Ivo D. Dinov, PhD

Computational Medicine and Bioinformatics, Medical School
Associate Director for Education and Training, Michigan Institute for Data Science
Department of Health Behavior and Biological Sciences Vice Chair
Department of Health Behavior and Biological Sciences
Room 4126 SNB
University of Michigan School of Nursing
426 North Ingalls Street
Ann Arbor, MI 48109-2003
Telephone: (734) 764-5557
Fax: (734) 647-2416


  • Big Data
  • Biomedical data science
  • Health and neuroscience informatics
  • Teaching with technology and blended instruction
  • Mathematical modeling and statistical computing

Dr. Dinov is the Director of the Statistics Online Computational Resource (SOCR) and is an expert in mathematical modeling, statistical analysis, high-throughput computational processing and scientific visualization of large datasets (Big Data). His applied research is focused on neuroscience, nursing informatics, multimodal biomedical image analysis, and distributed genomics computing. Examples of specific brain research projects Dr. Dinov is involved in include longitudinal morphometric studies of development (e.g., Autism, Schizophrenia), maturation (e.g., depression, pain) and aging (e.g., Alzheimer’s disease, Parkinson’s disease). He also studies the intricate relations between genetic traits (e.g., SNPs), clinical phenotypes (e.g., disease, behavioral and psychological test) and subject demographics (e.g., race, gender, age) in variety of brain and heart related disorders. Dr. Dinov is developing, validating and disseminating novel technology-enhanced pedagogical approaches for science education and active learning.

Current Research Grants and Programs

  • NS091856 Biostatistics and Data Management Core, Cholinergic Mechanisms of Gait Dysfunction in Parkinson's Disease. This research examines the role of cholinergic lesions in gait and balance abnormalities in Parkinson's Disease and develops novel treatment strategies targeted at cholinergic neurotransmission.
  • DK089503 Integrative Biostatistics and Informatics Core. The Michigan Nutrition Obesity Research Center conducts research to encourage and enable researchers to integrate advanced phenotyping and computational tools to more fully define individual and population characteristics that arise in response to dietary nutrient composition or amount.
  • NR015331 Center for Complexity and Self-management of Chronic Disease investigates health promotion, illness prevention and the burden of chronic illness burgeons using advanced methods, complexity theory, and data analytics.
  • NSF DUE 1023115 The Distributome Project (http://distributome.org/) is an open-source, open content-development project for exploring, discovering, learning, and computational utilization of diverse probability distributions. Role: Site-Principal Investigator.
  • EB020406 Big Data for Discovery Center aims to create a user-focused graphical system to dynamically create, modify, manage and manipulate multiple collections of big datasets and enrich next generation "Big Data" workflow technologies as well as to develop an interface to enable modeling, visualization, and the interactive exploration of Big Data.


Dr. Dinov’s teaching philosophy has evolved and matured over the past two decades from a concept-based instruction to a more pedagogically balanced approach of integrated research, practice and education. He has taught many core and multidisciplinary classes in statistics, mathematics, neuroscience and psychology. Dr. Dinov is developing active learning materials, web-based computational resources, dynamic databases, blended learning materials and electronic instructional resources. The foci of his ongoing educational research are on increasing learners’ motivation, enhancing the learning experiences and improving knowledge retention. As Director of the Statistics Online Computational Resource (SOCR), Dr. Dinov designs, implements and validates novel virtual experiments, web apps for probability, statistics and informatics education, and introduces new multilingual science, technology, engineering and mathematics (STEM) resources.

Notable Awards / Honors

  • World Wide Web Awards™ "Gold" Award, July 2007
  • IEEE Mathematical Methods in Biomedical Image Analysis (MMBIA) Best Paper Award, 2008
  • Runner up, ASA Hands-On Statistics Activity Competition, 2010


  • Ph.D., The Florida State University, Tallahassee, FL, 1998
  • M.S., The Florida State University, Tallahassee, FL, 1998
  • M.S., Michigan Technological University, Houghton, MI, 1993
  • B.S., Sofia University, Sofia, Bulgaria, 1991

Publication Highlights

  • Dinov, ID. (2018) Data Science and Predictive Analytics: Biomedical and Health Applications using R, Springer, Computer Science, ISBN 978-3-319-72346-4.

  • Dinov, ID, Palanimalai, S, Khare, A, and Christou, N. (2018) Randomization‐based Statistical Inference: A resampling and simulation infrastructure, Teaching Statistics, 40: 64–73. DOI: 10.1111/test.12156.

