Alex Dimakis, a Greek scientist of the University of Texas, will lead a team that will produce one of the most powerful artificial intelligence (AI) hubs in the academic world.
The University at Austin announced that the Center for Generative AI, powered by a new GPU computing cluster, will comprise 600 NVIDIA H100s GPUs. This is short for graphics processing units, which are specialized devices that enable rapid mathematical computations. The devices are ideal for training AI models.
The Texas Advanced Computing Center (TACC) will host and support the cluster, called Vista.
“Artificial intelligence is fundamentally changing our world, and this investment comes at the right time to help UT shape the future through our teaching and research,” said President Jay Hartzell.
With a core focus on biosciences, health care, computer vision, and natural language processing (NLP), the new center will be housed within UT’s interdisciplinary Machine Learning Laboratory and co-led by the Cockrell School of Engineering and the College of Natural Sciences.
Dimakis: Academia to play a leading role in AI
In recognition of AI’s growth across industries, it also includes faculty members and support from Dell Medical School, as well as researchers from the School of Information and McCombs School of Business.
“We believe academia should continue to play a leading role in the development of AI,” said Dimakis, director of the center and professor in the Cockrell School’s Chandra Family Department of Electrical and Computer Engineering.
“Open-source models, open data sets and interdisciplinary peer-reviewed research is the safest way to drive the upcoming AI revolution,” he explained. “Universities are uniquely suited to shape this ecosystem, and we are excited to be on the frontier of generative AI here in Austin.”
Alex Dimakis is a professor and holds the Stanly P. Finch Centennial Professorship in Engineering in the Chandra Family Department of Electrical and Computer Engineering at The University of Texas.
Dimakis received his Ph.D. in 2008 and M.S. degree in 2005 in electrical engineering and computer sciences from UC Berkeley. He also received a diploma degree from the National Technical University of Athens in 2003.
In 2009, he was a CMI postdoctoral scholar at Caltech. He received an NSF CAREER award in 2011, a Google faculty research award in 2012, and the Eli Jury dissertation award in 2008. He is the co-recipient of several best paper awards, including the joint Information Theory and Communications Society Best Paper Award in 2012.
He is currently serving as an associate editor for IEEE Signal Processing letters and has served as chair of the Data Storage track at GLOBECOM. He was a keynote speaker at the International Symposium on Network Coding (NetCod).
His research interests include information theory, coding theory, signal processing, and networking, with a current focus on distributed storage, network coding, distributed inference, and message passing algorithms.