I’m currently a third-year computer science PhD student at Hunan University, advised by Associate Prof. Zhe Quan. Now, I’m also a visiting scholar in BDSC Lab at University of Illinois at Chicago, advised by Prof. Philip S. Yu. My research generally focuses on:
- Machine Learning
- Graph Neural Networks, Knowledge Graph
- New!! One paper has been accepted by IJCAI, 04/2020.
- New!! One paper has been accepted by ECAI, 01/2020.
KGNN: Knowledge Graph Neural Network for Drug-Drug Interaction Prediction.
Xuan Lin, Zhe Quan, Zhi-Jie Wang, Tengfei Ma, Xiangxiang Zeng.
The 29th International Joint Conference on Artifical Intelligence (IJCAI), 2020.
DeepGS: Deep Representation Learning of Graphs and Sequences for Drug-Target Binding Affinity Prediction.
Xuan Lin, Kaiqi Zhao, Tong Xiao, Zhe Quan, Zhi-Jie Wang, Philip S. Yu.
The 24th European Conference on Artifical Intelligence (ECAI), 2020, Santiago de Compostela.
GraphCPI: Graph Neural Representation Learning for Compound-Protein Interaction.
Zhe Quan, Yan Guo, Xuan Lin, Zhi-Jie Wang, Xiangxiang Zeng.
IEEE International Conference on Bioinformatics & Biomedicine (BIBM), 2019, San Diego, California, USA.
A Novel Molecular Representation with BiGRU for Learning Atoms.
Xuan Lin, Zhe Quan, Zhi-Jie Wang, Huang Huang, Xiangxiang Zeng.
Breifings in Bioinformatics (BIB), doi:10.1093/bib/bbz125.
A Novel Model for Imbalanced Data Classification.
Jian Yin, Chunjing Gan, Kaiqi Zhao, Xuan Lin, Zhe Quan, Zhi-Jie Wang.
The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020, New York, USA.
A System for Learning Atoms Based on Long Short-Term Memory Recurrent Neural Networks.
Zhe Quan, Xuan Lin, Zhi-Jie Wang, Yan Liu, Fan Wang, Kenli Li.
IEEE International Conference on Bioinformatics & Biomedicine (BIBM), 2018, Madrid, Spain.
- Reviewer: IJCAI 2019, IJCAI 2020, HPCC 2019.
- Invited Reviewer: Briefings in Bioinformatics, NeuroComputing, International Journal of Pattern Recognition and Artificial Intelligence.