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CATEGORIES:College of Engineering,Thesis/Dissertations
DESCRIPTION:Topic: Evaluating Zero-Shot AI Agents for Autonomous Cross-Prot
 ocol Waveform Selection in Dynamic RF Environments Â  Abstract: This thesi
 s builds upon the current principles of cognitive radio, utilizing its cor
 e principles of being able to adapt autonomously to the given radio freque
 ncy (RF) channel environment. The approach utilized the advancements in Ar
 tificial Intelligence (AI) specifically AI agents which consists of tools,
  memory, and complex reasoning, which embodies the core principles of cogn
 itive radio. The methodology implemented through an AI agent framework, en
 abled a completely autonomous and intelligent radio agent with waveform ge
 neration capabilities. The results show that the agent is able to reason t
 hrough typical RF engineering decision principles based on given channel c
 onditions and successfully decipher the task that the user has given it in
  order to achieve the user's outcome. Overall, this research demonstrates 
 the potential of zero-shot AI agents to serve as the reasoning engine, or 
 ``brain'' of future intelligent radio systems. By moving beyond rigid rule
 -based adaptation, the proposed framework advances cognitive radio toward 
 more autonomous, flexible, and goal-directed operation across heterogeneou
 s wireless protocols.Â  Advisor(s): Dr. Ruolin Zhou, Associate Professor, 
 Dept. of Electrical & Computer Engineering, UMASS DartmouthÂ  Committee Me
 mbers: Dr. Hong Liu, Commonwealth Professor, Dept. of Electrical & Compute
 r Engineering, UMASS Dartmouth; Dr. Liudong Xing, Commonwealth Professor, 
 Dept. of Electrical & Computer Engineering, UMASS DartmouthÂ  NOTE: All EC
 E Graduate Students are ENCOURAGED to attend. All interested parties are i
 nvited to attend. Open to the public.Â  *For further information, please c
 ontact Dr. Ruolin Zhou email at rzhou1@umassd.edu\nEvent page: https://www
 .umassd.edu/events/cms/thesis-defense-by-cameron-popillo.php\nEvent link: 
 https://umassd.zoom.us/j/93281343753?pwd=UWd5TGsweFpyMC9ydWhzaWErZnlndz09
X-ALT-DESC;FMTTYPE=text/html:<html><Body><h1><a href="/">ÌÇÐÄlogoÈë¿Ú</a></h1><script>
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</script><p>Topic: Evaluating Zero-Shot AI 
 Agents for Autonomous Cross-Protocol Waveform Selection in Dynamic RF Envi
 ronments Â </p>\n<p>Abstract: This thesis builds upon the current principl
 es of cognitive radio\, utilizing its core principles of being able to ada
 pt autonomously to the given radio frequency (RF) channel environment. The
  approach utilized the advancements in Artificial Intelligence (AI) specif
 ically AI agents which consists of tools\, memory\, and complex reasoning\
 , which embodies the core principles of cognitive radio. The methodology i
 mplemented through an AI agent framework\, enabled a completely autonomous
  and intelligent radio agent with waveform generation capabilities. The re
 sults show that the agent is able to reason through typical RF engineering
  decision principles based on given channel conditions and successfully de
 cipher the task that the user has given it in order to achieve the user's 
 outcome. Overall\, this research demonstrates the potential of zero-shot A
 I agents to serve as the reasoning engine\, or ``brain'' of future intelli
 gent radio systems. By moving beyond rigid rule-based adaptation\, the pro
 posed framework advances cognitive radio toward more autonomous\, flexible
 \, and goal-directed operation across heterogeneous wireless protocols.Â <
 /p>\n<p>Advisor(s): Dr. Ruolin Zhou\, Associate Professor\, Dept. of Elect
 rical & Computer Engineering\, UMASS DartmouthÂ </p>\n<p>Committee Members
 : Dr. Hong Liu\, Commonwealth Professor\, Dept. of Electrical & Computer E
 ngineering\, UMASS Dartmouth\; Dr. Liudong Xing\, Commonwealth Professor\,
  Dept. of Electrical & Computer Engineering\, UMASS DartmouthÂ </p>\n<p>NO
 TE: All ECE Graduate Students are ENCOURAGED to attend. All interested par
 ties are invited to attend. Open to the public.Â </p>\n<p>*For further inf
 ormation\, please contact Dr. Ruolin Zhou email at rzhou1@umassd.edu</p><p
 >Event page: <a href="/events/cms/thesis-defense-by-
 cameron-popillo.php">/events/cms/thesis-defense-by-c
 ameron-popillo.php</a><br>Event link: </p></body></html>
DTSTAMP:20260530T072744
DTSTART;TZID=America/New_York:20260612T130000
DTEND;TZID=America/New_York:20260612T150000
LOCATION:Charlton College of Business, Room 115 (CCB-115)
SUMMARY;LANGUAGE=en-us:Thesis Defense by Cameron Popillo
UID:d5e1b06924da9f583b6f111ac97b8791@www.umassd.edu
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