Ph.D. Computer Science, Purdue University, November 2015.
M.S. Computer Science, Purdue University, May 2014.
B.S. Computer Science (Honors), Mathematics, minor in psychology, Purdue University, May 2011.
Dr. Abram Magner joined the University of Albany as an Assistant Professor in the Department of Computer Science in Fall 2019. Previously, he was Research Fellow in the Department of Electrical Engineering and Computer Science at the University of Michigan where he Conducted research in network science, mathematical methods for machine learning , and design of novel deep learning approaches to biomolecule design. Before that, he was an NSF Center for the Science of Information postdoctoral fellow at the Coordinated Science Lab, University of Illinois at Urbana-Champaign.
Dr. Magner's research primarily focuses on the foundations of network and data science, always with an eye toward applications: he is interested in the fundamental limits of learning/statistical inference and data compression/transmission problems involving networks, as well as efficient algorithms to achieve those limits. He is also interested in the modeling and mathematical analysis of complex networks as random graphs, and in the application of information theoretic tools to the above problems. His recent work has concerned various notions of learning the mechanisms underlying the evolution of dynamic graphs.
Publications, recent talks, CV, and news can be found here.