Speakers

Artificial Intelligence (AI) techniques are being applied to numerous applications from Healthcare to Cyber Security to Finance. For example, Machine Learning (ML) algorithms are being applied to solve security problems such as malware analysis and insider threat detection. However, there are many challenges in applying ML algorithms for various applications. For example, (i) the ML algorithms may be subject to cyber-attacks and (ii) they may violate the privacy of individuals. This is because we can gather massive amounts of data and apply ML algorithms on the data to extract highly sensitive information. Also, the attacks to the ML algorithms could result in catastrophic errors including in cyber physical systems such as transportation systems. The ML algorithms have to be resilient and recover from faults, malicious or otherwise. In addition to machine learning, the Generative AI (GenAI) systems may also be subject to attacks. On the other hand, both ML and GenAI algorithms could enhance the security of transportation systems. In this presentation, we discuss our research we are conducting as part of the USDOT National University Technology Center TraCR (Transportation Cybersecurity and Resiliency) led by Clemson University. In particular, we describe (i) the application of federated machine learning techniques for detecting attacks in transportation systems; (ii) publishing synthetic transportation data sets that preserves privacy, (iii) developing resiliency solutions for transportation systems to recover from malicious attacks, (iv) examining how GenAI systems are being integrated with transportation systems to provide security, and (v) improving the accuracy of the data to transportation systems that ensure integrity. Finally we discuss how the various features such as security, privacy, and integrity could be integrated so that robust transportation systems are developed.

Dr. Bhavani Thuraisingham is the Founders Chair Professor of Computer Science and the Founding Executive Director of the Cyber Security Research and Education Institute at the University of Texas at Dallas (UTD) (2004-2021). She is an elected Fellow of the ACM, IEEE, the AAAS, and the NAI. Her research interests are on integrating cyber security and artificial intelligence/data science including as they relate to the cloud, IoT, and Transportation Systems. She has received numerous technical, education and leadership awards including the IEEE CS 1997 Edward J. McCluskey Technical Achievement Award, the IEEE CS 2023 Taylor L. Booth Education Award, the IEEE Comsoc Communications and Information Security 2019 Technical Recognition Award, the IEEE ITSS 2026 Intelligence and Security Informatics Technical Achievement Award, the IEEE CS TC Services Computing 2017 Research Innovation Award, the IEEE Big Data Security 2024 Pioneer Award, the IEEE CS TCMC 2024 Technical Impact Award, the ACM SIGSAC 2010 Outstanding Contributions Award, and the ACM CODASPY 2017 Lasting Research Award. Her 46 year career includes industry (Honeywell), federal research laboratory (MITRE), US government (NSF) and US Academia. Her work has resulted in 140+ journal articles, 300+ conference papers, 200+ keynote and featured addresses, seven US patents, sixteen books, and over 120+ panel presentations including at Fortune Media, Lloyds of London Insurance, Dell Technologies World, The White House OSTP, and the United Nations. She has also written opinion columns for popular venues such as the New York Times, Inc. Magazine, Womensday.com and the Legal 500. She received her PhD from the University of Wales, Swansea, UK, and the prestigious earned higher doctorate (D. Eng) from the University of Bristol, UK. She also has a Certificate in Public Policy Analysis from the London School of Economics and Political Science. She has been featured ,in the book by the ACM in 2024 titled: “Rendering History: The Women of ACM-W” as one of the 30+ “Women that Changed the Face of World Wide Computing Forever.”

Data Centers, AI Workloads, and Efficiency: A Systems Perspective

Prashant Shenoy, PhD
University of Massachusetts Amherst
Massachusetts, USA

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AI, the Scaling Law, and the Memory-Wall Problem: An Entangled Advancement of Technology and Application

Xian-He Sun
Professor at Illinois Institute of Technology

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Learning the Action Grammar

Yiannis Aloimonos
Professor of Computational Vision and Intelligence at the Department of Computer Science, University of Maryland

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Planning Agents for Collaborative Reasoning and Multimodal Generation

Mohit Bansal
John R. & Louise S. Parker Distinguished Professor of Computer Science, UNC Chapel Hill

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The Eye In AI: Human Visual System (HVS) Approaches for Robust Artificial Intelligence

Karen Panetta
Distinguished Professor, Tufts University School of Engineering

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A new way of looking at the 3D World for Better Representation and Understanding

Chandra Kambhamettu
Professor of Computer Science at the University of Delaware

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Unlocking the Future: 30 Years of Innovation at the Crossroads of Visualization, Immersion, and Digital Twins

Carolina Cruz-Neira
Agere Chair Professor of Computer Science, University of Central Florida

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Traversing the AI + X Continuum for Impact

Nitesh Chawla
Frank M. Freimann Professor of Computer Science and Engineering, University of Notre Dame

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