Department of Statistics and the College
Jeremy Hoskins studies problems at the interface between physics, computation, and mathematics. A major theme of his research is studying the mathematical foundations of problems arising in imaging, in particular, what happens in highly scattering and quantum systems. His work also involves the concomitant development of fast, efficient, and accurate algorithms for solving large-scale problems, such as those arising in the simulation of complex optical systems. These methods have broad applications in many other disciplines, including signal processing, genomics, acoustics, and medical imaging.
His research has been published in Nature Methods, the SIAM Journal of Scientific Computing, Inverse Problems, Physical Review, and the Journal of Mathematical Analysis and Applications.
Hoskins received a PhD in applied mathematics from the University of Michigan. He was a Gibbs Assistant Professor in mathematics at Yale University.