Welcome.

I am Yaowen Ye (Elwin, or 叶耀文), a second-year undergraduate majoring in Computer Science at the University of Hong Kong. I have been deeply intrigued by research on machine intelligence since high school, and I hope to devote and contribute to this fantastic field in my future career. Currently, I am working with Dr. Chao Huang at Data Intelligence Lab@HKU, focusing on graph machine learning, self-supervised learning, and their applications on recommender systems.

Links:  [📮Email]  [📑Curriculum Vitae]

Research Interests

• 🎈 I’m interested in:
  • 🧠 Machine intelligence and abstract reasoning, especially studying the reasoning ability of deep-learning-based artificial intelligence.
  • ❄️ Learning on graphs, e.g., graph neural networks, and their application in knowledge graph reasoning, recommender systems, etc.
  • 🐷 Self-supervised learning, and how it can be applied to the upper-mentioned fields.
  • 📑 See [a short summary of my recent research experience and interests].
• 🧺 Other stuff:
  • 🤖️ I’m currently a member of HKU Astar, a fantastic while lack-of-fund RoboMaster-AI team.
  • 🎵 I love classical music, film music, harmony theory, and impromptu piano.
  • 📸 I love photography & cinematography.
  • 💬 Ask me anything! If you have the same interests as me, let’s be friends!

Publications

2023

Graph Masked Autoencoder for Sequential Recommendation.
     The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'23)
     Yaowen Ye, Chao Huang and Lianghao Xia. [pdf] [GitHub]

Masked Graph Transformer for Recommendation.
     The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'23)
     Chaoliu Li, Chao Huang, Lianghao Xia, Xubin Ren, Yaowen Ye and Yong Xu. [pdf]

Friends

• Henoru
• Another Henoru
• Yitao Liu (🌊God)
• Xuheng Cai
• Futrime
• Entong He