BIOMEDICAL INFORMATICS AND CLINICAL AI · EXPERT ADVISOR
Connecting human disease research, clinical data, and responsible AI.
I’m a biomedical informaticist, clinical AI data scientist, and AI researcher. My work brings scientific inquiry and health data systems together to advance research and patient care.
01 / About
From molecular mechanisms to the systems that make health data useful.
My work sits at the intersection of biomedical research, clinical data science, and multimodal clinical AI research
I study and work with data across pediatric and adult disease, including epilepsy, cancer, diabetes, and sickle cell disease. The question running through that work is how better use of biological and clinical information can improve our understanding of disease and support better decisions.
Through Precoh, I advise healthcare organizations, academic laboratories, and government health authorities on data platforms, interoperability, governance, and AI evaluation. My current research interests include multimodal foundation models for clinical and biomedical reasoning.
Dr. Michael W. Craige is a biomedical informaticist, clinical AI data scientist, AI researcher, and founder of Precoh. He works across human disease research, clinical data infrastructure, digital health strategy, and the responsible evaluation of AI.
He previously served as Deputy Director for Medical Informatics and Data Science at the American Society of Hematology Research Collaborative, leading work across clinical data architecture, analytics, governance, and interoperability. The organization’s 2025 Sickle Cell Disease Data Hub Report acknowledges his programmatic and statistical support.
At the Public Health Informatics Institute, a program of The Task Force for Global Health, he supported CDC-funded projects focused on surveillance modernization and electronic case reporting. His work included collaboration across public health agencies, healthcare providers, and health information technology organizations.
His doctoral dissertation at Rutgers investigated gene expression and pathway enrichment after status epilepticus. Subsequent postdoctoral research focused on computational approaches to cancer progression and therapeutic response. He received the 2021 NSF-supported Computing Innovation Fellowship and has coauthored research in Nature Communications, Scientific Reports, and Frontiers in Oncology.
From 2012 to 2020, he founded and managed CiDrep Informatics, serving clients in the United States and Canada. Earlier roles included technical consulting at Cerner Corporation, now Oracle Health, management at Accenture, and consulting engagements at IBM.
He is also the founding director of CiDrep SickKids Foundation, which supports families facing costs associated with serious childhood illness and advances equitable pediatric health research.
02 / Research & practice
My research and advisory work spans disease mechanisms, health data infrastructure, and the evaluation of clinical AI.
Government health advisory
Advisory support through Precoh for a government-led healthcare sandbox, covering health-data readiness, interoperability, experiment design, and governance for clinical AI evaluation. Work included translating clinical, technical, and policy requirements into feasible experiments and measurable evaluation plans.
Data readiness · Interoperability · Experiment design · GovernanceDisease research
Computational approaches to understanding disease biology across pediatric epilepsy, cancer, diabetes, and sickle cell disease, with attention to clinical outcomes and precision medicine.
Genomic data · Pathway analysis · Clinical outcomesCurrent research focus
A research focus on foundation models that bring together clinical and biomedical information, and on how to evaluate their reasoning, reliability, and suitability for real clinical settings.
Multimodal foundation models · Evaluation · TranslationHealth data systems
Clinical data platforms, multi-EHR infrastructure, interoperability, and real-world evidence. Experience includes hematology data networks and electronic case reporting for public health.
HL7 & FHIR · Real-world evidence · Data governanceResponsible implementation
Helping organizations assess readiness, define evidence requirements, and evaluate AI and digital health technologies within the clinical, technical, and regulatory context in which they will operate.
Readiness · Evidence · Regulatory context03 / Selected work
Selected coauthored papers, a research report contribution, a conference abstract, and policy commentary.
6 selected works
Policy commentary The Regulatory Review
An examination of transparency, institutional oversight, and accountability in clinical AI.
Michael W. Craige · Published 6 August 2026Research paper Scientific Reports
Computational analysis of alternative splicing and disease progression in colorectal cancer.
