I am a Research Assistant at National University of Singapore (NUS), supervised by Vaibhav Rajan. I submitted my doctoral thesis in Oct. 2023 and was a Ph.D. student in School of Computing at The Australian National University (ANU). My Ph.D. supervisors are Prof. Yu Lin, Vaibhav Rajan, and Lexing Xie. Before coming to ANU, I obtained my M.Eng. degree in computer science at Harbin Institute of Technology (HIT) in 2018, under the supervision of Prof. Yadong Wang and Jiajie Peng. I earned my B.M. degree from Nanjing Tech University (NJTech) in 2015. I also had the opportunity to visit or intern at NPU, Fudan, NUS, BioMap, and Alibaba Group during my academic pursuits.

My research interests span across Machine Learning and Computational Biology, focusing on representation learning on graphs, combinatorial optimization, and their practical applications in computational genomics, functional genomics, and healthcare.

1. Graph Neural Networks: Temporal, Bipartite, and Multiplex/Multi-View Networks;
2. Computational Genomics: Metagenomic Contigs Binning, and Haplotype Phasing;
3. Healthcare: Drug Reponse Prediction, Function Prediction, and Disease Diagnosis.

I am on the job market for faculty or postdoc positions! Please feel free to reach out if you have potential opportunities.

Selected Publications [Google Scholar, DBLP]

• Encoding Unitig-level Assembly Graphs with Heterophilous Constraints for Metagenomic Contigs Binning
  Hansheng Xue, Vijini Mallawaarachchi, Lexing Xie, and Vaibhav Rajan
  Twelfth International Conference on Learning Representations (ICLR), 2024.
  
• Graph Coloring via Neural Networks for Haplotype Assembly and Viral Quasispecies Reconstruction
  Hansheng Xue, Vaibhav Rajan, and Yu Lin
  Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022.
  
• RepBin: Constraint-based Graph Representation Learning for Metagenomic Binning
  Hansheng Xue, Vijini Mallawaarachchi, Yujia Zhang, Vaibhav Rajan, and Yu Lin
  The 36th AAAI Conference on Artificial Intelligence (AAAI), 2022.
  
• Multiplex Bipartite Network Embedding using Dual Hypergraph Convolutional Networks
  Hansheng Xue, Luwei Yang, Vaibhav Rajan, Wen Jiang, Yi Wei, and Yu Lin
  The 30th International World Wide Web Conference (WWW), 2021.
• Modeling Dynamic Heterogeneous Network for Link Prediction using Hierarchical Attention with Temporal RNN
  Hansheng Xue, Luwei Yang, Wen Jiang, Yi Wei, Yi Hu, and Yu Lin
  European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), 2020.
  
• Integrating Multi-network Topology for Gene Function Prediction using Deep Neural Networks
  Jiajie Peng†, Hansheng Xue†, Zhongyu Wei, Idil Tuncali, Jianye Hao, and Xuequn Shang
  Briefings in Bioinformatics, 2020.
• Personalised Drug Identifier for Cancer Treatment with Transformers using Auxiliary Information
  Aishwarya Jayagopal, Hansheng Xue, Ziyang He, Robert J Walsh, Krishna Kumar Hariprasannan, David Shao Peng Tan, Tuan Zea Tan, Jason J Pitt, Anand D Jeyasekharan, and Vaibhav Rajan
  ArXiv, 2024.
• Graph Representation Learning for Structured Data and Genomic Analysis
  Hansheng Xue, Phd Thesis, The Australian National University, March 2024.