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DESCRIPTION:Abstract:\n\nThis presentation will discuss recent developments
  from Dr. Wang’s research group\, focusing on how artificial intelligenc
 e (AI)\, particularly deep reinforcement learning (DRL)\, is being used to
  improve urban intersection management. These advancements have led to mor
 e sustainable traffic systems\, promoting safer environments while reducin
 g travel times\, fuel consumption\, and emissions. We will also address th
 e challenges of deploying these AI technologies in complex urban settings\
 , with a focus on early efforts using edge AI for UAV obstacle avoidance a
 nd rapid traffic management. Lastly\, Dr. Wang will introduce the role of 
 explainable AI in enhancing the resilience\, privacy\, and accountability 
 of future AI-based cybersecurity solutions.\n\nBio:\n\nDr. Shen Wang is cu
 rrently an Assistant Professor (Tenured) at the School of Computer Science
 \, University College Dublin\, Ireland. Dr. Wang is a senior member of IEE
 E and an active member of its ITS society. He is also a member of the UCD 
 Earth Institute which focuses on interdisciplinary sustainability research
 . He received an M.Eng. degree from Wuhan University\, China\, and a Ph.D.
  degree from Dublin City University\, Ireland. Dr. Wang has been involved 
 with several EU projects as a co-PI\, WP\, and Task leader in big data str
 eaming for air traffic control\, and trustworthy AI for intelligent cybers
 ecurity systems. Some key industry partners of his applied research projec
 ts are IBM Research Brazil\, Boeing Research and Technology Europe\, and F
 raunhofer FOKUS. His research interests include connected autonomous vehic
 les\, explainable artificial intelligence\, and security and privacy for m
 obile networks.\n\nBldg: Old engineering building (Y3)\, G36\, Birmingham\
 , England\, United Kingdom\, B15 2TT
LOCATION:Bldg: Old engineering building (Y3)\, G36\, Birmingham\, England\,
  United Kingdom\, B15 2TT
ORGANIZER:zxj548@student.bham.ac.uk
SEQUENCE:14
SUMMARY:Distinguished Lecture: AI-Driven Connected Transportation: Moving B
 eyond Efficiency Towards Sustainability
URL;VALUE=URI:https://events.vtools.ieee.org/m/435160
X-ALT-DESC:Description: <br /><p><strong><img src="https://events.vtools.ie
 ee.org/vtools_ui/media/display/13c66e51-1f9e-4016-92e0-40c599c457dd"></str
 ong></p>\n<p><strong>Abstract:</strong></p>\n<p>This presentation will dis
 cuss recent developments from Dr. Wang&rsquo\;s research group\, focusing 
 on how artificial intelligence (AI)\, particularly deep reinforcement lear
 ning (DRL)\, is being used to improve urban intersection management. These
  advancements have led to more sustainable traffic systems\, promoting saf
 er environments while reducing travel times\, fuel consumption\, and emiss
 ions. We will also address the challenges of deploying these AI technologi
 es in complex urban settings\, with a focus on early efforts using edge AI
  for UAV obstacle avoidance and rapid traffic management. Lastly\, Dr. Wan
 g will introduce the role of explainable AI in enhancing the resilience\, 
 privacy\, and accountability of future AI-based cybersecurity solutions.</
 p>\n<p><strong>Bio:</strong></p>\n<p>Dr. Shen Wang is currently an Assista
 nt Professor (Tenured) at the School of Computer Science\, University Coll
 ege Dublin\, Ireland. Dr. Wang is a senior member of IEEE and an active me
 mber of its ITS society. He is also a member of the UCD Earth Institute wh
 ich focuses on interdisciplinary sustainability research. He received an M
 .Eng. degree from Wuhan University\, China\, and a Ph.D. degree from Dubli
 n City University\, Ireland. Dr. Wang has been involved with several EU pr
 ojects as a co-PI\, WP\, and Task leader in big data streaming for air tra
 ffic control\, and trustworthy AI for intelligent cybersecurity systems. S
 ome key industry partners of his applied research projects are IBM Researc
 h Brazil\, Boeing Research and Technology Europe\, and Fraunhofer FOKUS. H
 is research interests include connected autonomous vehicles\, explainable 
 artificial intelligence\, and security and privacy for mobile networks.</p
 >
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