Mauricio Santillana

Professor, Physics
Professor, Electrical and Computer Engineering

Contact

m.santillana@northeastern.edu
1010 - 177 (177 Huntington Ave)
Boston, MA 02111

Social Media

Research Focus

Modeling of geographic patterns of population growth, modeling fluid flow to inform coastal floods simulations and atmospheric global pollution transport models, and design and implementation of disease outbreaks prediction platforms and mathematical solutions to healthcare

About

Mauricio Santillana, PhD, MSc is the director of the Machine Intelligence Research Lab in the Network Science Institute. He is a Professor in the Physics and Electrical and Computer Engineering Departments at Northeastern University. 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, the Bill and Melinda Gates Foundation, and multiple foundations such as: the Johnson and Johnson Foundation, Ending Pandemics Fund,

Education

PhD, Computational and Applied Mathematics, the University of Texas at Austin, ICES, 2008

Research Overview

Selected Research Projects

Machine Intelligence Group for the betterment of Health and the Environment
- – PI, Network Science Institute at Northeastern University

Selected Publications

Druckman J, Ognyanova K, Baum M, Lazer D, Perlis R, Volpe JD, Santillana M, Chwe H, Quintana A, Simonson M. The role of race, religion, and partisanship in misinformation about COVID-19. Group Processes & Intergroup Relations. 2021;24 (4) :638–657.
Perlis R, Santillana M, Ognyanova K, Green J, Druckman J, Lazer D, Baum M. Factors associated with self-reported symptoms of depression among adults with and without a previous COVID-19 diagnosis. JAMA Network Open. 2021;4 (6).
Castro LA, Generous N, Luo W, y Piontti AP, Martinez K, Gomes MFC, Osthus D, Fairchild G, Ziemann A, Vespignani A, et al. Using heterogeneous data to identify signatures of dengue outbreaks at fine spatio-temporal scales across Brazil. PLoS Neglected Tropical Diseases. 2021.Abstract
de Salazar P, Link N, Lamarca K, Santillana M. High coverage COVID-19 mRNA vaccination rapidly controls SARS-CoV-2 transmission in Long-Term Care Facilities. Nature Communications Medicine. 2021;1 (16).Abstract
Perlis RH, Ognyanova K, Santillana M, Baum MA, Lazer D, Druckman J, Volpe JD. Association of Acute Symptoms of COVID-19 and Symptoms of Depression in Adults. JAMA Network Open. 2021;4 (3) :e213223.Abstract
de Salazar PM, Lu F, Hay JA, Gomez-Barroso D, Fernandez-Navarro P, Martinez EV, Astray-Mochales J, Amillategui R, Garcia-Fulgueiras A, Chirlaque MD, et al. Near real-time surveillance of the SARS-CoV-2 epidemic with incomplete data. medRxiv. 2021.Abstract
Mena G, Martinez PP, Mahmud AS, Marquet PA, Buckee CO, Santillana M. Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile. Science. 2021 :eabg5298.Abstract
Kiang MV, Santillana M, Chen JT, Onnela J-P, Krieger N, Engø-Monsen K, Ekapirat N, Areechokchai D, Maude R, Buckee CO. Incorporating human mobility data improves forecasts of Dengue fever in Thailand. Scientific Reports. 2021;11 (923).Abstract
Kogan NE, Clemente L, Liautaud P, Kaashoek J, Link NB, Nguyen AT, Lu FS, Huybers P, Resch B, Havas C, et al. An Early Warning Approach to Monitor COVID-19 Activity with Multiple Digital Traces in Near Real-Time. Science Advances. 2021;7 (10).Abstract
Poirier C, Hswen Y, Bouzille G, Cuggia M, Lavenu A, Brownstein JS, Brewer T, Santillana M. Influenza forecasting for the French regions by using EHR, web and climatic data sources with an ensemble approach. PLoS One. 2021.Abstract
Lu FS, Nguyen AT, Link N, Molina M, Davis JT, Chinazzi M, Xiong X, Vespignani A, Lipsitch M, Santillana M. Estimating the cumulative incidence of COVID-19 in the United States using influenza surveillance, virologic testing, and mortality data: four complementary approaches. PLoS Computational Biology . 2021.Abstract
Aiken EL, Nguyen AT, Viboud C, Santillana M. Towards the Use of Neural Networks for Influenza Prediction at Multiple Spatial Resolutions. Science Advances. 2021;7 (25).Abstract
McGough S, Kutz NJ, Clemente LC, Santillana M. A dynamic, ensemble learning approach to forecast dengue fever epidemic years in Brazil using weather and population susceptibility cycles. Journal of the Royal Society Interface. 2021;18 (179).Abstract

Faculty

Dec 07, 2023

2023 Stanford University Annual Assessment of Author Citations

The following COE professors are among the top scientists worldwide selected by Stanford University representing the top 2% of the most-cited scientists with single-year impact in various disciplines. The selection is based on the top 100,000 by c-score (with and without self-citations) or a percentile rank of 2% or above. The list below includes those […]