Aryan Mokhtari is an Assistant Professor in the Electrical and Computer Engineering Department of the University of Texas at Austin (UT Austin) where he holds the Fellow of Texas Instruments/Kilby. Before joining UT Austin, he was a Postdoctoral Associate in the Laboratory for Information and Decision Systems (LIDS) at the Massachusetts Institute of Technology (MIT), from January 2018 to July 2019. Before that, he was a Research Fellow at the Simons Institute for the Theory of Computing at the University of California, Berkeley, for the program on “Bridging Continuous and Discrete Optimization”, from August to December 2017. Prior to that, he was a graduate student at the University of Pennsylvania (Penn) where he received his M.Sc. and Ph.D. degrees in electrical and systems engineering in 2014 and 2017, respectively, and his A.M. degree in statistics from the Wharton School in 2017. During his graduate study, he was a Research Intern with the Big-Data Machine Learning Group at Yahoo!, Sunnyvale, CA, USA, from June to August 2016. Dr. Mokhtari received his B.Sc. degree in electrical engineering from Sharif University of Technology, Tehran, Iran, in 2011. His research interests include the areas of optimization, machine learning, and artificial intelligence. His current research focuses on the theory and applications of convex and non-convex optimization in large-scale machine learning and data science problems. He has received several awards and fellowships, including the Army Research Office (ARO) Early Career Program Award, the Simons-Berkeley Research Fellowship, and Penn’s Joseph and Rosaline Wolf Award for Best Doctoral Dissertation in electrical and systems engineering.
