Prof. Al Bovik has received a grant to develop methodologies for testing the perceptual quality of images delivered by microwave, submillimeter wave, millimeter-wave, x-ray, infra-red, and optical imaging devices commonly deployed in security applications.
The Department of Electrical and Computer Engineering extends a warm welcome to Dr. David Soloveichik and Dr. Milos Gligoric, who join the department beginning Fall 2015.
Twelve students have been recognized with the Halliburton Foundation’s Move Forward Program Merit Award for the academic year 2014 – 2015.
Ken Pesyna was selected as a 2015 Marconi Society Paul Baran Young Scholar. The award recognizes Pesyna’s academic achievements and leadership in the field of communications and information science.
Texas ECE student Xinnian Zheng has received the "Stamatis Vassiliadis Best Paper Award" at the 15th International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation (SAMOS) that took place in Samos, Greece on July 20-23, 2015.
This week the University of Texas (UT) Solar Vehicle Team is participating in the Formula Sun Grand Prix 2015, which is taking place at the Circuit of The Americas in Austin, Texas.
Francesco Monticone, doctoral student in the Department of Electrical and Computer Engineering at The University of Texas at Austin’s Cockrell School of Engineering has received the Graduate Student Fellowship established by the IEEE Photonics Society for the academic year 2015-2016.
Prof. Lizy Kurian John along with Prof. Andreas Gerstlauer have received a grant for their project titled, ‘Adaptive Energy-Efficient Designs for Next Generation Smart Phone CPUs’ from Samsung Electronics through its 2015 Global Research Outreach (GRO) Program.
Professor Christine Julien will be awarded the prestigious 2015 Regents’ Outstanding Teaching Awards this August. It is considered to be the highest teaching honor bestowed by the University of Texas System Board of Regents.
Prof. Alan Bovik along with Lark Kwon Choi have developed a no-reference perceptual fog density prediction model and a perceptual image defogging algorithm that are based on natural scene statistics (NSS) and fog aware statistical features.
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