My research interests lie in machine learning, deep learning and artificial intelligence. My long-term goal is to develop intelligent systems, which can learn from a massive volume of complex (e.g., weakly-supervised, adversarial, and private) data (e.g, single-/multi-label, ranking, domain, similarity, graph, and demonstration) automatically. Recently, I develop core machine learning methodology. Besides, I am actively applying our fundamental research into the healthcare domain (e.g., electronic health records analysis and medical image understanding).
My current research work center around four major themes:
Weakly-supervised Machine Learning: How can we train complex models robustly using weakly-supervised information?
Security, Privacy and Robustness in Machine Learning: How can we preserve the security, privacy and robustness in training complex models?
Automated Machine Learning: How can we reason about intelligent systems without human intervention?
Interdisciplinary Problems: How can we apply the above fundamental research to the healthcare domain?