Co-chair: Ryan Simpson
Ryan Simpson is a second year Masters Student at the Friedman School of Nutrition Science and Policy, enrolled in the new Nutrition Data Sciences division. As part of the Tufts Initiative for the Forecasting and Modeling of Infectious Diseases (InForMID), Ryan works on forecasting infectious and foodborne diseases as well as famine humanitarian emergencies on a research grant in collaboration with the US Department of Defense’s Defense Advanced Research Projects Agency (DARPA). His work utilizes time series analysis approaches to model varying features of infectious diseases (primarily influenza) and applies these techniques for foodborne illnesses and complex emergencies. Prior to Tufts, he received two Bachelors of Arts degrees from Yale University in Environmental Engineering and Global Affairs.
Co-chair: Aishwarya Venkat
Ash is a first-year doctoral student in Agriculture, Food, & Environment at Friedman. Her research involves identification of spatiotemporal patterns in complex events, such as infectious disease outbreaks and famine. She is also part of the Tufts Initiative for the Forecasting and Modeling of Infectious Diseases (InForMID) team, and is currently using time series methods and machine learning approaches to forecast influenza and famine. Ash received a Masters in Environmental Engineering at Tufts, and completed her Bachelors in Biosystems Engineering at Virginia Tech.
Operations Coordinator: Yi Zhao
Yi is a second-year master’s student in Nutritional Epidemiology at Friedman with a substantial research interest in diet and cognition. Currently, she is using machine learning methods to link complex dietary factors as a mixture with health outcomes including cardiovascular diseases and cognitive impairment among the elderly population. Prior to Tufts, Yi received a master’s degree in Global Health from Duke University and worked on the Global Burden of Disease project at the Institute for Health Metrics and Evaluation.