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