معرفی
George Dewey is a Postdoctoral Researcher at Northeastern University's Network Science Institute, where he contributes to the MIGHTE group (The Machine Intelligence Group for the betterment of Health and the Environment). His work integrates network science and epidemiology to advance outbreak forecasting and human behavior analysis during public health emergencies.
He earned his PhD in Epidemiology from UCLA, specializing in network methods applied to behavioral science, public health, and scientometrics. His doctoral research established foundational approaches for analyzing population-level dynamics during health crises.
Dewey's research focuses on developing high-quality data platforms for network-based public health surveillance. He investigates real-time human behavior changes during pandemics, leveraging non-traditional data streams to model disease transmission and design effective interventions. His methodology combines computational network analysis with epidemiological frameworks to address complex health challenges.
His 2024-2025 publications reveal a cohesive research trajectory spanning pandemic behavior analysis, respiratory virus seasonality, mental health measurement, and network-based disease control. These works consistently employ advanced network methodologies and time-series analysis, demonstrating strong interdisciplinary integration across epidemiology, behavioral science, and data science.
As part of the MIGHTE group, Dewey collaborates on projects spanning digital epidemiology, pandemic preparedness, and climate-health interactions. The lab utilizes machine learning and mathematical modeling to predict disease outbreaks, optimize hospital resource allocation, and improve clinical decision-making through innovative data integration approaches.