Coauthor · DOI 10.1038/s41598-026-35903-wResearch report contribution ASH Research Collaborative
Real-world insights into sickle cell disease burden, treatment patterns, and outcomes across contributing clinical sites.
Acknowledged for programmatic and statistical support · PDFResearch paper Nature Communications
Mechanism-based investigation of therapeutic resistance in castration-resistant prostate cancer.
Coauthor · DOI 10.1038/s41467-024-44686-5Conference abstract ASH Annual Meeting · Blood
A collaborative approach to generating real-world evidence for multiple myeloma research.
Coauthor · Blood 144 (Supplement 1): 3792.5 · DOI 10.1182/blood-2024-210957Research paper Frontiers in Oncology
Research linking tissue-specific biological aging signals with cancer progression.
Coauthor · DOI 10.3389/fonc.2023.122216804 / Research support
NSF-supported fellowship research in computational biology and precision oncology.
2021 / Fellowship award
In 2021, I was awarded a Computing Innovation Fellowship through the Computing Research Association (CRA) and the Computing Community Consortium (CCC), with support from the National Science Foundation (NSF).
Approximate research funding
$380,185 over 3 years
Research title
Research description
The project aimed to develop new computational biology algorithms to uncover transcriptional mechanisms of resistance to anti-androgen treatment in castration-resistant prostate cancer (CRPC), and identify drugs and drug combinations that inhibit those mechanisms.
05 / Leadership & service
Scientific work and organizational leadership share the same purpose: making better health possible.
Advisory work at the intersection of clinical data science, digital health strategy, AI governance, and health data infrastructure. Supporting healthcare, research, and government teams as they evaluate and implement responsible innovation.
Explore PrecohSupporting families of sick children when insurance and other financial resources are exhausted, while advancing equitable pediatric health research.
Visit the foundationExperience
Advisory work through Precoh supporting a government-led healthcare sandbox on data readiness, interoperability, experiment design, and clinical AI evaluation governance.
Former Deputy Director for Medical Informatics and Data Science, with leadership across clinical data architecture, analytics, governance, and interoperability.
Work on CDC-funded surveillance and electronic case reporting initiatives through The Task Force for Global Health.
Doctoral research on gene expression and pathway enrichment in epilepsy, followed by postdoctoral computational cancer research at Rutgers.
Laboratory research in the Department of Neurology focused on pediatric epilepsy.
Founder of CiDrep Informatics from 2012 to 2020, building on earlier consulting and management experience across healthcare, technology, and life sciences.
Education & research training
Biomedical and Health Informatics
Rutgers, The State University of New Jersey
Master in Health Services (MHS)
Keller Graduate School of Management
Master of Business Administration
Georgia Institute of Technology
Computational biology · Genome science · Biomedical sciences
Rutgers, The State University of New Jersey · Icahn School of Medicine at Mount Sinai · Emory · Columbia University
06 / Fellowships & training
Completed fellowships and professional training in early-stage investment, patent drafting and prosecution, and research commercialization.
Venture capital training
Trained in early-stage advanced technology investment, with experience sourcing and funding capital for multinational and community-based institutions. Worked alongside the IndieBio New York team to identify and support early-stage life sciences companies focused on transforming human and planetary health.
IndieBio New York is now SOSV NY.
Patent law training
Completed training in patent application drafting and prosecution.
Life sciences patent training
Completed life sciences patent training covering patent fundamentals, drafting, and prosecution.
Technology transfer fellowship
Rutgers Innovation Ventures
Awarded the Rutgers Innovation Ventures Technology Transfer Fellowship, with training in intellectual property protection and research commercialization.
07 / Industry credentials
Continuous learning strengthens the expertise I bring to research and practice.
My industry training and certifications complement my academic preparation, published research, and experience across biomedical informatics, clinical data science, and responsible AI. I use continued professional development to keep my technical knowledge current and inform how I evaluate emerging technologies, design health data systems, and advise research and healthcare teams.
My digital credentials and badges are shared through Credly, providing a record of this professional development.
View my credentials on Credly08 / Connect
For research collaboration, scientific advisory work, or a conversation about responsible AI and health data.