Giannis Daras

Giannis Daras

Ph.D. student, Computer Science, UT Austin

I am a fourth year Computer Science Ph.D. student at UT Austin, supervised by Prof. Alexandros Dimakis.

I am doing research on deep generative models. My main goal is to explore the theoretical and practical limits of solving inverse problems using deep generative priors. I am interested in improving many aspects of deep generative models that could be useful for achieving that goal, such as fairness, high-quality sample generation, out-of-distribution generation, controllable synthesis, etc. Application wise, I hope that my research on inverse problems with generative priors will prove useful to important real-world applications, e.g. accelerating MRI.

During Summer 2022, I interned at Google Research with Peyman Milanfar, Mauricio Delbracio and Hossein Talebi. Prior to this internship, I worked as a Research Intern at Google with Vincent Chu and Abhishek Kumar. Before joining the Ph.D., I received my undergraduate degree in ECE from the National Technical University of Athens (NTUA). During my undergraduate studies, I worked as a Machine Learning Researcher in ExplosionAI and I successfully completed Google Summer of Code 2018.

News

Publications

DataComp: In search of the next generation of multimodal datasets

Published as an Oral in NeurIPS 2023 [Paper] [Code]

Citation: Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt, "DataComp: In search of the next generation of multimodal datasets" , NeurIPS 2023