CTO · CO-FOUNDER
Joel Saltz, MD, PhD
A pioneering computer scientist, physician, and informatician whose work connects AI, large-scale computing, and the practical use of complex data.
Joel earned his MD and a PhD in computer science at Duke University, followed by postgraduate training in clinical pathology at Johns Hopkins. He is board-certified in clinical pathology and clinical informatics.
A founding leader in biomedical informatics, he established and chaired departments at Ohio State, Emory, and Stony Brook. He is a Fellow of the American College of Medical Informatics.
Turning complex data into understanding.
His research turns pathology images into quantitative data, combining computer vision, machine learning, and large-scale computing to study tissue structure, cancer biology, and clinical outcomes. His group developed methods to map tumor-infiltrating lymphocytes across 13 cancer types.
He also played a foundational leadership role in the National COVID Cohort Collaborative (N3C), helping shape its architecture and leading a group that contributed tools for data curation, quality control, and analysis. His clinical informatics work includes predictive models for hospital readmissions, laboratory quality assurance, and clinical decision support.
A foundation in computing and spatial data.
Earlier, his group developed the pioneering Virtual Microscope system for viewing whole-slide tissue images. His technical contributions include the Active Data Repository and DataCutter, systems for processing very large datasets across parallel and distributed computers.
He and his coauthors received the 2024 VLDB Test of Time Award for Hadoop-GIS, a system for large-scale spatial data analysis. He directed the High Performance Systems Software Laboratory at the University of Maryland, held computer science faculty appointments at Maryland and Yale, and served as lead computer scientist at NASA Langley.
As Malachite’s CTO, Joel leads technology development, bringing this experience in AI, computing, and data infrastructure to population and government planning.
CTO · Co-founder
Joel Saltz
MD, PhD
A pioneering computer scientist, physician, and informatician whose work connects AI, large-scale computing, and the practical use of complex data.
Joel earned his MD and a PhD in computer science at Duke University, followed by postgraduate training in clinical pathology at Johns Hopkins. He is board-certified in clinical pathology and clinical informatics.
A founding leader in biomedical informatics, he established and chaired departments at Ohio State, Emory, and Stony Brook. He is a Fellow of the American College of Medical Informatics.
Turning complex data into understanding.
His research turns pathology images into quantitative data, combining computer vision, machine learning, and large-scale computing to study tissue structure, cancer biology, and clinical outcomes. His group developed methods to map tumor-infiltrating lymphocytes across 13 cancer types.
He also played a foundational leadership role in the National COVID Cohort Collaborative (N3C), helping shape its architecture and leading a group that contributed tools for data curation, quality control, and analysis. His clinical informatics work includes predictive models for hospital readmissions, laboratory quality assurance, and clinical decision support.
A foundation in computing and spatial data.
Earlier, his group developed the pioneering Virtual Microscope system for viewing whole-slide tissue images. His technical contributions include the Active Data Repository and DataCutter, systems for processing very large datasets across parallel and distributed computers.
He and his coauthors received the 2024 VLDB Test of Time Award for Hadoop-GIS, a system for large-scale spatial data analysis. He directed the High Performance Systems Software Laboratory at the University of Maryland, held computer science faculty appointments at Maryland and Yale, and served as lead computer scientist at NASA Langley.
As ’s CTO, Joel leads technology development, bringing this experience in AI, computing, and data infrastructure to population health and government planning.