Shuheng Zhou is a Full Professor of Statistics at the University of California, Riverside. Her research focuses on high dimensional statistics, machine learning, privacy, approximation and randomized algorithms, and network and combinatorial optimization. Her research addresses challenges in computational biology, neuroscience, genomics, and spatio-temporal modeling. 

Dr. Zhou received her Bachelor’s degree from Tsinghua University in Beijing, China, and her PhD in Electrical and Computer Engineering from Carnegie Mellon University. Prior to her tenured appointment at UC Riverside, she served on the faculty at the University of Michigan (2010–2017) and held postdoctoral fellowships at ETH Zürich (2008–2010) and Carnegie Mellon University (2006–2008). Her honors and recognition include being an Elected Fellow of the Institute of Mathematical Statistics, recipient of the Elizabeth Crosby Research Award at the University of Michigan, as well as having a featured article on differential privacy, co-authored with Professor Larry Wasserman, from the American Statistical Association.