Alexandros G. Dimakis
Professor
![](/sites/default/files/2024-02/dimakis_alex.jpg)
Alex Dimakis is a professor in UT Austin. He received his Ph.D. from UC Berkeley and the Diploma degree from NTU in Athens, Greece. He has published more than 150 papers and received several awards including the James Massey Award, NSF Career, a Google research award, the UC Berkeley Eli Jury dissertation award, and several best paper awards. He served as an Associate Editor for several journals, as an Area Chair for major Machine Learning conferences (NeurIPS, ICML, AAAI) and as the chair of the Technical Committee for MLSys 2021. He is an IEEE Fellow for contributions to distributed coding and learning. His research interests include Information Theory and Machine Learning.
Research
Research Areas:
Research Interests:
- Information theory
- Coding theory
- Machine Learning
Current Research:
Generative models and deep learning.
Research Labs & Affiliations:
Wireless Networking and Communications Group (WNCG)
Machine Learning Lab (MLL)
Institue for Foundations of Machine Learning (IFML)
Select Publications
March 20, 2019. Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes.
.February 21, 2019. Quantifying Perceptual Distortion of Adversarial Examples.
.December 2, 2018. Restricted strong convexity implies weak submodularity. Institute of Mathematical Statistics.
.December 1, 2018. Discrete Attacks and Submodular Optimization with Applications to Text Classification.
.November 26, 2018. Adversarial Video Compression Guided by Soft Edge Detection.
.Awards & Honors
- 2014 - Army Research Office (ARO) Young Investigator Award
- 2012 - Best Paper, Joint Information Theory and Communications Society
- 2012 - Google Faculty Research Award
- 2011 - NSF Career Award
- 2010 - Best Paper, ComSoc Data Storage Committee
- 2008 - Eli Jury Dissertation Award
Contact Info
Alexandros G. Dimakis
Professor
(512) 471-3068
EER 6.816