Pierre-Emmanuel Gaillardon is a Professor in the Department of Electrical & Computer Engineering and Adjunct Professor in the School of Computing at the University of Utah. He holds a joint appointment since July 2024, having previously served as Assistant Professor (2016–2019) and Adjunct Assistant Professor in Computing (2016–2019). His research focuses on FPGA design, VLSI systems, nanoelectronics, and hardware security. He leads projects in emerging devices like TIGFETs, compute-in-memory architectures, and radiation-hardened FPGA fabrics. Teaching includes courses on Digital VLSI Design, Embedded Systems Design, and thesis supervision. He has secured grants from NSF, DARPA, and industry partners totaling over $10M, addressing topics like FPGA redaction, neuromorphic systems, and environmental sensors. Notable awards include the NSF CAREER Award (2018) and IEEE Senior Member elevation (2016). He actively serves on IEEE committees for nanoelectronics and EDA tools, contributing to standards like OpenFPGA.
Frank Piessens is a Full Professor in the Department of Computer Science at KU Leuven's Faculty of Engineering Science, where he leads the Distributed and Secure Software (DistriNet) research group. His research focuses on cutting-edge security challenges at the hardware-software interface. His research interests span: Hardware-software co-design for end-to-end security Confidential computing architectures Microarchitectural side-channel mitigation Secure IoT development Compiler-based security mechanisms Control-flow integrity techniques Recent publications (2024-2025) demonstrate strong focus on: Hardware security cost/performance tradeoffs Processor-level security enhancements (RISC-V, high-end CPUs) IoT device lifecycle security Control-flow leakage prevention Microcontroller IP protection He currently supervises PhD students including M. Bognár and H. Winderix, and leads major research initiatives such as: Hardening confidential computing through vertically integrated system design (2025-2031) Designing secure hardware for software-exploitable attacks (2025-2029) Compiler-based mitigations for microarchitectural side-channels (2023-2027) Security Arms Race at the Hardware-Software Boundary (2020-2025)
Nele Mentens is a full professor at both KU Leuven and Leiden University, where she leads cutting-edge research in applied cryptography, hardware security, and secure embedded systems. At KU Leuven, she is affiliated with the Faculty of Engineering Technology and the Electrical Engineering Department (ESAT), leading the Emerging Technologies, Systems & Security (ES&S) research group at the Diepenbeek campus. Simultaneously, she holds a full professorship at Leiden University’s Leiden Institute of Advanced Computer Science (LIACS), focusing on applied cryptography and security. She has been instrumental in numerous national and international research initiatives, including Horizon Europe and NWO-funded projects. Full Professor, KU Leuven (since 2023) Full Professor, Leiden University (since 2020) Associate Professor, KU Leuven (2014–2023) Post-doctoral Researcher & Lecturer, KHLim / KU Leuven (2007–2014) Ph.D. in Engineering Science, KU Leuven (2007) M.Sc. in Electrical Engineering, KU Leuven (2003) Her research focuses on secure and efficient hardware design, particularly for cryptographic applications on FPGAs, reconfigurable architectures, IoT security, and neuromorphic computing. She explores physical attack resistance, side-channel analysis protection, and trusted computing architectures, with applications in healthcare, industrial monitoring, and endpoint AI. Her work bridges theoretical cryptography with practical hardware implementations, emphasizing energy efficiency and real-time performance. The 15 most recent publications reflect a strong trend toward secure, energy-efficient, and intelligent embedded systems. Topics include neuromorphic AI accelerators, trusted IoT architectures, dynamic reconfiguration for side-channel protection, and secure medical data processing. These works span disciplines such as computer architecture, cybersecurity, digital design, and embedded systems, with a focus on hardware-software co-design and real-world deployment. Nele Mentens has received recognition for her contributions, including: Best Paper Award, DATE'16 Best Paper Nomination, AsianHOST'17 Best Paper Award, CHES'19 She has supervised over 15 Ph.D. students and post-docs, both current and former, and has served as principal investigator in approximately 25 funded research projects. Her work has attracted significant grants from Horizon Europe, NWO, FWO, and national innovation programs. She actively contributes to the academic community through editorial roles in top journals and leadership in major conferences. Nele Mentens leads the ES&S research group at KU Leuven and collaborates closely with LIACS at Leiden University. Her team includes Ph.D. students, post-docs, and research experts working on projects like NimbleAI, NeuroSoC, and TrustedIoT. She has also established secure electronics labs through infrastructure grants and maintains strong international ties with institutions such as EPFL, Ruhr University Bochum, and ETH Zurich.
