Xuan Lin (林 轩)
Associate Professor
School of Computer Science
Xiangtan University

Location: Engineering Building, #401, Yuhu District, Xiangtan, Hunan, China
About Me | Work Experience | Research Interests | Education | Publications | Grants | Professional Services |

Email: jack_lin@xtu.edu.cn
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About Me

 I am currently an associate professor in the School of Computer Science, Xiangtan University (XTU), P. R. China. Prior to joining XTU, I received my Ph.D. degree in School of Computer Science and Electronic Engineering from Hunan University in June 2021. Since October 2019 till August 2020, I was a visiting scholar at Univesity of Illinois at Chicago (UIC), under the supervison of Prof. Philip S. Yu. My research interests include multi-modal learning, large language model, and AI for drug discovery. I have published more than 20 technical papers in refereed conference proceedings such as AAAI, IJCAI, ECAI, and BIBM, and journals such as IEEE TKDE, TCBB, WIREs Computational Molecular Science and Briefings in Bioinformatics.

Work Experience

Research Interests

 My research interests include machine learning and graph neural networks for bioinformatics. Currently, I focus on the following research topics:

Education

Publications

  • Xuan Lin, Qingrui Liu, Hongxin Xiang*, Daojian Zeng, and Xiangxiang Zeng, “Enhancing chemical reaction and retrosynthesis prediction with large language model and dual-task learning,” The 34th International Joint Conference on Artificial Intelligence (IJCAI), 2025, accepted. [PDF] [Code]

  • Dan Luo, Jinyu Zhou, Le Xu, Sisi Yuan and Xuan Lin*, “DynamicDTA: drug-target binding affinity prediction using dynamics descriptors and graph representation,” Interdisciplinary Science: Computational Life Sciences, 2025: 1-16. [PDF] [Code]

  • Guosheng Han, Lingzhi Peng, Aocheng Ding, Yan Zhang and Xuan Lin*, “CTF-DDI: Constrained tensor factorization for drug–drug interactions prediction,” Future Generation Computer Systems, 161: 26-34, 2024. [PDF] [Code]

  • Xuan Lin, Xi Zhang, Zu-Guo Yu, Yahui Long*, Xiangxiang Zeng and Philip S. Yu, “CSCL-DTI: predicting drug-target interaction through cross-view and self-supervised contrastive learning,” 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024. [PDF] [Code]

  • Xuan Lin, Qi Wen, Sijie Yang, Zu-Guo Yu, Yahui Long*, and Xiangxiang Zeng, “Interpretable attention network with multi-view learning for drug-drug interaction prediction,” 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023. [PDF] [Code]

  • Xuan Lin, Lichang Dai, Yafang Zhou, Zu-Guo Yu, Wen Zhang, Jian-Yu Shi, Dong-Sheng Cao, Li Zeng, Haowen Chen*, Bosheng Song*, Philip S. Yu and Xiangxiang Zeng, “Comprehensive evaluation of deep and graph learning on drug–drug interactions prediction,” Briefings in Bioinformatics, 24(4): bbad235, 2023. [PDF] [Code]

  • Xuan Lin, Zhe Quan*, Zhi-Jie Wang, Yan Guo, Xiagxiang Zeng, Philip S Yu, “Effectively Identifying Compound-Protein Interaction using Graph Neural Representation,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 20(2): 932-943, 2022. [PDF] [Code]

  • Tengfei Ma, Xuan Lin*, Bosheng Song, Philip S Yu, Xiagxiang Zeng*, “KG-MTL: Knowledge Graph Enhanced Multi-Task Learning for Molecular Interaction,” IEEE Transactions on Knowledge and Data Engineering, 35(7): 7068-7081, 2022. [PDF] [Code]

  • Xiaoqin Pan, Xuan Lin*, Dongsheng Cao, Xiagxiang Zeng*, Philip S Yu, Lifang He, Ruth Nussinov, Feixiong Cheng, “Deep learning for drug repurposing: methods, databases, and applications,” WIREs Computational Molecular Science, e1597, 2022. [PDF], Highly Cited Paper

  • Kuan Li, Yue Zhong*, Xuan Lin*, Zhe Quan, “Predicting the disease risk of protein mutation sequences with pre-training model,” Frontiers in Genetics, 11, 1-10, 2020. [PDF] [Bibtex]

  • Xuan Lin, Zhe Quan, Zhi-Jie Wang*, Huang Huang, Xiangxiang Zeng, “A novel molecular representation with BiGRU neural networks for learning atom,” Briefings in Bioinformatics, 21 (6), 2099-2111, 2020. [PDF] [Bibtex]

  • Xuan Lin, Zhe Quan*, Zhi-Jie Wang*, Tengfei Yu, Ma, Xiangxiang Zeng, “KGNN: Knowledge Graph Neural Network for Drug-Drug Interaction Prediction,” The 29th International Joint Conference on Artifical Intelligence (IJCAI), 2739-2745, 2020. [PDF] [Bibtex] [Poster] [Code]

  • Xuan Lin, Kaiqi Zhao, Tong Xiao, Zhe Quan*, Zhi-Jie Wang*, Philip S Yu, “DeepGS: Deep Representation Learning of Graphs and Sequences for Drug-Target Binding Affinity Prediction,” The 24th European Conference on Artificial Intelligence (ECAI), 1-8, 2020. [PDF] [Bibtex] [Code]

  • Zhe Quan, Xuan Lin, Zhi-Jie Wang*, Yan Liu, Fan Wang, Kenli Li, “A System for Learning Atoms Based on Long Short-Term Memory Recurrent Neural Networks,” 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 728-733, 2018. [PDF] [Bibtex]


Grants

Professional Services

Conference Program Committee:

  • The International Joint Conference on Artificial Intelligence (IJCAI 2020-2025)
  • The AAAI Conference on Artificial Intelligence (AAAI 2021-2025)

Invited Journal Reviewer:

  • Briefings in Bioinformatics/Neurocomputing/Neural Networks/Frontiers in Genetics/International Journal of Pattern Recognition and Artificial Intelligence