CASS Talks with Nader Bagherzadeh, University of California at Irvine, USA

#CASS #Talks #2021

Abstract:

In this talk, an overview of current trends in machine learning computer design will be discussed with an emphasize on challenges and opportunities facing this field. It will focus on deep learning methods and applications. Deep learning has emerged as one of the most promising research fields in artificial intelligence. The significant advancements that deep learning methods have brought about for large scale image classification tasks have generated a surge of excitement in applying the techniques to other problems in computer vision and more broadly into other disciplines of computer science. Moreover, the impact of machine learning on education, research, and economy will be briefly presented. The rapid growth of machine learning is positioned to impact our lives in a way that we have not been able to fully imagine. It behooves government leaders to take a lead in developing the necessary resources to ride the projected benefits of machine learning. 

Short Bio: 

Nader Bagherzadeh is a professor of computer engineering in the department of electrical engineering and computer science at the University of California, Irvine, where he served as a chair from 1998 to 2003. Dr. Bagherzadeh has been involved in research and development in the areas of: computer architecture, reconfigurable computing, VLSI chip design, network-on-chip, 3D chips, sensor networks, computer graphics, memory and embedded systems, since he received a Ph.D. degree from the University of Texas at Austin in 1987. He is a Fellow of the IEEE.