My research is at the intersection of medical vision (medical image analysis), machine learning, and bioinformatics. I develop algorithms to analyze and understand medical images, genetic data, and other electrical health records, such as clinical reports. The main themes of research in my lab are about the main challenges of AI in healthcare: (1) Explainability, (2) Data Efficiency, (3) Multimodal Data Fusion, and Causality. My lab works on Alzheimer’s, Chronic Obstructive Pulmonary Disease (COPD), and Non-Alcoholic Fatty Liver Disease (NAFLD) projects. Our research is supported by funding from NIH, NSF, and industry awards. I am co-founder of MLxMed, a multi-campus online similar series focusing on ML methods specifically for healthcare applications. I am co-founder of READE.ai, a start-up about the Realtime Evaluation of Adverse Events during surgery.