William J. Bosl

Associate Professor; Director, MSHI Program

Program Director • Full-Time Faculty

(415) 422-4638 Cowell Hall 202


Dr. William (Bill) Bosl is currently an associate professor of Health Informatics and Clinical Psychology at the University of San Francisco, where he is also the current and founding director of the master’s degree program in Health Informatics. His primary research focus is in clinical neurophysiology and neurodiagnostics.

Projects to discover patterns in infant EEG signals that can serve as biomarkers for autism and other neurodevelopmental pathology continue with collaborations at Boston Children’s Hospital (BCH) in Developmental Medicine. A proposal to move this work to the bedside is a finalist for a BCH Innovation & Digital Health Accelerator award. Bill is working with neurologists in the BCH Epilepsy clinic to find measures of ‘epileptigenicity’ or tendency to have epileptic seizures.

Together with Professor Andy Nguyen at USF, Dr. Bosl is working on a crowd-sourcing approach to annotation of clinical EEGs for research for the American Society of Electrodiagnostic Technologists. Other projects involve neurodevelopment in premature infants (with Rutgers medical school) and emergence of neurological impairment in Kenyan children following cerebral malaria (with Oxford University). An early-stage effort to detect mTBI following concussive head injuries via EEG analysis is starting to collect data. Clinical applications for all of this work will require integration of EEG-derived information with other patient data in Electronic Health Records, and presentation to clinicians, topics that are being developed with the Computational Health Informatics Program at Boston Children’s Hospital. Professor Bosl has recently been appointed Visiting Associate Professor of Pediatrics at Harvard Medical School.

In May 2018, Dr. Bosl, together with his colleagues at Harvard Medical School and Boston Children's Hospital released a study in the Scientific journal that predicts occurrences of ASD (Autism Spectrum Disorder) with greater than 95% accuracy. These findings pave way for critical early intervention and treatment.
Director, MSHI Program
PhD, Behavioral Neuroscience, Boston University School of Medicine
PhD, Geophysics, Stanford University
MA, Mathematics, University of Pittsburgh
MS, Atmospheric Physics, University of Michigan
BS, Chemistry, Miami University
Early detection of neurodevelopmental disorders using nonlinear EEG analysis.
Integrating behavioral informatics into primary care for mental health screening.
Informatics for global health, especially mental and neurological impairment.
Cognitive phenotypes, consciousness and electrophysiology.
Nonlinear signal analysis and machine learning in healthcare systems.

Bosl, William J. and Tager-Flusberg, Helen and Nelson, Charles A. "EEG Analytics for Early detection of Autism Spectrum Disorder: A data-driven approach" (2018). Scientific Reports. URL: https://doi.org/10.1038/s41598-018-24318-x 

Chavakula, V., S. Fernandez, J. Peters, G. Popil, Bosl, W. J., S. Rakhade, A. Rotenberg, T. Loddenkemper. (2013). Automated quantification of spikes. Epilepsy and Behavior, 26(2).

Bosl, W. J., Mandel, J., Jonikas, M., Ramoni, R.B., Kohane, I.S., and Mandl, K.D. (2013). Scalable decision support at the point of care: A substitutable electronic health record app for monitoring medication adherence. Intert J of Med Res 2(2): e13.

Bosl, W. J. (2012). Neurotechnology and psychiatric biomarkers, in Ghista, D. (Ed.), Biomedical Engineering - Book 3; InTech Publishers.

Bosl, W. J.,Tager-Flusberg, H., Tierney, A., Nelson, C.A. (2011). EEG complexity as a biomarker for autism spectrum disorder risk. BMC Medicine, 9(18).

Kriete, A., Bosl, W. J., and Booker, G. (2010). Rule-based cell systems model of aging using feedback loop motifs mediated by stress responses. PLoS Comput Biol 6, e1000820.

Bosl, W. (2007). Systems biology by the rules: Hybrid intelligent systems for pathway discovery and analysis. BMC Systems Biology, 1(13).

 Bosl, W. & Li, R. (2005). Mitotic exit control as an evolved complex system. Cell, 121. 325-333.

Professional Affiliations

American Medical Informatics Association

IEEE, Computational Intelligence SIG

International Neuropsychological Society

American Psychological Society