Kayvan Najarian, PhD
Professor of Computational Medicine and Bioinformatics
Professor of Emergency Medicine
Medical School and Professor of Electrical Engineering and Computer Science
College of Engineering
[email protected]

Available to mentor
Kayvan Najarian, PhD
Professor
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    About

    Dr. Kayvan Najarian is a Professor in the Gilbert S. Omenn Department of Computational Medicine and Bioinformatics (DCMB) as well as the departments of Emergency Medicine and Electrical Engineering and Computer Science at the University of Michigan. He is the Director of the Biomedical and Clinical Informatics Laboratory (BCIL), an Associate Director for the Weil Institute for Critical Care Research and Innovation, and an Associate Director for the Michigan Institute for Data and AI in Society (MIDAS), serving as the point person for data science collaboration in Biological Sciences and Health Sciences. Dr. Najarian is also the director of a national NSF Industry-University Cooperative Research Center (IUCRC) for Data-Driven Drug Development and Treatment Assessment (DATA) which aims to facilitate industry-wide collaborations on artificial intelligence (AI) methodologies for drug development.

    Dr. Najarian received his Ph.D. in Electrical and Computer Engineering from University of British Columbia, Canada, M.Sc in Biomedical Engineering from Amirkabir University, Iran, and B.Sc. in Electrical Engineering from Sharif University, Iran.

    Dr. Najarian’s research has been continually funded by agencies such as the National Science Foundation, the National Institutes of Health, the Department of Defense, and private companies. Overall, his research has resulted in more than 350 peer reviewed publications and over 40 patents in this field, some of which have been commercialized through industry partners including start-ups and large corporations. He has also written two textbooks in biomedical informatics that are being used at many universities and research institutes.

    Links
    • Najarian Lab
    Center Memberships
    • Center Member
      Institute for Healthcare Policy and Innovation
    • Center Member
      Caswell Diabetes Institute
    • Center Member
      e-Health and Artificial Intelligence Initiative
    Research Overview

    Dr. Najarian's reserach focuses on the design of computational systems using advanced signal/image processing and artificial intelligence for clinical applications, including computer-aided decision support systems and drug design, with the goal of improving patient care and reducing the cost of healthcare. In particular, he focuses on creating decision support systems to manage traumatic brain injuries, respiratory illnesses, cardiac arrest, gastrointestinal diseases, and other critical care states.

    Recent Publications See All Publications
    • Journal Article
      Identification of digital twins to guide interpretable AI for diagnosis and prognosis in heart failure
      Gu F, Meyer AJ, Ježek F, Zhang S, Catalan T, Miller A, Schenk NA, Sturgess VE, Uceda D, Li R, Wittrup E, Hua X, Carlson BE, Tang YD, Raza F, Najarian K, Hummel SL, Beard DA. Npj Digital Medicine, 2025 Dec 1; 8 (1): DOI:10.1038/s41746-025-01501-9
    • Journal Article
      AXpert: human expert facilitated privacy-preserving large language models for abdominal X-ray report labeling
      Zhang Y, Kohne JG, Webster K, Vartanian R, Wittrup E, Najarian K. JAMIA Open, 2025 Feb 1; 8 (1): DOI:10.1093/jamiaopen/ooaf008
    • Journal Article
      EvolveFNN: An interpretable framework for early detection using longitudinal electronic health record data
      Zhang Y, Wittrup E, Hodgman M, Mathis M, Najarian K. IEEE Journal of Biomedical and Health Informatics, 2025 Jan 1; DOI:10.1109/JBHI.2025.3551312
    • Chapter
      Predicting Efficacy of Cancer Drug Combinations Using Machine Learning
      Liu W, Rajaei F, Najarian K. Communications in Computer and Information Science, 2025 Jan 1; 2259 CCIS: 425 - 431. DOI:10.1007/978-3-031-85908-3_34
    • Journal Article
      Enhancing heart failure treatment decisions: interpretable machine learning models for advanced therapy eligibility prediction using EHR data
      Zhang Y, Golbus JR, Wittrup E, Aaronson KD, Najarian K. BMC Medical Informatics and Decision Making, 2024 Dec 1; 24 (1): DOI:10.1186/s12911-024-02453-y
      PMID: 38355512
    • Journal Article
      Identifying selective PDHK inhibitors using coupled tensor matrix completion and experimental validation
      Rajaei F, Toogood P, Jacob R, Baber M, Gough M, Derksen H, Wittrup E, Najarian K. Discover Artificial Intelligence, 2024 Dec 1; 4 (1): DOI:10.1007/s44163-024-00202-8
    • Preprint
      Identification of Digital Twins to Guide Interpretable AI for Diagnosis and Prognosis in Heart Failure
      Gu F, Meyer AJ, Ježek F, Zhang S, Catalan T, Miller A, Schenk N, Sturgess V, Uceda D, Li R, Wittrup E, Hua X, Carlson BE, Tang Y-D, Raza F, Najarian K, Hummel SL, Beard DA. 2024 Nov 13; medRxiv, DOI:10.1101/2024.11.11.24317106
    • Proceeding / Abstract / Poster
      Toward Closed Loop Control of Fluid Management after Congenital Heart Surgery: Obtaining Transparent Therapeutic Optima (OTTO) of Furosemide using a Tropical Geometry-Based Fuzzy Neural Network
      Ehrmann DE, Hodgman M, Wittrup E, Charpie J, Owens G, Aiyagari R, Najarian K. 2024 Nov 14;
    Featured News & Stories DATA Center 2025 spring meeting - Dr Najarian
    Department News
    DATA for drug discovery and treatment assessment: DATA Center 2025 Spring Meeting
    On April 10, 2025, the Center for Data-Driven Drug Development and Treatment Assessment (DATA), an NSF Industry-University Cooperative Research Center (IUCRC), held its third Spring meeting, in Ann Arbor, MI. Hosted at the University of Michigan (U-M), DATA creates and fosters scientific partnerships between industry, government, and academia, focusing on drug discovery that is based on data and tools such as modeling, AI and machine learning.
         Yufeng Zhang, PhD
    Department News
    Yufeng Zhang, PhD, defended her bioinformatics dissertation thesis on machine learning models
    Zhang's research focuses on developing data-driven identification and prediction systems for real-world medical applications. I am particularly interested in enhancing the generalization and interpretability of machine learning and deep learning models in medicine, as well as exploring innovative methods to improve model accuracy. To address challenges such as the lack of annotated data, limited generalization capabilities, and the need for interpretable models, I have applied several strategies, including privileged information learning, self-supervised learning, and approximate reasoning.
         World map using maize stars to indicate France, China and Korea
    Department News
    Meet DCMB's international visiting students, Summer 2024
    This summer and into the fall, DCMB is hosting three international students for up to six months each. They come from China, France and Korea, eager to learn and expand their education and experience through an extended visit at the University of Michigan (U-M) and DCMB.
    Department News
    DATA research call for proposals
    DATA research call for proposals in the DCMB at the U-M Medical School.
    Department News
    Kayvan Najarian received a Fulbright Specialist award
    Kayvan Najarian in the department of computational medicine and bioinformatics at the University of Michigan received a Fulbright Specialist award.
    Department News
    Clinical research and data science come together to improve diagnostic capabilities
    Clinical research and data science come together to improve diagnostic capabilities