BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Sao_Paulo BEGIN:DAYLIGHT DTSTART:20380119T001407 TZOFFSETFROM:-0300 TZOFFSETTO:-0300 RRULE:FREQ=YEARLY;BYDAY=3TU;BYMONTH=1 TZNAME:-03 END:DAYLIGHT BEGIN:STANDARD DTSTART:20190216T230000 TZOFFSETFROM:-0200 TZOFFSETTO:-0300 RRULE:FREQ=YEARLY;BYDAY=3SA;BYMONTH=2 TZNAME:-03 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20211222T134347Z UID:B91D429E-F952-4BA8-A2CF-194F423292E1 DTSTART;TZID=America/Sao_Paulo:20211015T133000 DTEND;TZID=America/Sao_Paulo:20211015T153000 DESCRIPTION:Abstract:\n\nIn this talk\, an overview of current trends in ma chine learning computer design will be discussed with an emphasize on chal lenges and opportunities facing this field. It will focus on deep learning methods and applications. Deep learning has emerged as one of the most pr omising research fields in artificial intelligence. The significant advanc ements 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 oth er disciplines of computer science. Moreover\, the impact of machine learn ing on education\, research\, and economy will be briefly presented. The r apid 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 leade rs to take a lead in developing the necessary resources to ride the projec ted benefits of machine learning.\n\nShort Bio:\n\nNader Bagherzadeh is a professor of computer engineering in the department of electrical engineer ing 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\, recon figurable computing\, VLSI chip design\, network-on-chip\, 3D chips\, sens or networks\, computer graphics\, memory and embedded systems\, since he r eceived a Ph.D. degree from the University of Texas at Austin in 1987. He is a Fellow of the IEEE.\n\nVirtual: https://events.vtools.ieee.org/m/2799 97 LOCATION:Virtual: https://events.vtools.ieee.org/m/279997 ORGANIZER:jose.azambuja@inf.ufrgs.br SEQUENCE:1 SUMMARY:CASS Talks with Nader Bagherzadeh\, University of California at Irv ine\, USA URL;VALUE=URI:https://events.vtools.ieee.org/m/279997 X-ALT-DESC:Description: <br /><p>&nbsp\;</p>\n<p>&nbsp\;</p>\n<p>Abstract:< /p>\n<p>In this talk\, an overview of current trends in machine learning c omputer design will&nbsp\;be discussed with an emphasize on challenges and opportunities facing this field. It&nbsp\;will focus on deep learning met hods and applications. Deep learning has emerged as&nbsp\;one of the most promising research fields in artificial intelligence. The significant&nbsp \;advancements that deep learning methods have brought about for large sca le image&nbsp\;classification tasks have generated a surge of excitement i n applying the techniques&nbsp\;to other problems in computer vision and m ore broadly into other disciplines of&nbsp\;computer science. Moreover\, t he impact of machine learning on education\, research\,&nbsp\;and economy will be briefly presented. The rapid growth of machine learning is&nbsp\;p ositioned to impact our lives in a way that we have not been able to fully imagine.&nbsp\;It behooves government leaders to take a lead in developin g the necessary&nbsp\;resources to ride the projected benefits of machine learning.&nbsp\;</p>\n<p>Short Bio:&nbsp\;</p>\n<p>Nader Bagherzadeh is a professor of computer engineering in the department of&nbsp\;electrical en gineering and computer science at the University of California\, Irvine\,& nbsp\;where he served as a chair from 1998 to 2003. Dr. Bagherzadeh has be en involved&nbsp\;in research and development in the areas of: computer ar chitecture\, reconfigurable&nbsp\;computing\, VLSI chip design\, network-o n-chip\, 3D chips\, sensor networks\, computer&nbsp\;graphics\, memory and embedded systems\, since he received a Ph.D. degree from&nbsp\;the Univer sity of Texas at Austin in 1987. He is a Fellow of the IEEE.&nbsp\;</p> END:VEVENT END:VCALENDAR