Prof. Dr. Andreas Herkersdorf is a Full Professor and Chair of Integrated Systems at the Technical University of Munich (TUM) School of Computation, Information and Technology. His research focuses on application-specific multicore processors (MPSoC), FPGA-based prototyping, fault-tolerant systems, and energy-efficient architectures, with applications in IP packet processing, automotive systems, and visual computing. He has received multiple IBM innovation awards and serves on editorial boards including the DFG Review Board for computer architecture. Education: Dipl.-Ing. Electrical Engineering (TUM, 1987), Dr. techn. Electrical Engineering (ETH Zurich, 1991) Research: MPSoC architectures, autonomic computing, NoC resilience, FPGA acceleration, and self-optimizing systems. Awards: IBM Master Inventor (1998), IBM Outstanding Technical Achievement Award (2001), multiple IBM Innovation Achievement Awards (1996-2003) His recent publications emphasize hardware/software co-design, machine learning integration for runtime optimization, and network-on-chip innovations. He collaborates on projects involving 6G systems, smartNICs, and automotive communication protocols.
Eric Wustrow is an Associate Professor in the Department of Electrical, Computer & Energy Engineering at the University of Colorado Boulder , affiliated with the College of Engineering and Applied Science . His research focuses on network security, internet censorship, and cryptographic protocols. Contact: ewust@colorado.edu , Phone: 734-330-8702, Office: ECCR 1B13. Academic Rank: Associate Professor Department: Electrical, Computer & Energy Engineering University: University of Colorado Boulder Eric Wustrow's research explores methods to measure and circumvent internet censorship, analyze network vulnerabilities, and enhance privacy in digital communications. His work includes studying the Great Firewall of China, DNS and TLS security, and developing anticensorship tools like ShadowTLS and WATER. He also investigates cryptographic weaknesses in network devices and secure hardware implementations. Recent publications examine the effectiveness of anticensorship tools, the impact of IPv6 on information controls, and vulnerabilities in encrypted protocols. His studies include speculative execution attacks, DNS censorship measurement, and techniques to exploit transient errors in TLS for key compromise. These works highlight evolving network threats and countermeasures. Eric's research has been supported by grants such as the CAREER: Combating Censorship from within the Network (2022) and SaTC: CORE: Medium: Collaborative: Studying the Impact of IPv6 on Information Controls and Censorship Circumvention (2020). These projects focus on developing network-level solutions to censorship and security challenges.
Sam Pagliarini is a Professor in the Department of Electrical and Computer Engineering (ECE) at Carnegie Mellon University (CMU), where he leads research in hardware security and trustworthy integrated circuit design. Prior to joining CMU in 2024, he directed the Centre for Hardware Security at Tallinn University of Technology (2019–2023). He holds a Ph.D. in Electrical Engineering from Télécom Paris (France, 2013), an M.S. in Microelectronics from Universidade Federal do Rio Grande do Sul (Brazil, 2011), and a B.S. in Computer Engineering from the same institution (2008). His research focuses on securing hardware design pipelines, including EDA tools for secure chips, countermeasures against hardware trojans, and obfuscation techniques to protect intellectual property. He has pioneered work on reconfigurable-based obfuscation (ReBO), layout-effect-based security mechanisms, and post-quantum cryptographic accelerators. Recent efforts include collaborations on post-quantum cryptography vulnerabilities and silicon demonstrations of hardware trojan insertion methods. Prof. Pagliarini's work spans academia and industry, with contributions to both theoretical frameworks (e.g., SCARF framework for chip security) and applied solutions like the G-GPU ASIC accelerator generator. His research has addressed emerging threats in the IC supply chain and explored trade-offs between security, performance, and design complexity in post-silicon manufacturing.
