Keren Li is an Assistant Professor at
the Department of Mathematics, University of Alabama at Birmingham. He
graduated in mathematics from Nankai University in 2001 and received an MS in
Mathematics from Louisiana State University in 2004. He got his Ph.D. degree in
Statistics from the University of Illinois at Chicago in 2018. Then he joined
Northwestern University as a Postdoctoral Fellow in the Department of
Statistics and Data Science and NSF-Simons Center for Quantitative Biology
(2018-2022). He served as an Associate Scientist at the Informatics Institute,
University of Alabama at Birmingham from 2023 to 2024. He has been an Assistant
Professor at the University of Alabama at Birmingham since 2022. His research
interests include distributed machine learning, federated learning, deep
learning, bioinformatics, and financial mathematics. His major research
interests are the communication constraint scenarios in distributed learning
and federated learning. He is a member of the Institute of Mathematical Statistics.
Keren Li is an Assistant Professor at
the Department of Mathematics, University of Alabama at Birmingham. He
graduated in mathematics from Nankai University in 2001 and received an MS in
Mathematics from Louisiana State University in 2004. He got his Ph.D. degree in
Statistics from the University of Illinois at Chicago in 2018. Then he joined
Northwestern University as a Postdoctoral Fellow in the Department of
Statistics and Data Science and NSF-Simons Center for Quantitative Biology
(2018-2022). He served as an Associate Scientist at the Informatics Institute,
University of Alabama at Birmingham from 2023 to 2024. He has been an Assistant
Professor at the University of Alabama at Birmingham since 2022. His research
interests include distributed machine learning, federated learning, deep
learning, bioinformatics, and financial mathematics. His major research
interests are the communication constraint scenarios in distributed learning
and federated learning. He is a member of the Institute of Mathematical Statistics.