Dr. Wang, Minjie
PhD New York University
Adjunct Associate Professor
Email: minjiewang@hkushxlab.com
Homepage: https://scholar.google.com/citations?user=OJja8NgAAAAJ&hl=en
Dr. Minjie Wang received his Ph.D. in Computer Science from New York University and his bachelor’s degree from the ACM Honor Class at Shanghai Jiao Tong University. He currently serves as the Executive Director of the HKU Shanghai Cross Innovation Lab.
Prior to joining HKU, Dr. Wang was a Principal Applied Scientist at Amazon Web Services and one of the youngest Principal Applied Scientists in the Asia-Pacific region. At AWS, he worked on enterprise AI systems, leading the design of AI agent architectures and evaluation frameworks for large-scale applications.
Dr. Wang is a key contributor to deep learning systems and graph machine learning. He initiated and led several globally influential open-source projects, including Apache MXNet—Amazon’s preferred deep learning framework—and the Deep Graph Library (DGL), one of the most widely adopted frameworks for graph machine learning. DGL has been deployed by many enterprises worldwide and has supported large-scale production systems in industry.
Research Interests
Dr. Wang’s research focuses on the intersection of machine learning systems, structured data intelligence, and AI agents. His current research interests include:
- Graph Machine Learning and Relational Learning
- Algorithms and systems for learning from graph and relational data
- Machine Learning Systems and Infrastructure
- Scalable systems for deep learning, including compilers, runtimes, and distributed training frameworks.
- Foundation Models for Structured Data
- Developing foundation models capable of reasoning over structured data such as tables, graphs, and relational databases.
- AI Agents and Intelligent Systems
- Architectures and evaluation frameworks for AI agents operating in real-world enterprise environments.