Damon L. Woodard is a Professor in the Department of Electrical and Computer Engineering at the University of Florida (UF) and serves as Director of the Florida Institute for National Security (FINS) and the Applied Artificial Intelligence (AAI) Group. His research focuses on applied artificial intelligence, hardware security, and biometrics, with particular emphasis on adversarial AI, AI-enabled hardware assurance, and explainable AI (XAI). He holds IEEE and ACM Senior Member status and is a Kavli Frontiers Fellow. Education: Ph.D. in Computer Science and Engineering, University of Notre Dame M.E. in Computer Science and Engineering, Penn State University B.S. in Computer Science and Computer Information Systems, Tulane University Research Interests: Dr. Woodard explores cutting-edge areas such as AI hardware acceleration, multi-modal AI systems, and counter-AI strategies. His work bridges cognitive science and technology through projects like text stylometry and psychological analysis frameworks. Key focus areas include semiconductor reverse engineering, hardware trojan detection via SEM imaging and machine learning, and secure IoT biometric systems. Highlighted Awards: National Academy of Science Kavli Frontiers Fellow IEEE Senior Member ACM Senior Member AAAI Membership Leadership & Contributions: As FINS Director, he oversees national security initiatives integrating AI and hardware assurance. His AAI Group develops resource-efficient AI solutions for constrained environments. Notable projects include the SECURE segmentation metric for IC reverse engineering and the MaGNIFIES GAN framework for electronic system inspection. Labs & Teams: Leads the Applied Artificial Intelligence Group and collaborates across disciplines through FINS, fostering innovation in AI-driven security and semiconductor integrity.
Yazhou Tu is an Assistant Professor in the Department of Computer Science and Software Engineering at Auburn University. He specializes in Cyber-Physical System Security, Side Channel Analysis, and Privacy in embedded systems. His work focuses on addressing vulnerabilities in sensors, actuators, and IoT devices to enhance security and privacy in critical systems. Education: Ph.D. Computer Science, University of Louisiana at Lafayette M.S. Software Engineering, Tsinghua University B.S. Software Engineering, Wuhan University Research Interests: Dr. Tu’s research explores cutting-edge topics such as adversarial control of embedded systems, acoustic and magnetic side-channel attacks, and privacy risks in robotic and biomedical systems. He develops novel defense mechanisms like ADC-Bank and Transduction Shield to counteract physical signal injection attacks. Key Contributions: His work spans sensor security, IoT exploitation, and healthcare technology, with notable studies on 3D printer IP theft, vehicle control via smart glasses, and keystroke tracking via audio. He also investigates physics-informed ML for porous media and glucose monitoring systems. Awards & Grants: No specific awards or grants listed in the provided data, but his prolific publication record highlights sustained research excellence. Labs & Collaborations: Engaged in Auburn’s Center for Artificial Intelligence and Cybersecurity Engineering and other interdisciplinary initiatives focused on secure embedded systems and cyber-physical infrastructure.
Tarik Graba is a Lecturer at Télécom Paris and a member of the Secure and Safe Hardware (SSH) research team within the Information Processing and Communication Laboratory (LTCI) department. His work focuses on hardware security, embedded systems, and cryptographic implementation. Education: Not explicitly mentioned Current Affiliations: Télécom Paris (Faculty), LTCI, SSH Team His research explores designing secure and reliable integrated systems , with emphasis on managing complexity, power consumption, and flexibility in embedded environments. He contributes to side-channel analysis , lightweight cryptographic algorithms , and hardware-based security mechanisms . The 15 most recent publications highlight his work in lightweight cryptography , hardware security , and embedded system optimization , particularly focusing on RISC-V extensions , side-channel leakage , TRNG circuits , and secure cryptographic processors . Scientific Awards Academic Palms award, Télécom Paris (2021) Tarik Graba collaborates extensively in hardware security research and has advised multiple projects on physical security countermeasures and embedded cryptographic systems . He works with teams like the SSH Laboratory to develop secure hardware architectures.
Marcus Norrgård is a Professor of Law at the University of Helsinki , leading the Vaasa Unit of Legal Studies within the Faculty of Law. His expertise spans intellectual property law , copyright , design law , and the ethical implications of AI and 3D printing on legal frameworks. He actively contributes to Nordic legal research and EU copyright harmonization , with recent projects focusing on AI-generated content and virtue ethics in private law . His 15 most recent articles analyze topics such as Nordic copyright legislation , AI training data protection , and design law harmonization , reflecting his work with foundations like Harry Schaumans Stiftelse and Vaasan Aktiasäätiö . Norrgård serves on doctoral committees and as an opponent in thesis defenses , while advising Finnish parliamentary committees on copyright and telecommunications reforms . He has held leadership roles including Chairman of the Finnish Copyright Council (2008–2020) and Director of the IPR University Center (2018–2021).
