with a focus on AI-driven target discovery and molecular design. The design space of molecular science is virtually infinite, whereas wet-lab validation remains costly, slow, and burdened by an extremely low success rate. To resolve this central tension, I study a new paradigm for precise molecular-science discovery built on four-in-one collaboration—”Expert Wisdom + General Intelligence + Specialized Tools + Automated Experimentation”—and build a human–AI collaborative, dry–wet closed-loop intelligent research platform, advancing AI from a computational aid toward practical, autonomous molecular-science discovery. Representative work has appeared as lead author in journals such as Nature Machine Intelligence and Advanced Science. Current research interests include:

  • Foundational AI: large-model agents and swarm intelligence; graph data processing and graph learning
  • AI for Science: targeted design of small molecules, peptides, proteins, small nucleic acids, and materials; dry–wet closed-loop robotic scientists

Let’s talk: I’m always glad to hear from fellow researchers and students—happy to exchange ideas and explore collaborations (WeChat: yvquanli).

Call for papers: Submissions to TIDD / The Innovation / Exploration / iMeta are warmly welcomed—high-quality manuscripts will be recommended for expedited peer review.

Recruiting: Openings for Master’s/PhD students, joint-training candidates, and interns. My pledge: never grab first authorship, never berate students, never unjustly delay graduation. You can expect a proper onboarding, attentive day-to-day guidance, and ample computing resources. My goal is for every student to produce a first-author paper in a Q1 journal or A-level conference, with full support for outstanding students aiming at Nature/Cell/Science sub-journals.

🎓 Education

2019.9  - 2024.6
2015.9  - 2019.6 		Ph.D. - Lanzhou University, School of Chemistry and Chemical Engineering (Major: Chemoinformatics, Supervisor: Prof. Xiaojun Yao)
Bachelor - Qinghai University, School of Computer Science (Major: Computer Science and Technology)

🧑‍💻 Work Experience

2024.10 - Present
2024.10 - Present
2022.7  - 2023.4
2020.8  - 2022.6
 Guizhou University, Provincial Big Data Laboratory / College of Computer Science, Special-term Professor
Guizhou University, State Key Laboratory of Green Pesticide, Visiting Researcher
Beijing Academy of Artificial Intelligence (BAAI) Jie Fu's Team, Research Intern
Tencent Quantum Lab, Joint Training (Co-supervisor: Dr. Changyu Hsieh)

🏛️ Academic Services

2026.5  - Present
2026.1  - Present
2025.8  - Present
2025.8  - Present
2024.9  - Present
2024.8  - Present
2026.1
2025.1, 2025.8
 Professional Committee on Agricultural and Forestry Informatics, China Society of Bioinformatics, Youth Committee Member
"The Innovation Drug Discovery" (Targeting IF 25~30), Founding Preparatory Committee Member; Academic Editor (Executive)
"The Innovation" (Comprehensive Q1 IF=39.5), Youth Editorial Board
"iMeta" (Biology Q1 IF=44.4), Youth Editorial Board
"Exploration" (Comprehensive Q1 IF=30.4), Youth Editorial Board, Deputy Director of Plant Division of Youth Committee
China-Sri Lanka Belt and Road Joint Laboratory of Tea Green Prevention and Control Technology, Founding Participant
The 6th International Conference on Green Plant Protection Innovation, Organizing Committee
Guizhou Provincial Big Data Bureau Project Artificial Intelligence Industry Direction Review Expert Group, Leader

📑 Research Projects

[1] National Data Bureau Pilot Dataset Program — Multimodal Plant-Protection Dataset of Crop Pests, Diseases, Weeds, and Pesticides, 2026, Sub-project PI
[2] NSFC Regional Project — AI-Driven Mining of RNAi Genes in Wheat-Field Aphids and RNAi Pesticide Design, ¥320K, 2026, PI
[3] Guizhou University Talent Introduction Program — Novel Methods for Multi-Constrained Small-Molecule Generative Design, ¥400K, 2024, PI

👥 Team Members

Own Students
Yuxuan Jiang, Master '25, RNA Small Molecule Inhibitors
Weixun Chen, Master '25, Agent Molecular Design
 Joint Ph.D. Students
Xinyu Dong¹, Ph.D. '24, Multi-objective Molecular Generation
Guangyi Huang¹, Ph.D. '24, AI Target Discovery
Mutian He², Ph.D. '25, Macromolecular Drugs
Shihang Wang², Ph.D. '25, Cell Phenotype Learning
Daohong Gong², Ph.D. '25, Targeted Protein Degradation Design
Jinyu Cui³, Ph.D. '25, Peptide and Delivery Design
Hushuangyin Tang², Ph.D. '26, Delivery Systems
 Joint Master's Students
Jun Zhou¹, Master '24, Synthesis Planning
Lei Zhu³, Master '24, Antimicrobial Peptide Design
Chaoyang Xie⁴, Master '23, Molecular Property Prediction

