CUSP Research Seminar – Data-driven machine learning approaches to monitor and forecast the dynamics of disease outbreaks
Please join NYU's Center for Urban Science and Progress (CUSP) for our Research Seminar Series, featuring leading voices in the growing field of Urban Informatics.
Our next virtual seminar will feature Mauricio Santillana, director of the Machine Intelligence Research Lab in the Computational Health Informatics Program at Boston Children’s Hospital, for a discussion on “Data-driven machine learning approaches to monitor and forecast the dynamics of disease outbreaks.”
Data-driven machine learning approaches to monitor and forecast the dynamics of disease outbreaks
I will describe data-driven machine learning methodologies that leverage Internet-based information from search engines, Twitter microblogs, crowd-sourced disease surveillance systems, electronic medical records, and weather information to successfully monitor and forecast disease outbreaks in multiple locations around the globe in near real-time. I will present how these approaches can be used to build early warning systems to anticipate COVID-19 outbreaks.
Mauricio Santillana, Ph.D., is the director of the Machine Intelligence Research Lab in the Computational Health Informatics Program at Boston Children’s Hospital. He is an Assistant Professor at both the Department of Pediatrics, Harvard Medical School, and the Department of Epidemiology, T.H. Chan Harvard 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 work 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 (member of the NIH), the U.S. Centers for Disease Control and Prevention, the Bill and Melinda Gates Foundation, and multiple foundations such as: the Johnson and Johnson Global Citizen Fund, 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 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 Wall Street Journal, Vox.com, Politico, National Public Radio, CNN, BBC, among others.