Edward Ionides

Edward Ionides is a Professor of Statistics and Associate Chair for Undergraduate Studies at the University of Michigan, affiliated with the Department of Statistics within the College of Literature, Science, and the Arts. He holds a Ph.D. from the University of California, Berkeley (2001) and a B.A. in Mathematics from the University of Cambridge (1994). His research focuses on statistical theory and computational methods for time series analysis, particularly in ecology, epidemiology, and public health. He develops methodologies for inference in partially observed stochastic dynamic systems, with applications to infectious disease modeling, climate change, and economic health interactions.

Ionides has made significant contributions to statistical software, notably the R package pomp for analyzing partially observed Markov processes. He has been recognized with prestigious awards, including Fellow of the Institute of Mathematical Statistics (2023) and Fellow of the AAAS (2019). His teaching spans courses like Time Series Analysis (STATS 531), Probability (MATH/STATS 425), and Applied Statistical Methods (STATS 401). He has advised numerous Ph.D., master's, and undergraduate students, contributing to over 50 peer-reviewed publications and multiple funded grants totaling over $15 million.

Key grants include studies on urban vector-borne disease transmission and spatiotemporal statistical inference, funded by the NSF and NIH. His work integrates interdisciplinary collaborations, addressing challenges in public health policy, climate science, and mathematical biology. He also chairs departmental committees, including Undergraduate Programs and the Michigan Student Symposium for Interdisciplinary Statistical Sciences.