Yang Menglin

Location: SHB 1024; The Chinese University of Hong Kong; Shatin, N.T., Hong Kong
Email: mlyang at cse.cuhk.edu.hk     
[GitHub]

About Me

I am third-year PhD student from Department of Computer Science and Engineering;
The Chinese University of Hong Kong (CUHK) advised by Prof. Irwin King. I am interested
in the (temporal) graph representation learning, hyperbolic/sphere/semi-Riemannian space
embedding, and machine learning theory. Currently, I focus on the following research topics:

• Graph theory for graph embedding
• Temporal network embedding
• Hyperbolic represenation learning
• Recommender system
• Knowledge graph
• Graph-based Drug discovery

Welcome outstanding undergraduates and Master/PhD students to visit our WISC laboratory
and cooperate with me for graph-related research. If you are interested, just drop an email
to me and Prof. King.

Recent Publications

• [KDD 2021] Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning in Hyperbolic Space (acceptance rate: 15.4%) [pdf] [code]
  Menglin Yang, Min Zhou, Marcus Kalander, Zengfeng Huang, Irwin King


• [ICDM 2020] FeatureNorm: L2 Feature Normalization for Dynamic Graph Embedding (acceptance rate: 9.8%) [pdf] [code]
  Menglin Yang, Ziqiao Meng, Irwin King


• [WSDM 2022] Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation (acceptance rate: 20.23%) [pdf]
  Yankai Chen, Menglin Yang, Yingxue Zhang, Mengchen Zhao, Ziqiao Meng, Jian Hao, Irwin King


• [ICDE 2022] Discovering Representative Attribute-stars via Minimum Description Length.
  Jiahong Liu, Philippe Fournier-Viger, Min Zhou, Lujia Pan, Menglin Yang


• [NeurIPS 2021 Workshop] Enhancing Hyperbolic Graph Embeddings via Contrastive Learning
  Authors(to be updated)

Reviewer

• ICML 2020
• ICML 2021
• NeurIPS 2021
• ICLR 2022
• WebConf 2022

Teaching

• CSCI2100A Data Structure
• ENGG 2760A / ESTR 2018: Probability for Engineers