Prof. Dr. Noor Zaman Jhanjhi

Prof. Dr. Noor Zaman Jhanjhi is a distinguished Senior Professor of Computer Science at Taylor’s University, Malaysia, where he specializes in Artificial Intelligence and Cybersecurity. As the Director of the Research Center, Center for Intelligent Innovation CII, and Program Director for Postgraduate Research Degree Programmes, he plays a pivotal role in shaping academic excellence and driving cutting-edge research initiatives.

Globally acclaimed for his scholarly contributions, Prof. Jhanjhi has been consistently ranked among the world’s top 2% research scientists (2022, 2023, 2024, and 2025) and stands as one of Malaysia’s top computer science researchers. He has been named amongst the top 0.05% of all scholars worldwide according to the 2025 ScholarGPS rankings. His exceptional work has earned him prestigious accolades, including the Outstanding Faculty Member Award (MDEC Malaysia, 2022) and the Vice Chancellor’s Best Research Citations Award (Taylor’s University, 2023).

A prolific author and editor, Prof. Jhanjhi has published over 80 research books with leading publishers such as Springer, Elsevier, IGI Global, Bentham, IET, and Wiley, etc., amassing 1,000+ impact factor points. His mentorship spans 45 postgraduate completions, and he has examined 70+ Ph.D. and Master’s theses worldwide.

As an Editor-in-Chief, Associate Editor, and Editorial Board member for top-tier journals (PeerJ Computer Science, IEEE Access, CMC Computers), he advances scholarly discourse. His leadership extends to securing 40+ international research grants, underscoring his influence in innovation.

A dynamic keynote speaker, Prof. Jhanjhi, has delivered 100+ invited talks and chaired major conferences. His decade-long engagement with ABET, NCAAA, and NCEAC accreditation bodies highlights his dedication to global academic standards. Combining research brilliance, academic leadership, and a passion for mentorship, Prof. Jhanjhi continues to inspire the next generation of computer scientists while shaping the future of AI and cybersecurity.

Dr. Birhanu Eshete

Title: The Provenance of Trust: Securing the Deep Learning Lifecycle from Data to Decision

Dr. Birhanu Eshete is an Associate Professor of Computer Science in the College ofEngineering and Computer Science at the University of Michigan–Dearborn, where he directs the Data-Driven Security & Privacy Laboratory. His research develops methods and systems to identify, characterize, and mitigate security, privacy, safety, transparency, and ethical risks in AI systems with emphasis on high-stakes applications such as autonomous vehicles, predictive diagnostics, financial forecasting, and cyber-attack detection.

Dr. Eshete’s research has been published in all leading venues in security, privacy, and AI, including IEEE S&P, ACM CCS, USENIX Security, ISOC NDSS, IEEE/IFIP DSN, ACM PETS, IEEE ACSAC, and IEEE SaTML, and featured in widely accessible venues such as Science Magazine. His expertise has also contributed to national efforts, including the U.S. National Institute of Standards and Technology (NIST) Trustworthy & Responsible AI Resource Center.

His contributions have been recognized with highly competitive awards and funding, including the 2024–2025 Fulbright U.S. Scholar Award from the U.S. Department of State, the 2024–2025 Faculty Excellence in Research Award from the College of Engineering and Computer Science, the 2023 NSF CAREER Award from the U.S. National Foundation, the 2018 USENIX Security Symposium Distinguished Paper Award, and was a finalist for the Best Applied Security Research Award in North America in 2018.

Dr. Selçuk Köse

Invited Talk: Thrusting the Quantum Computer: Security Threats from Side-channel Leakage to PUFs and Trojans

Selçuk Köse received his PhD degree in Electrical and Computer Engineering from the University of Rochester in 2012. After spending nearly seven years at the University of South Florida (USF), he joined the Department of Electrical and Computer Engineering at the University of Rochester where he is currently a Professor. He previously worked at TÜBİTAK, NXP semiconductor, Intel corporation, and Eastman Kodak. Dr. Köse is a recipient of the NSF CAREER award (2014), USF College of Engineering Outstanding Junior Research Achievement Award (2014), USF Outstanding Faculty Award (2016), Cisco Research Award (2015, 2016, and 2017) and USF Outstanding Research Achievement Award (2017). His research interests include VLSI circuit design, hardware security, cryogenic electronics, and quantum computing. His research has been funded by NSF, DARPA, Department of Energy, SRC, Cisco, Intel, and TSMC.

Superconducting digital electronics provide the classical control and readout infrastructure for many quantum computing platforms, operating in close proximity to superconducting qubits at cryogenic temperatures. This talk will begin with an overview of superconducting digital logic and the physical realization of superconducting qubits, establishing the hardware foundations of contemporary quantum computing systems. After reviewing key operating principles, the focus will shift to the interface circuits that connect superconducting digital controllers to qubit and readout subsystems.

These interface circuits define critical security boundaries by translating ultrafast superconducting signals into accessible electrical quantities. The talk will examine side-channel leakage mechanisms arising from superconducting digital control and interface circuitry, followed by a discussion of hardware Trojans that may be embedded within the digital control and readout stack. Recent work on physical unclonable functions (PUFs) implemented in superconducting digital control circuits will also be presented as a hardware-rooted approach to device identification and authentication.

Looking ahead, this talk argues that hardware trust must be treated as a fundamental design requirement in superconducting quantum computing systems. As these platforms scale, security considerations will increasingly influence the co-design of qubits, superconducting digital logic, and interface circuits, shaping how reliable and trustworthy quantum computers are ultimately built.

Dr. Al Amin Hossain

Title: Securing AI with Zero Trust

Abstract:

The widespread adoption of artificial intelligence (AI) across mission-critical systems, Internet of Things (IoT) environments, and microelectronics-enabled infrastructures has substantially expanded the cyber-attack surface. Traditional perimeter-based security models are no longer adequate to protect modern AI systems that are highly distributed, data-centric, and continuously evolving. Zero Trust Architecture (ZTA), grounded in the principle of "never trust, always verify," offers a robust, adaptive security paradigm to address these challenges. Accordingly, it is essential to examine the role of Zero Trust as a foundational enabler of secure and trustworthy AI technologies. Our study analyzes the application of Zero Trust principles to AI-enabled enterprise systems, cloud-native platforms, and large language models (LLMs) across the AI lifecycle, including data ingestion, model training, inference, and deployment. Emphasis is placed on least-privilege access, continuous verification, micro-segmentation, and data integrity. The spectacular findings demonstrate that integrating Zero Trust into AI architectures enhances system resilience, mitigates adversarial threats, and enables secure AI deployment within IoT and microelectronics-driven environments.