Tiago Manuel Ribeiro Gomes is an Assistant Professor at the Department of Industrial Electronics within the School of Engineering at the University of Minho, Portugal. He is also a Senior Researcher at Centro ALGORITMI and a member of both the IE R&D Group and the ESRG R&D Lab. Holding a Ph.D. in Electronics and Computers Engineering, his research focuses on embedded real-time systems, computer architectures, and hardware/software co-design for IoT devices. Academic Degree: Ph.D. in Electronics and Computers Engineering Current Position: Assistant Professor, School of Engineering, University of Minho Gomes has led extensive research in IoT systems over 15 years, particularly in hardware acceleration for automotive LiDAR sensors, secure embedded systems, and efficient OS frameworks for low-end devices. His work includes the EU-funded CROSSCON project and spans hardware-assisted security, dynamic binary translation, and wireless sensor networks. Recent publications highlight his expertise in automotive sensor technology, with articles like FOG-Zip for LiDAR compression, SecureQNN for TinyML security, and Hardware-Assisted Range Image Generation for LiDAR processing. His work bridges IoT, embedded systems, and cybersecurity, focusing on real-time performance and hardware-software co-design. Projects include the development of reliable/secure automotive sensor solutions and EU project CROSSCON. He contributes to open-source frameworks like UTango for IoT security and investigates heterogeneous fault tolerance architectures using Arm/RISC-V processors. Labs: IE R&D Group, ESRG R&D Lab Education: Ph.D. in Electronics and Computers Engineering, Master’s in Telecommunications Engineering (both from University of Minho)
Francesco Regazzoni is a Senior Researcher at the Faculty of Informatics, Università della Svizzera italiana (USI), and affiliated with the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI). His work bridges embedded systems, cybersecurity, and artificial intelligence, with a focus on securing hardware and cyber-physical systems. Research Interests: His expertise spans embedded and cyber-physical systems security, side-channel attacks, post-quantum cryptography, hardware trojans, random number generators, and the security of AI and approximate computing. He also contributes to hardware/software co-design and operating systems security. The analysis of his recent publications reveals a consistent focus on hardware and system-level security , particularly in resource-constrained environments like IoT and embedded devices. His work integrates machine learning for attack detection and applies formal methods to ensure trust in hardware. A growing emphasis is placed on securing AI systems from physical and adversarial threats. Scientific Contributions: Over 100 peer-reviewed publications One book and one patent Extensive international collaboration (Belgium, Netherlands, USA, Switzerland, Singapore) Advising and Grants: While specific advisees and grants are not listed, his leadership in funded research projects and involvement with ALaRI and IDSIA suggest active mentorship and project coordination. His work has been supported by industry (e.g., ST Microelectronics, HP), the Swiss National Foundation, and the European Union. Labs and Teams: He is part of the Graph Machine Learning Group (GMLG) at IDSIA, which evolved from the Advanced Learning and Research Institute (ALaRI). This group focuses on graph machine learning, reinforcement learning, and dynamical systems, particularly in non-stationary environments.
Patanjali Sristi is an Assistant Professor at Augusta University's School of Computer and Cyber Sciences, specifically within the Department of Cybersecurity Engineering. Located at 100 Grace Hopper Lane in Augusta, Georgia, Dr. Sristi joined the university in January 2025 after previously working as a Postdoctoral Researcher at the University of Florida with Dr. Swarup Bhunia. Their academic journey began with a B.Tech in Electrical and Electronics Engineering from Pondicherry University in 2011, followed by both MS and Ph.D. in Computer Engineering from the Indian Institute of Technology (IIT Madras). Dr. Sristi's educational background demonstrates a strong foundation in electrical engineering and computer science, with advanced specialization in hardware security. Their Ph.D. research at IIT Madras was supervised by Dr. Kamakoti Veezhinathan, focusing on critical aspects of hardware security that would form the basis of their future research career. Dr. Sristi's research program centers on addressing one fundamental question: "How can we design, measure and build efficient and affordable security assurances for a given hardware design in the context of an untrusted supply chain while respecting the design constraints at each level of abstraction?" This research vision spans three interconnected domains: AI for System Design: Developing data models and AI techniques for next-generation hardware systems AI for Hardware Security: Creating AI models for vulnerability detection, countermeasure evaluation, and mitigation of supply chain threats Cybersecurity for AI: Establishing metrics and algorithms for secure development, deployment, and operation of AI systems