  • Sepehrband, F., Lynch, K.M., Cabeen, R.P., González-Zacarías, C., Zhao, L., D’Arcy, M., Kesselman, C., Herting, M.M., Dinov, I.D., Toga, A.W., Clark, K.A. (2018) Neuroanatomical morphometric characterization of sex differences in youth using statistical learning, NeuroImage, 172:217–227, DOI: 10.1016/j.neuroimage.2018.01.065.

  • Kalinin, AA, Higgins, GA, Reamaroon, N, Soroushmehr, SM, Allyn-Feuer, A, Dinov, ID, Najarian, K, Athey, BD. (2018) Deep Learning in Pharmacogenomics: From Gene Regulation to Patient Stratification, arXiv:1801.08570.

  • Amiri, S and Dinov, ID. (2017). msktuple: An integrated R library for alignment-free multiple sequence k-tuple analysis. Chemometrics and Intelligent Laboratory Systems 168:84-88, DOI: 10.1016/j.chemolab.2017.07.012.

  • Huang Z, Zhang H, Boss J, Goutman SA, Mukherjee B, Dinov ID, Guan, Y. (2017) Complete hazard ranking to analyze right-censored data: An ALS survival study . PLoS Comput Biol 13(12): e1005887, DOI: 10.1371/journal.pcbi.1005887.

  • Stelmokas J, Yassay L, Giordani B, Dodge H, Dinov, ID, Bhaumik A, Sathian, K, Hampstead, BM. (2017) Translational MRI Volumetry with NeuroQuant: Effects of Version and Normative Data on Relationships with Memory Performance in Healthy Older Adults and Patients with Mild Cognitive Impairment. Journal of Alzheimer's disease 60(4):1499-1510, DOI: 10.3233/JAD-170306.

  • Kalinin AA, Allyn-Feuer A, Ade A, Fon G-V, Meixner W, Dilworth D, de Wet, JR, Higgins, GA, Zheng, G, Creekmore, A, Wiley, JW, Verdone, JE, Veltri, RW, Pienta, KJ, Coffey, DS, Athey, BD, Dinov, ID. (2017) 3D cell nuclear morphology: microscopy imaging dataset and voxel-based morphometry classification results. bioRxiv 168:84-88, DOI: 10.1101/208207.

  • Kalinin, AA, Palanimalai, S, Dinov, ID. (2017). SOCRAT Platform Design: A Web Architecture for Interactive Visual Analytics Applications. Proceedings of HILDA’17, Chicago, IL, USA, May 14, 2017, 6 pages. DOI: 10.1145/3077257. 3077262.

  • Dinov, ID. (2016) Methodological challenges and analytics opportunities for modeling and interpreting Big Healthcare Data. GigaScience, 5(12) 1-15, DOI:10.1186/s13742-016-0117-6

  • Dinov, ID. (2016) Volume and Value of Big Healthcare Data. Journal of Medical Statistics and Informatics, 4(3)1-7 DOI: 10.7243/2053-7662-4-3

  • Lederman, C, Joshi, A, Dinov, ID, Van Horn, JD, Vese, L, Toga, A. (2016) A Unified Variational Volume Registration Method Based on Automatically Learned Brain Structures. Journal of Mathematical Imaging and Vision, 55(2)179-198.

  • Husain, SS, Kalinin, A, Truong, A, Dinov, ID. (2015) SOCR data dashboard: an integrated big data archive mashing medicare, labor, census and econometric information. Journal of Big Data, 2(13):1-18. DOI: 10.1186/s40537-015-0018-z

  • Moon, S, Dinov, ID, Kim, J, Zamanyan, A, Hobel, S, Thompson, PM, Toga, AW. (2015) Structural Neuroimaging Genetics Interactions in Alzheimer's Disease. Journal of Alzheimer's Disease, 48(4) 1051-63. DOI:10.3233/JAD-150335 PMID: 26444770

  • Dinov, ID, Siegrist, K, Pearl, DK, Kalinin, A, Christou, N (2015). Probability Distributome: a web computational infrastructure for exploring the properties, interrelations, and applications of probability distributions. Computational Statistics, 594: 1-19. DOI: 10.1007/s00180-015-0594-6

  • Complete List of Publications: http://www.socr.umich.edu/people/dinov/publications.html