My research focuses on creating label-efficient and explainable deep learning models for medical imaging to improve clinical workflow and patient care. In particular, I am excited about exploring the following directions. Multimodal learning: How can we efficiently integrate information from different modalities (e.g. imaging, text, tabular data, sequential data) to better inform clinical decisions? Explainable AI: Can we enable computer-aided diagnosis systems to explain their reasoning in a way that mimics how humans communicate? Human-AI collaboration: What is the optimal way to present an AI’s diagnosis to clinicians so they can collaborate effectively to maximize patient outcomes?