Team |
Lab Director
Biography
Mauricio Santillana, PhD, MSc is the director of the Machine Intelligence Group for the betterment of Health and the Environment (MIGHTE) at the Network Science Institute at Northeastern University. He is a Professor at both the Physics and Electrical and Computer Engineering Departments at Northeastern University, and an Adjunct Professor at the Department of Epidemiology, at the Harvard T.H. Chan School of Public Health. Dr. Santillana’s research areas include the modeling of geographic patterns of population growth, modeling fluid flow to inform coastal floods simulations and atmospheric global pollution transport models, and most recently, the design and implementation of disease outbreaks prediction platforms and mathematical solutions to healthcare. His research has shown that machine learning techniques can be used to effectively monitor and predict the dynamics of disease outbreaks using novel data sources not designed for these purposes such as: Internet search activity, social media posts, clinician’s searches, human mobility, weather, etc. His original research and perspectives have appeared in journals such as Nature, Science, Proceedings of the National Academy of Science, Science Advances, Nature Communications, and Nature Climate Change, among others. His work has been funded by the National Institute of General Medical Sciences (National Institutes of Health, NIH), the U.S. Centers for Disease Control and Prevention, and multiple foundations such as: the Bill and Melinda Gates Foundation, the Johnson and Johnson Foundation, Ending Pandemics Fund, Skoll Global Threats Fund. Dr. Santillana has advised the US CDC, Africa CDC, and the White House on the development of population-wide disease forecasting tools. His original research and perspectives have been featured in a diverse array of national and international news outlets such as The New York Times, The Washington Post, The Atlantic, The Wall Street Journal, Vox.com, Politico, National Public Radio, CNN, CNN Espanol, Fox, BBC, among others. Mauricio received a B.S. in Physics with highest honors from Universidad Nacional Autónoma de México in Mexico City, and a Master’s and PhD in Computational and Applied Mathematics from the University of Texas at Austin. Mauricio was a Postdoctoral fellow at the Harvard Center for the Environment and later became a lecturer in applied mathematics at the Harvard School of Engineering and Applied Sciences, receiving two awards for excellence in teaching. He became a tenure-track faculty member at Boston Children's Hospital, Harvard Medical School, and the Harvard T.H. Chan School of Public Health. He recently joined the faculty at Northeastern University. Works on: Using social media, Internet searches, and electronic health records to predict incidence of influenza, dengue fever, malaria, COVID-19, antibiotic resistance, in multiple locations worldwide. Using electronic health records to predict outcomes in pediatric intensive care units. Developing approaches to improve resource allocation in Hospitals. Characterizing epidemic outbreaks in real-time. Pandemic Preparedness. Numerical Solutions of Partial Differential Equations. Scientific Computing. |
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Team Members
Biography
Leonardo Clemente is a Research Scientist and Data Infrastructure Manager at MIGHTE Works on: Using social media, Internet searches, and electronic health records to predict incidence of influenza, dengue fever, malaria, COVID-19, antibiotic resistance, in multiple locations worldwide. Using electronic health records to predict outcomes in pediatric intensive care units. Developing approaches to improve resource allocation in Hospitals. Characterizing epidemic outbreaks in real-time. Pandemic Preparedness. Numerical Solutions of Partial Differential Equations. Scientific Computing.
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Biography
Nicole Kogan is a PhD Student at the Harvard T.H. Chan School of Public Health and a Research Scientist at MIGHTE. Works on: Using social media, Internet searches, and electronic health records to predict incidence of influenza, dengue fever, malaria, COVID-19, antibiotic resistance, in multiple locations worldwide. Using electronic health records to predict outcomes in pediatric intensive care units. Developing approaches to improve resource allocation in Hospitals. Characterizing epidemic outbreaks in real-time. Pandemic Preparedness. Numerical Solutions of Partial Differential Equations. Scientific Computing.
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Affiliate Members
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Alumni
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David Castiñeira, PhD. Chemical Engineering, Postdoctoral Fellow, Massachusetts Institute of Technology
Team member: 2016 - 2017 Now: Principal Advisor for Emerging Technologies, Hess Corporation Gaston Fiore, M.S. Computer Science, Massachusetts Institute of Technology Team member: 2016 - 2017 Now: Entrepreneur Kaycie Schlosser, Medical Doctor, Chief Fellow, Boston Children's Hospital Team member: 2016 - 2017 Now: Pediatric Intensivist, Columbia University Irving Medical Center Gal Wachtel, B.S. Molecular & Cellular Biology, Harvard University Team member: 2017 Now: Data Scientist, Palantir Sam Tideman, M.S. Epidemiology, Harvard School of Public Health Team member: 2017 Now: Data Scientist, Northshore University Healthsystem Nick Generous, M.S. Epidemiology, Harvard School of Public Health Team member: 2017 Now: Scientist, Los Alamos National Laboratory Suqin Hou, M.S. Biostatistics, Harvard School of Public Health Team member: 2016 Now: Data Scientist, KAYAK Andre Nguyen, B.S. Applied Math, Harvard University Team member: 2014 - 2016 Now: Director of Machine Learning, JURA Bio, Inc. |
