Ben Reis, PhD
Director, Predictive Medicine Group
Faculty, Children's Hospital Informatics Program at
the Harvard-MIT Division of Health Sciences and Technology
|Academic Title||Assistant Professor|
Boston Children's Hospital
300 Longwood Avenue
Boston MA 02115
Dr. Ben Reis is Director of the Predictive Medicine Group at Harvard Medical School and the Children’s Hospital Informatics Program. His research focuses on understanding the essential patterns of human disease, and on developing novel approaches for predicting disease. He has created systems that allow doctors to predict dangerous clinical conditions years in advance, as well as predictive pharmacology systems that allow public health officials to identify life-threatening adverse drug effects years in advance. Dr. Reis has designed predictive health monitoring systems for regional and national settings, and has advised governments worldwide on establishing biodefense and biosurveillance infrastructures. He has been recognized by the White House for his work on harnessing social networks to promote health, and by the US State Department, USAID and NASA for his work in global health innovation.
Dr. Reis’s main research areas include:
- Intelligent Histories: Developing advanced predictive methods that allow doctors to identify important clinical risks, from diabetes to domestic abuse, years in advance.
- Predictive Pharmacology: Developing predictive network-based approaches to pharmacovigilance, capable of identifying dangerous drug side effects and interactions years in advance.
- Social Networks and Health: The HealthySocial project explores how emerging social networks can be used to promote and spread positive health behaviors, such as blood donation and influenza vaccination. HealthySocial apps have been used by tens of thousands of people worldwide.
- Public Health Surveillance: Designing adaptive public health monitoring systems that allow public health officials to maintain situational awareness during times of increased risk and uncertainty, including pandemics and major public events.
- Computational Linguistics: The SpeechWars project combines history, politics and language to study and visualize hundreds of years of history. SpeechWars was selected by the United States Library of Congress for inclusion in its official historic collections.
About Ben Reis, PhD
Dr. Reis received his Ph.D. from the University of Cambridge as a Marshall Scholar, where he researched the prediction of musical sequences and the cognitive processes underlying musical learning. He completed his postdoctoral training at Harvard Medical School as an NIH Fellow in Health Informatics, researching the dynamics of genetic expression networks. He is currently a faculty member at Harvard Medical School and Children’s Hospital Boston. Dr. Reis has advised the US government on establishing national biodefense systems in the wake of the 9/11 attacks, the Hong Kong government on building health infrastructure in response to the SARS pandemic, the Greek government on establishing biodefense systems for the 2004 Athens Summer Olympics, and the Chinese Government in advance of the 2008 Beijing Summer Olympics. His research has been reported on widely, including in Nature, The New York Times and The Wall Street Journal.
- Cami A, Arnold A, Manzi S, Reis B. Predicting adverse drug events using pharmacological network models. Science Trans Med. 2011 Dec 21;3(114).
- Reis BY, Kohane IS, Mandl KD. Longitudinal histories as predictors of future diagnoses of domestic abuse: modelling study. British Medical Journal. 2009 Sep 29;339:b3677
- Reis BY, Kohane IS, Mandl KD. An epidemiological network model for disease outbreak detection. PLoS Medicine. June 01, 2007 2007;4(6):e210.
- Reis B.Y., et al. AEGIS: A Robust and Scalable Real-time Public Health Surveillance System. J Am Med Inform Assoc. Sep 2007.
- Reis B.Y., Pagano M, Mandl K.D. Using temporal context to improve biosurveillance. Proceedings of the National Academies of Science U S A. 2003,100(4):1961-1965.
- Reis B.Y., Butte A.J., Kohane I.S. Extracting knowledge from dynamics in gene expression. Journal of Biomedical Informatics. 2001, Feb;34(1):15-27.