Ali R. Walsh, Ph.D., MFA, MPH

Research Fellow
Department of Systems, Populations and Leadership
Room 3351 400NIB

University of Michigan School of Nursing
400 North Ingalls Building
Ann Arbor, MI 48109-5482


  • Social network analysis
  • Behavioral interventions
  • Adolescent health

Dr. Walsh’s research interests center around social network analysis, specifically, how individual and structural social features can encourage or inhibit behavior change. She is particularly interested in the application of network theory to enhance behavioral intervention adherence and effectiveness.


As a doctoral student at the University of Michigan School of Public Health, Dr. Walsh worked as a graduate student instructor for multiple graduate and undergraduate epidemiology and public health courses. She currently co-coaches the ‘Disease Detectives’ event for a local middle school Science Olympiad team.

Affiliations / Service

  • Sponsorship Chair, Colorectal Cancer Alliance Detroit Undy Engagement Committee, 2019-present
  • Co-coach, Slauson Middle School Science Olympiad (Disease Detectives), 2018-present
  • Member, Society for Epidemiologic Research, 2012-present

Notable Awards / Honors

  • One Term Dissertation Fellowship, University of Michigan Rackham Graduate School, 2017
  • Doctoral Program Day Best Poster/Presentation Award, University of Michigan School of Public Health Department of Epidemiology, 2015


  • Ph.D., University of Michigan, Ann Arbor, MI, 2019
  • MPH, University of Michigan, Ann Arbor, MI, 2013
  • MFA, Brooklyn College, Brooklyn, NY, 2007
  • BA, Grinnell College, Grinnell, IA, 2001

Publication Highlights

  • Aiello, A.E., Simanek, A.M., Eisenberg, M.C., Walsh, A.R., Davis, B., et al. (2016). Design and methods of a social network isolation study for reducing respiratory infection transmission: the eX-FLU cluster randomized trial. Epidemics. 15:38–55. doi: 10.1016/j.epidem.2016.01.001.

  • Fan, K., Eisenberg, M., Walsh, A., Aiello, A., and Heller, K. (2015). Hierarchical graph-coupled HMMs for heterogeneous personalized health data. Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 239–248. ACM. doi: 10.1145/2783258.2783326.