Machine Learning Laboratory
The Machine Learning Laboratory research focuses on building human-machine collaborative AI systems that can learn context-aware and explainable models from multi-source and interconnected data. We are developing graph-based deep learning techniques for time-series prediction and natural language processing.
Director
Students
PhD advisees
Master’s advisees
Undergraduate advisees
- Tran Chau
- Yuan Chen
- Joshua Matthew
- Sophia Pentakalos
- Mia Taylor
Alumni
- Milad Afzalan MS 2020 - ENGIE North America - Data Scientist
Committee membership
PhD committees
- Mohamed W. Hassan
- Seifeldeen Eteifa
- Xinyue Wang