黎育权 特聘教授C岗硕士生导师 研究领域：人工智能(大语言模型、图学习、自动机器学习)、科学智能(人工智能分子设计) 招生专业：电子信息 招生方向：公共大数据融合与集成 通信地址：贵州省贵阳市贵州大学西校区崇厚楼822 电子邮件：yvquan.li@gzu.edu.cn 个人网页：http://yvquanli.github.io/  个人简介 黎育权，特聘教授，硕导，目前就职于贵州大学公共大数据国家重点实验室。兰州大学硕博连读提前毕业博士，在读期间曾前往腾讯公司量子实验室进行两年期联合培养，合作导师为谢昌谕博士。 长期从事AI基础研究和AI分子设计应用研究，相关成果以第一/通讯作者身份在Nature Machine Intelligence、Chemical Engineering Journal、Briefings in Bioinformatics在内的多个期刊发表。截至目前，在Nature Machine Intelligence, Nature Communication等期刊共发表SCI论文10篇，其中一作或通讯身份4篇，篇均引用57次。担任Exploration期刊青年编委。依托国家重点实验室的优势和个人联系可与浙江大学和上海交通大学相关团队老师共同联合指导学生，共同助力学生论文的发表和产出。
发表论文[1]Yuquan Li, et al. An adaptive graph learning method for automated molecular interactions and properties predictions. Nature Machine Intelligence. 2022. (第一作者，Nature子刊，当年IF=23.8，中科院1区) [2]Yuquan Li, et al. Introducing block design in graph neural networks for molecular properties prediction[J]. Chemical Engineering Journal. 2021. (第一作者，当年IF=16.7，中科院1区) [3]Xiaorui Wang†, Yuquan Li†, et al. RetroPrime: A Diverse, plausible and Transformer-based method for Single-Step retrosynthesis predictions. Chemical Engineering Journal. 2021. (共同第一作者，当年IF=16.7，中科院1区) [4]Pengyong Li†, Yuquan Li†, et al. TrimNet : learning molecular representation from triplet messages for biomedicine[J]. Briefings in Bioinformatics. 2021. (共同第一作者，当年IF=13.9，中科院2区) [5]Xiaorui Wang, Xiaodan Yin, Dejun Jiang, Huifeng Zhao, Zhenxing Wu, Odin Zhang, Jike Wang, Yuquan Li, et al. Multi-modal deep learning enables efficient and accurate annotation of enzymatic active sites. Nature Communications. 2024. (合作作者，Nature子刊，当年IF=14.7，中科院1区) [6]Shuo Liu, Jialiang Yu, Ningxi Ni, Zidong Wang, Mengyun Chen, Yuquan Li, et al. Versatile Framework for Drug–Target Interaction Prediction by Considering Domain-Specific Features. Journal of Chemical Information and Modeling. 2024. (合作作者，当年IF=5.6，中科院2区) [7]Xiaodan Yin, Xiaorui Wang, Yuquan Li, et al. CODD-Pred: A Web Server for Efficient Target Identification and Bioactivity Prediction of Small Molecules. Journal of Chemical Information and Modeling. 2023. (合作作者，当年IF=5.6，中科院2区) [8]Ruiqiang Lu, Jun Wang, Pengyong Li, Yuquan Li, et al. Improving drug-target affinity prediction via feature fusion and knowledge distillation. Briefings in Bioinformatics. 2023. (合作作者，当年IF=6.8，中科院2区) [9]Xiaorui Wang, Chang-Yu Hsieh, Xiaodan Yin, Jike Wang, Yuquan Li, et al. Generic Interpretable Reaction Condition Predictions with Open Reaction Condition Datasets and Unsupervised Learning of Reaction Center. Research. 2023. (合作作者，当年IF=8.5，中科院1区) [10]Dejun Jiang, Huiyong Sun, Jike Wang, Chang-Yu Hsieh, Yuquan Li, et al. Out-of-the-box deep learning prediction of quantum-mechanical partial charges by graph representation and transfer learning. Briefings in Bioinformatics. 2022. (合作作者，当年IF=6.8，中科院2区)
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