Alumni
Huiyang Hong, Undergrad '22, Now at Prof. Tingjun Hou's Group

Close Collaborators (Supervisors): Gefei Hao¹, Xiaojun Yao², Wenchao Yang³, Joint Supervisor⁴
Close Partner: Xiaorui Wang, Special-term Associate Professor at School of Synthetic Biology, Shenzhen University of Technology, Research Direction: AI Synthesis Planning

📝 Selected Publications

[1] Li et al. An adaptive graph learning method for automated molecular interactions and properties predictions. Nature Machine Intelligence IF=29.8 [HTML] [PDF]

[2] Li et al. Introducing block design in graph neural networks for molecular properties prediction. Chemical Engineering Journal IF=12.5 [HTML] [PDF]

[3] Li* et al. Spectral decomposition of chemical semantics for activity cliffs-aware molecular property prediction. Advanced Science IF=14.1 [HTML] [PDF]

[4] Li* et al. Learning hierarchical interaction for accurate molecular property prediction. Communications Chemistry IF=6.2 [HTML] [PDF]

All Publications

2026

  • [2026b] Chaoyang Xie, Junhu Xu, Guangyi Huang, Shihang Wang, Mutian He, Xinyu Dong, Huiyang Hong, Xiaojun Yao, Qi Wang*, Yuquan Li*. Spectral decomposition of chemical semantics for activity cliffs-aware molecular property prediction[J]. Advanced Science, 2026: e17579. [HTML] [PDF]
  • [2026a] Huiyang Hong, Xinkai Wu, Hongyu Sun, Chaoyang Xie, Qi Wang*, Yuquan Li*. Learning hierarchical interaction for accurate molecular property prediction[J]. Communications Chemistry,2026. [HTML] [PDF]
  • [2026c] Chaoyang Xie, Xiaorui Wang, Yawen Dong, Xiaojun Yao*, Gefei Hao*, Yuquan Li*. Reshaping the drug discovery ecosystem with open science and collaborative innovation[J]. The Innovation Drug Discovery, 2026, 1(1): 100016. [HTML] [PDF]

2025

  • [2025c] Yanan Tian, Ruiqiang Lu, Xiaoqing Gong, Yuquan Li, Wei Zhao, Xiaorui, Wang, Xinming Jia, Qin Li, Yuwei Yang, Henry H. Y. Tong, Joel P. Arrais*, Huanxiang Liu*, Xiaojun Yao*. Enhancing Kinase-Inhibitor Activity and Selectivity Prediction Through Multimodal and Multiscale Contrastive Learning with Attention Consistency[J]. Nature Communications,2025,16:10860. [HTML] [PDF]
  • [2025b] Xiaorui Wang†, Xiaodan Yin†, Xujun Zhang†, Huifeng Zhao, Shukai Gu, Zhenxing Wu, Odin Zhang, Wenjia Qian, Yuansheng Huang, Yuquan Li, Dejun Jiang, Mingyang Wang, Huanxiang Liu, Xiaojun Yao*, Chang-Yu Hsieh*, Tingjun Hou*. A virtual platform for automated hybrid organic-enzymatic synthesis planning[J]. Nature Communications,2025,16:10929. [HTML] [PDF]
  • [2025a] Zhenglu Chen, Chunbin Gu*, Shuoyan Tan, Xiaorui Wang, Yuquan Li, Mutian He, Ruiqiang Lu, Shijia Sun, Chang-Yu Hsieh*, Xiaojun Yao*, Huanxiang Liu*, Pheng-Ann Heng. Interpretable PROTAC Degradation Prediction With Structure-Informed Deep Ternary Attention Framework[J]. Advanced Science, 2025. [HTML] [PDF]

2024

  • [2024a] Xiaorui Wang, Xiaodan Yin, Dejun Jiang, Huifeng Zhao, Zhenxing Wu, Odin Zhang, Jike Wang, Yuquan Li, Yafeng Deng, Huanxiang Liu, Pei Luo, Yuqiang Han, Tingjun Hou*, Xiaojun Yao*, Chang-Yu Hsieh*. Multi-modal deep learning enables efficient and accurate annotation of enzymatic active sites[J]. Nature Communications, 2024, 15(1): 7348. [HTML] [PDF]

