Research Labs
From developing novel AI methods to improving healthcare delivery, the Division of Computational Medicine’s faculty-led laboratories are advancing the science and practice of computational medicine. Our investigators bring together expertise in biomedical informatics, machine learning, biostatistics, genomics, implementation science, and health services research to address complex challenges in medicine.
Principal Investigator: Jonathan Chen, MD, PhD
Designing and evaluating clinical decision support systems and applying machine learning to improve patient care.
Principal Investigator: Manisha Desai, MD, PhD
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Principal Investigator: Olivier Gevaert, PhD
Applying artificial intelligence and multimodal data integration to precision oncology and biomedical discovery.
Principal Investigator: Tina Hernandez-Boussard, PhD, MPH
Using data science to improve healthcare quality, outcomes, equity, and health policy.
Principal Investigator: Daniel Katz, MD
Advancing learning health systems and leveraging clinical data to improve quality, safety, and healthcare delivery.
Principal Investigator: Purvesh Khatri, PhD
Leveraging systems immunology and computational approaches to advance precision medicine and identify clinically actionable biomarkers.
Principal Investigator: Mark A. Musen, MD, PhD
Developing biomedical ontologies, knowledge representation methods, and tools that enable the organization, integration, and sharing of scientific knowledge.
Principal Investigator: Elior Rahmani, PhD
Developing statistical and machine learning methods to uncover insights from large-scale genomic and biomedical datasets.
Principal Investigator: Shriti Raj, PhD
Investigating how genetic variation shapes cellular function and disease through integrated computational and experimental approaches.
Principal Investigator: Nigam H. Shah, MBBS, PhD
Advancing artificial intelligence, biomedical informatics, and learning health systems to improve healthcare delivery and patient outcomes.