Mingyi Hong received his Ph.D. degree from the University of Virginia, Charlottesville, in 2011. He is currently an Associate professor in the Department of Electrical and Computer Engineering at the University of Minnesota, Minneapolis. His research has been focused on developing optimization theory and algorithms for applications in signal processing and machine learning, and most recently applying these techniques for foundation model training, finetuning and alignment. He is an Associate Editor for IEEE Transactions on Signal Processing. His work has received two IEEE Signal Processing Society (SPS) Best Paper Awards (2021, 2022), an International Consortium of Chinese Mathematicians Best Paper Award (2020), and a few Best Student Paper Awards in signal processing and machine learning conferences. He is an Amazon Scholar, and he is the recipient of an IBM Faculty Award, a Meta research award, a Cisco research award, and the 2022 Pierre-Simon Laplace Early Career Technical Achievement Award from IEEE SPS.
