荣誉与获奖
国际荣誉与奖励
l 亚马逊机器学习研究奖（2020）
l 全球高被引科学家（ 科睿维安，2020，2021，2022，2023）
l 中国高被引学者（爱思唯尔，2021，2022，2023）
l 全球前十万名科学家（全球学者库，2020，2021，2022）
l 全球前2%顶尖科学家（Stanford University，2020，2021，2022）
l 世界人工智能大会“卓越引领者奖（SAIL奖）”榜单（2020）
l 第二十届智能计算国际会议（ICIC）Best Paper Award（2024）
l Cell出版社中国年度最佳论文（2021）
l 国际膜计算学会（IMCS）年度Best Paper Award（2020）
国内荣誉与奖励
l 国家高层次人才计划（2024，编号：62425204）
l 全国人工智能应用场景创新挑战赛“优秀指导老师”（2023）
l 中国智能计算科技创新人物（麻省理工科技评论-DeepTech，2022）
l 国家高层次青年人才计划（2021，编号：62122025）
l 吴文俊人工智能优秀青年奖（2019）
l 2020年度中国“学术媒体公众号Top10”（创始人）
l 湖南省杰青（2020，编号：2021JJ10020）
l 福建省自然科学奖三等奖（2021，第一完成人）
l 福建省教学成果奖二等奖（2018）
l CCF科学技术奖技术发明二等奖（2021）
l 湖南大学岳麓学者（特聘岗，2020）
l 湖南大学岳麓学者（晨星岗，2019）
l 厦门大学教学成果奖特等奖（2017）
l 厦门大学春雨奖教金（2015）
l 厦门大学游泳比赛教工组200米蛙泳冠军，100米自由泳冠军，4*50接力亚军
l 武汉716横渡长江大赛金镶玉奖章（2009）
l 湖南大学天马杯象棋大赛冠军
学术著作
出版书籍
宋弢，曾湘祥，王爽，王建民，智能药物研发，清华大学出版社，2022（国内首本人工智能药物研发教材，京东购买链接）
Pan Zheng, Shudong Wang, Xun Wang and Xiangxiang Zeng, Artificial Intelligence in Bioinformatics and Drug Repurposing: Methods and Applications. 2022.
Xiangxiang Zeng, Alfonso Rodríguez-Patón, Molecular Computing and Bioinformatics, MDPI, 2019.
邹权，陈启安，曾湘祥，刘向荣，系统生物学中的网络分析方法，西安电子科技大学出版社，2015.
潘林强，曾湘祥，宋弢，膜计算导论，华中科技大学出版社，2012.
2024年论文
[19] Houtim Lai, Longyue Wang, Ruiyuan Qian, Junhong Huang, Peng Zhou, Geyan Ye, Fandi Wu, Fang Wu, Xiangxiang Zeng, Wei Liu. Interformer: an interaction-aware model for protein-ligand docking and affinity prediction. Nature Communications 15, 10223, 2024. (Nature子刊)
[18] Pengyong Li, Kaihao Zhang, Tianxiao Liu, Ruiqiang Lu, Yangyang Chen, Xiaojun Yao, Lin Gao, Xiangxiang Zeng, A Deep Learning Approach for Rational Ligand Generation with Toxicity Control via Reactive Building Blocks, Nature Computational Science. 2024. (Nature子刊)
[17] Hongxin Xiang, Li Zeng, Linlin Hou, Kenli Li, Zhimin Fu, Yunguang Qiu, Ruth Nussinov, Jianying Hu, Michal Rosen-Zvi, Xiangxiang Zeng, Feixiong Cheng, A Molecular Video-derived Foundation Model Streamlines Scientific Drug Discovery, Nature Communications, 2024. (Nature子刊)
[16] Tingting Li, Xuanbai Ren, Xiaoli Luo, Zhuole Wang, Zhenlu Li, Xiaoyan Luo, Jun Shen, Yun Li, Dan Yuan,Ruth Nussinov, Xiangxiang Zeng, Junfeng Shi, Feixiong Cheng, A Foundation Model Identifies Broad-Spectrum Antimicrobial Peptides against Drug-Resistant Bacterial Infection, Nature Communications, 2024, doi.org/10.1038/s41467-024-51933-2. (Nature子刊)
[15] Xuanbai Ren, J. Wei, X. Luo, Y. Liu, K. Li, Q. Zhang, X. Gao, S. Yan, X. Wu, X. Jiang, M. Liu, D. Cao, L. Wei, Xiangxiang Zeng, Junfeng Shi, HydrogelFinder: A Foundation Model for Efficient Self-Assembling Peptide Discovery Guided by Non-Peptidal Small Molecules. Advanced Science, 2024, 11, 2400829. (IF: 15.1)
[14] Hongxin Xiang, Shuting Jin, Jun Xia, Man Zhou, Jianmin Wang, Li Zeng, Xiangxiang Zeng. An Image-enhanced Molecular Graph Representation Learning Framework, IJCAI, 2024 (CCF A)
[13] Taisong Jin; Xixi Yang; Zhengtao Yu, Han Luo, Yongmei Zhang, Feiran Jie, Xiangxiang Zeng, Min Jiang, WalkGAN: Network Representation Learning With Sequence-Based Generative Adversarial Networks, IEEE Transactions on Neural Networks and Learning Systems, 2024, 35(4), 5684-5694.
