Alex Dimakis

Alex Dimakis is a Professor in the EECS department at the University of California, Berkeley. His research interests include Artificial Intelligence (AI) and Information, Data, Network, and Communication Sciences (IDNCS). He has published more than 150 papers and has served as an Associate Editor for several journals, as well as an Area Chair for major Machine Learning conferences. His research focuses on Generative AI, Information Theory, and Machine Learning. He is also an IEEE Fellow for contributions to distributed coding and learning.

Alexandros G Dimakis is a Professor in the Department of Electrical Engineering and Computer Sciences at UC Berkeley, specializing in Machine Learning and Information Theory. His research focuses on the intersection of these fields, with applications in distributed storage systems, wireless communication, and signal processing. Key contributions include network coding for data storage, compressed sensing with generative models, and deep learning techniques for inverse problems in imaging. His work also explores decentralized erasure codes, gossip algorithms, and robust methods for data recovery. Dimakis has published extensively on topics such as femtocaching, gradient coding, and causal generative models.