Alex Dimakis

Alex Dimakis is a Professor in the EECS department at University of California, Berkeley. He holds a Ph.D. from UC Berkeley (2008) and a Diploma from National Technical University of Athens (2003). His research focuses on Generative AI, Information Theory, and Machine Learning with over 150 publications.

Education: PhD in EECS (UC Berkeley, 2008); Diploma in ECE (NTUA, 2003).

He has received prestigious awards including the James Massey Award, NSF CAREER (2011), and IEEE Fellow distinction for contributions to distributed coding and learning. His service includes editorial roles at major journals, Area Chair positions at NeurIPS/ICML/AAAI, and chairing the MLSys 2021 Technical Committee.

Research interests emphasize generative models, information-theoretic foundations, and scalable machine learning systems. His work bridges theory and practice in areas like compressed sensing and distributed algorithms.