2023

  • [2023a] Xiaorui Wang†, Chang-Yu Hsieh†, Xiaodan Yin, Jike Wang, Yuquan Li, Yafeng Deng, Dejun Jiang, Zhenxing Wu, Hongyan Du, Hongming Chen, Yun Li, Huanxiang Liu, Yuwei Wang, Pei Luo, Tingjun Hou*, Xiaojun Yao*. Generic Interpretable Reaction Condition Predictions with Open Reaction Condition Datasets and Unsupervised Learning of Reaction Center[J]. Research, 2023, 6: 0231. [HTML] [PDF]

2022

  • [2022a] Yuquan Li†, Chang-Yu Hsieh†, Ruiqiang Lu, Xiaoqing Gong, Xiaorui Wang, Pengyong Li, Shuo Liu, Yanan Tian, Dejun Jiang, Jiaxian Yan, Qifeng Bai, Huanxiang Liu, Shengyu Zhang , Xiaojun Yao*. An adaptive graph learning method for automated molecular interactions and properties predictions[J]. Nature Machine Intelligence, 2022, 4(7):645-651. [HTML] [PDF]

2021

  • [2021c] Pengyong Li†, Yuquan Li†, Chang-Yu Hsieh, Shengyu Zhang, Xianggen Liu, Huanxiang Liu, Sen Song*, Xiaojun Yao*. TrimNet: learning molecular representation from triplet messages for biomedicine[J]. Briefings in Bioinformatics, 2021, 22(4): bbaa266.[HTML] [PDF]
  • [2021b] Xiaorui Wang†, Yuquan Li†, Jiezhong Qiu, Guangyong Chen, Huanxiang Liu, Benben Liao*, Chang-Yu Hsieh*, Xiaojun Yao*. RetroPrime: A Diverse, plausible and Transformer-based method for Single-Step retrosynthesis predictions[J]. Chemical Engineering Journal, 2021, 420: 129845. [HTML] [PDF]
  • [2021a] Yuquan Li, Pengyong Li, Xing Yang, Chang-Yu Hsieh, Shengyu Zhang, Xiaorui Wang, Ruiqiang Lu, Huanxiang Liu, Xiaojun Yao*. Introducing block design in graph neural networks for molecular properties prediction[J]. Chemical Engineering Journal, 2021, 414: 128817. [HTML] [PDF]

*Corresponding Author †Co-first Author

🌟 Honors & Awards

2025.9
2024.10
 "Exploration" Journal 2025 Outstanding Youth Editorial Board Member Award
Guizhou University First-class Discipline Construction Special Talent Introduction

🏛️ Academic Activities

2026.5
2026.5
2026.3
2026.1
2026.1
2025.11
2025.10
2023.3
Membership
Review
Editorial
 Appointed Expert of the National Graduate Education Evaluation and Monitoring Expert Pool, reviewing Master's and Doctoral dissertations
The Innovation Drug Discovery Youth Editorial Board
The Innovation Youth Editorial Board
Exploration Inaugural International Symposium on Plant Science, Chair
The 6th International Conference on Green Plant Protection Innovation, Talk: AI-Driven Essential-Gene Mining and RNAi Pesticide Design
Yangzhou University, "Green Agriculture" Academic Lecture Series, Talk: AI-Assisted Pesticide Design
The 14th National Conference on Bioinformatics and Systems Biology, Talk: Multi-Objective Gradient-Guided Molecular Generation
Lanzhou University, 15th Graduate Academic Annual Meeting, Talk: Chemistry × AI — Present and Future
Member of the China Society of Plant Protection, Chinese Association for Artificial Intelligence, China Computer Federation, Chinese Chemical Society, and others
Reviewer for iMeta, Nature Communications, Advanced Science, Briefings in Bioinformatics, JCIM, and others
As Academic Editor (Executive), handled editorial work for The Innovation Drug Discovery (Youth Editorial Board interview-panel chair ×3; full manuscript handling ×5); as a Youth Editorial Board member, contributed to iMeta (organizing a Bioinformatics Special Issue)

🙌 Others

ARAM, War3 RPG/RTS, DNF
Proud owner of five “Fire-Stick” Dragon-Slaying Sabers in Legend of Mir
I know all too well that no two people walk the same path—so I lie in a bed that is mine alone.
Associate Editor (AE) of the “world-class bottom-tier” journal Silence
Associate Editor (AE) of the “world-class bottom-tier” journal Call