[12] Jiacai Yi, Shaohua Shi, Li Fu, Ziyi Yang, Pengfei Nie, Aiping Lu, Chengkun Wu, Yafeng Deng, Changyu Hsieh, Xiangxiang Zeng, Tingjun Hou, Dongsheng Cao. OptADMET: a web-based tool for substructure modifications to improve ADMET properties of lead compounds, Nature Protocols, 2024, 19(4):1105-1121. (Nature子刊)
2023年论文
[11] Yu Wang, Chao Pang, Yuzhe Wang, Junrui Jin, Jingjie Zhang, Xiangxiang Zeng, Ran Su, Quan Zou, Leyi Wei. Retrosynthesis prediction with an interpretable deep-learning framework based on molecular assembly tasks. Nature Communications 14, 6155 (2023). (Nature子刊)
[10] Shugao Chen, Ziyao Li, Xiangxiang Zeng, Guolin Ke. Amalga: Designable Protein Backbone Generation with Folding and Inverse Folding Guidance, NeurIPS, 2023 (CCF A)
[9] Bin Wu, Jinyuan Fang, Xiangxiang Zeng, Shangsong Liang, Qiang Zhang, Adaptive Compositional Continual Meta-Learning, ICML 2023 (CCF A)
[8] Xixi Yang, Li Fu, Yafeng Deng, Yuansheng Liu, Dongsheng Cao, Xiangxiang Zeng, GPMO: Gradient perturbation-based contrastive learning for molecule Optimization , IJCAI 2023. (CCF A)
[7] Peng Zhou, Zongqian Wu, Xiangxiang Zeng, Guoqiu Wen, Junbo Ma, Xiaofeng Zhu, Totally Dynamic Hypergraph Neural Network , IJCAI 2023. (CCF A)
[6] Chunyan Li, JunfengYao, Jinsong Su, Zhaoyang Liu, Xiangxiang Zeng, Chenxi Huang, LagNet: Deep Lagrangian Mechanics for Plug-and-Play Molecular Representation Learning, AAAI 2023. (CCF A)
[5] Junlin Xu, Jielin Xu, Yajie
Meng, Changcheng Lu, Lijun Cai, Xiangxiang Zeng, Ruth Nussinov, Graph Embedding and Gaussian Mixture Variational
Autoencoder Network for End-to-End Analysis of Single-Cell RNA-Sequencing Data. Cell Reports Methods. 2023. (Cell子刊)
2022年论文
[4] Xiangxiang Zeng, Hongxin Xiang, Linhui Yu, J Wang, Kenli Li, R Nussinov, Feixiong Cheng. Accurate prediction of molecular properties and molecular targets usinga self-supervised image representation learning framework. Nature Machine Intelligence.2022. (Nature子刊)
[3] Xiangxiang Zeng, Fei Wang, Yuan Luo, Seung-gu Kang, Jian Tang, Felice C. Lightstone, Evandro F. Fang, Wendy Cornell, Ruth Nussinov, Feixiong Cheng, Deep Generative Molecular Design Reshapes Drug Discovery, Cell Reports Medicine, 2022. (Cell子刊)
[2] Xiaoqin Pan, Xuan Lin, Dongsheng Cao, Xiangxiang Zeng, Phillipe Yu, Lifang He, Feixiong Cheng. Deep learning for drug repurposing:Methods,databases, and applications. WIREs Comput Mol Sci. 2022; e1597. (IF:25.11)
[1] Chunyan Li , Junfeng Yao, Wei Wei, Zhangming Niu , Xiangxiang Zeng, Jin Li , Jianmin Wang, Geometry-Based Molecular Generation With Deep Constrained Variational Autoencoder, IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2022.3147790.(IF:10.451)
更多论文请见：//scholar.google.com/citations?user=B20HBMIAAAAJ&hl=en
科研项目
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