Explainable AI for Computational Biology, Healthcare, and Medicine

The goal of our research is to conceptually and fundamentally advance the way AI is integrated with biomedicine by addressing novel, forward-looking, and stimulating scientific questions, enabled by AI advances. Our lab develops various computational biology approaches using AI and ML for a broad spectrum of applications from basic biology to bedside applications, in addition to fundamental AI and machine learning research. Current research themes include:

  • Foundational AI/ML advances

  • Cancer biology and precision medicine

  • Alzheimer's disease (AD) therapeutic target discovery

  • Unsupervised deep learning for gene expression and multi-modal data

  • AI for clinical medicine and healthcare

    • Emergency medicine

    • Biology of aging

  • Model and data auditing

    • Radiology

    • Dermatology

Research keywords:

  • Computational biology & medicine - precision medicine, systems biology, & genetics

  • Machine learning - explainable AI, interpretability, feature selection, & probabilistic graphical models

Selected Talks

AI & Precision Medicine - UW Medicine "Science in Medicine" lecture

Interpretable ML in Precision Medicine - UW AI Seminar

Interpretable Machine Learning for Precision Medicine

  • Selected as the best talk at Computational Genomics Winter Institute (CGWI) 2018