Title: Real-time pandemic planning and response: experiences from the ongoing COVID-19 pandemic
Abstract: Dr. Majumder will discuss three of her research group’s recent publications at the intersection of machine learning and epidemiology to answer a wide range of research questions about the ongoing COVID-19 pandemic. Broadly, the talk will cover agent-based models for epidemic dynamics, natural language processing for bibliometrics analysis, and novel digital data sources for misinformation surveillance.
Recording of the talk: https://youtu.be/Yurj0fW6gLg
Dr. Maimuna (Maia) Majumder is a computational epidemiologist specializing in emerging epidemics and a recent graduate of the Engineering Systems program at MIT’s Institute for Data, Systems, and Society (IDSS). In between her graduate studies and her current position at CHIP, Maia spent a year at the Health Policy Data Science lab at Harvard Medical School’s Health Care Policy department as a postdoctoral fellow. During her masters and doctoral studies at MIT, she was funded through a graduate fellowship at HealthMap. Prior to Maia’s arrival at MIT, she earned a Bachelors of Science in Engineering Science (with a concentration in Civil and Environmental Engineering) and a Masters of Public Health in Epidemiology and Biostatistics at Tufts University. While at Tufts, Maia was a field researcher with the International Centre for Diarrheal Disease Research, Bangladesh (ICDDR,B), where she worked with clinic patients (and their data) to learn how to better tell their stories. Her current research interests involve probabilistic modeling, artificial intelligence, and “systems epidemiology” in the context of public health, with a focus on causal inference for infectious disease surveillance using digital disease data (e.g. search trends; news and social media). She also enjoys exploring novel techniques for data procurement, writing about data for the general public, and creating meaningful data visualizations. As of January 2019, Maia has been engaged in pandemic response efforts and is a leading expert in COVID-19 epidemiology.
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LOCATION: STATUS:CONFIRMED DTSTART:20201207T190000Z DTEND:20201207T190000Z END:VEVENT END:VCALENDAR