Principal Investigator Mauricio Santillana, Ph.D. Professor of Physics and Electrical and Computer Engineering Network Science Institute, Northeastern University |
The Machine Intelligence Group for the betterment of Health and the Environment (MIGHTE), now based at the Network Science Institute, at Northeastern University and the Center for Communicable Disease Dynamics at the Harvard T.H. Chan School of Public Health (from 2017 to 2022, our research lab, the Machine Intelligence Lab, was based at Boston Children’s Hospital) has a multidisciplinary research agenda. Our research involves the conception and implementation of machine intelligence analytics tools, capable of predicting unobserved events in epidemiology and healthcare in the immediate or near future. Our work ranges from tracking disease outbreaks around the Globe, leveraging information from big data sets from Internet-based services (such as Google search activity, Twitter microblogs, Weather, Human Mobility, Electronic Health Records), to bed-side patient-centered monitoring approaches aimed at improving care in clinical settings. We also focus on the use of mathematical approaches to discover relationships between relevant outcomes in the health, physical and environmental sciences. For example we have studied the influence of climate change on the prevalence of antibiotic resistant infections, or the role of socio-economic factors and political leaning and mortality during the COVID-19 pandemic.
Generally speaking, our approaches use machine learning techniques to identify patterns that have occurred historically that may be predictive of specific and future events of interest, for example:
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Latest news
2/2025
Prof Santillana is among the top 2% of the most-cited scientists with a single-year impact in various disciplines, top scientists worldwide selected by Stanford University. 2/2025
Prof. Santillana gave a seminar on February 24th during the CSTE/CDC VBD Forecasting Call, focusing on the topic ‘Ensemble forecasting approaches to anticipate Dengue outbreaks, aiming to support resource allocation for clinical trials: A case study in over 180 locations worldwide.’ 2/2025
Mauricio Santillana and Raul Garrido participated in the 2025 Mathematical Modeling and Public Health Workshop on March 4th , presenting the lecture 'Machine Learning & Novel Data Sources.' This event is organized by the CCDD at the Harvard T.H. Chan School of Public Health. 12/2024 Prof. Santillana presented the ongoing performance of an Early Warning System to anticipate sharp increases of Influenza-like Illnesses in the US to the InsightNet community (a network of professionals that work closely with the Centers for Disease Control and Prevention on National Outbreak Analytics ) on December 4th. |