Hi, it's Zhaocheng.

I am a final-year Ph.D. candidate at Mila - Quebec AI Institute, University of Montreal, advised by Prof. Jian Tang. Prior to that, I obtained my B.S. in Computer Science from Peking University.

My research focuses on machine learning and its applications on large-scale data, with an emphasis on structured and relational data like knowledge graphs and biomedical networks. I work on graph representation learning, machine learning systems and drug discovery. Besides, I also have a deep interest in computer vision and natural language processing, particularly in understanding how human and AI process information. See my CV for full details.

I believe that principles are more essential than solutions, and should come first in most cases. I also have a great fondness for elegant and efficient designs. These values motivated most of my works.


In my spare time, I enjoy photography a lot. Together with hiking, these hobbies drive me to explore the beauty of the land, as well as learn about myself and life.

Click the images to zoom in and browse more.

Selected Publications

Neural-Symbolic Models for Logical Queries on Knowledge Graphs
Zhaocheng Zhu, Mikhail Galkin, Zuobai Zhang, Jian Tang
ICML 2022   Paper / Code
TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery
Zhaocheng Zhu, Chence Shi, Zuobai Zhang, Shengchao Liu, Minghao Xu, Xinyu Yuan, Yangtian Zhang, Junkun Cheng, Huiyu Cai, Jiarui Lu, Chang Ma, Runcheng Liu, Louis-Pascal Xhonneux, Meng Qu, Jian Tang
arXiv 2022 (31k+ downloads)   Paper / Website / Tutorial / Code
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
Zhaocheng Zhu, Zuobai Zhang, Louis-Pascal Xhonneux, Jian Tang
NeurIPS 2021
Paper / Code (original) / Code (new) / Code (PyG) / OGB-LSC
GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding
Zhaocheng Zhu, Shizhen Xu, Meng Qu, Jian Tang
WWW 2019 (5k+ downloads)   Paper / Website / Tutorial / Code