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VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
X-WR-CALNAME:EECS Faculty Candidate Seminar: Chen Chen
X-WR-TIMEZONE:Eastern Time (US & Canada)
BEGIN:VEVENT
DTSTAMP:20260711T172300Z
UID:tag:localist.com\,2008:EventInstance_52207018441496
DTSTART:20260303T160000Z
DTEND:20260303T170000Z
DESCRIPTION:Democratizing AI in Low-Resource Settings: Towards Efficient\, 
 Reliable\, and Self-Improving Knowledge Adaptation\n \n\nAbstract\n\nHardw
 are is at the heart of computing systems. However\, in recent years\, ther
 e have been more attacks exploiting hardware vulnerabilities and other exp
 loits that even traditional software-based protections cannot prevent. Har
 dware fuzzing has shown promise in detecting vulnerabilities in large-scal
 e designs\, such as modern processors. In this talk\, PhD candidate from T
 exas A&M University Chen Chen will first introduce hardware fuzzing as a m
 ethod for finding vulnerabilities and outline its three major problems. He
  will then detail how fuzzing techniques can be combined with traditional 
 methods\, such as formal verification and information flow tracking\, to a
 ddress these problems. Finally\, he will discuss AI for hardware fuzzing a
 nd future research directions.\n \n\nBiography\n\nChen Chen is a PhD candi
 date in the Department of Electrical and Computer Engineering at Texas A&M
  University\, advised by JV Rajendran. He received his BS degree from Purd
 ue University. His research focuses on hardware security\, with publicatio
 ns in top-tier conferences\, including USENIX Security\, NDSS\, DAC\, ICCA
 D\, and DATE. He received the Distinguished Paper Award at USENIX Security
  2024. He co-organizes HackTheSilicon\, the world's largest hardware secur
 ity capture-the-flag competition\, co-located with DAC\, USENIX Security\,
  CHES\, and DATE. He also founded and led the first Texas A&M Cohort for H
 ardware Security. In addition\, he serves on the program committee of the 
 CWE RTL Ad-Hoc Working Group.
GEO:35.958178;-83.924516
LOCATION:Min H. Kao Electrical Engineering and Computer Science\, 435
SUMMARY:EECS Faculty Candidate Seminar: Chen Chen
URL;VALUE=URI:https://calendar.utk.edu/event/eecs-faculty-candidate-seminar
 -chen-chen
CATEGORIES:Lectures & Presentations
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