Education

• B.S. in Computer Science & Technology, IEEE Honor Class, Shanghai Jiao Tong University, 2017-2021
• Ph.D in Computer Science & Technology, Shanghai Jiao Tong University, 2021-2026 (expected)

Research Interest

• Generative Models
• Out-of-Distribution Generalization
• AI-aided Drug Discovery
• Graph Neural Networks

Internship

• Dynamic Multi-graph Embedding for Recommendation
  • Meituan
  • April 2021 - August 2021
  • Honored with 2020-2021 Best Research Collaboration Award
• Drug AI
  • Research Intern, Tencent AI Lab
  • November 2022 - Present
  • Co-supervised by Dr. Jiaxiang Wu and Dr. Yatao Bian.

Research Experience

• April 2019 - July 2020: Research Assistant
  • Advanced Network Lab, SJTU
  • Supervisor: Prof. Xiaofeng Gao
• 🌟 August 2020 - Now: Research Assistant
  • 💞️ ThinkLab, SJTU
  • Supervisor: Prof. Junchi Yan

Publications

EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning

MoleRec: Combinatorial Drug Recommendation with Substructure-Aware Molecular Representation Learning

Learning Substructure Invariance for Out-of-Distribution Molecular Representations

Molecule Generation for Drug Design: a Graph Learning Perspective

Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation

Middle Layer Based Scalable Learned Index Scheme

Award

• Huatai Securities Science & Technology Scholarship, 2023
• SJTU Merit Student, 2023
• SJTU Academic Scholarship, 2018

Academic Service

Journal refereeing: IEEE Access, TNNLS, Neural Networks

Conference refereeing:

• NeurIPS 2023
• ICML 2024
• ICLR 2024
• LOG 2023
• IJCAI 2024
• GenBio@NeurIPS2023