Thomas Goldstein

Thomas Goldstein is an associate professor in the Department of Computer Science.

Goldstein’s research focuses on large-scale optimization and distributed algorithms for big data. His work has applications in machine learning and image processing, especially for MRI and CT.

He received his doctorate in applied mathematics from UCLA in 2010. Goldstein joins UMIACS from a postdoctoral fellowship with the Department of Electrical and Computer Engineering at Rice University. He has also served as a postdoctoral fellow at Stanford University, and as a data scientist for the Washington University School of Medicine.

Go here to view Goldstein's academic publications on Google Scholar.