Dr. Sristi's scholarly output reveals a consistent focus on hardware security challenges within the modern distributed electronics supply chain. Their work demonstrates a progression from foundational research on hardware trojans and side-channel attacks toward comprehensive frameworks addressing the emerging "zero trust" paradigm in hardware security. A notable trend is the integration of AI/ML techniques with traditional hardware security approaches, reflecting the evolving nature of security threats and countermeasures. Their publications span prestigious venues including IEEE Transactions on VLSI Systems, IEEE Transactions on Computers, and various IEEE conferences, indicating strong recognition within the hardware security community. While specific awards aren't detailed in the available information, Dr. Sristi's research impact is evident through multiple US patents (including US Patent 11,899,827 and US Patent App. 17/392,376) and invitations to deliver talks at prominent organizations including Sony Finishing School, Northrop Grumman, and IEEE events. Their work on Netflix Privacy Analysis was featured in Wired, demonstrating real-world relevance and impact. Dr. Sristi actively engages with students through courses including CSCI 8940 (Dissertation Research), CSCI 8720 (Problems in Computer & Cyber), and CSCI 7900 (Research Colloquium). Their research program appears well-supported through collaborations with major institutions and industry partners, as evidenced by workshops conducted for the Indian Army in conjunction with Pravartak and IIT Madras. These partnerships suggest substantial research funding and collaborative opportunities that enhance the educational experience for students. Though specific lab information isn't provided in the available text, Dr. Sristi's research scope suggests involvement with hardware security laboratories equipped for VLSI design, testing, and security evaluation. Their work on IoT security, hardware trojans, and supply chain security would require facilities for physical device testing, side-channel analysis, and hardware emulation. The focus on "zero trust" implementation for hardware security indicates a research environment that bridges theoretical security models with practical implementation challenges.
Jennifer Wong-Ma is an Associate Teaching Professor at the University of California, Irvine (UCI), affiliated with the Donald Bren School of Information and Computer Sciences and the Computer Science Department. She joined UCI in 2018, previously serving as teaching faculty at Stony Brook University. Her roles include Vice Chair of Undergraduate Studies and advisor for organizations like Women in Information and Computer Sciences (WICS). She holds a Ph.D. in Computer Science from UCLA, with prior research focused on wireless systems and hardware IP protection. Education: Ph.D., Computer Science, University of California, Los Angeles, 2006 Research & Teaching Interests: Development of learning and teaching tools for CS education Alternative assessment strategies and pedagogical innovation CS education equity and retention initiatives Integration of theater techniques in classroom engagement Key Contributions: Co-founded the Coffee Meets Teaching program to foster faculty collaboration Member of UCI’s inaugural Faculty Academy for Teaching Excellence (FATE) Advocate for women in technology through WIT@UCI and WICS mentorship Awards: CS Department Award for Undergraduate Education (2012) CS Department Award for Major Contributions to Undergraduate Education (2016) Honored at 2023 ICS Awards Celebration Her work emphasizes community-building in education, bridging academia and industry, and leveraging technology to enhance student success. Current projects include optimizing grading infrastructure and predictive modeling for academic retention.
Youhua Shi is a full Professor in the Faculty of Science and Engineering at Waseda University, Japan. He obtained his Doctor of Engineering from Waseda in 2005 and is an active member of IEICE, IPSJ, IEEE, and two Japanese academic societies. His research portfolio integrates trustworthy computing, hardware security of AI accelerators, energy-harvesting interface circuits for triboelectric nanogenerators, and low-power VLSI design-for-test methodologies. Education: Doctor of Engineering, Waseda University (2005) Graduate studies, Waseda University, Division of Engineering (completed 2005) Research Interests: Prof. Shi pursues trustworthy and secure silicon systems, spanning hardware Trojans in automated AI-accelerator flows, radiation-hardened latch design for soft-error resilience, and power-efficient CNN accelerators exploiting zero-gating and data-reuse techniques. Parallel work targets energy-autonomous IoT through advanced interface circuits for triboelectric nanogenerators, achieving record energy-per-cycle beyond the classical CMEO limit. Publication Trends: Recent articles (2024-2025) emphasize two thrusts: (i) security of AI/FPGA accelerators—proposing stealthy hardware-Trojan frameworks embedded within design-space-exploration flows that can misclassify up to 97% of inputs—and (ii) power electronics for triboelectric harvesters—introducing dual-output rectifiers and Bennet-doubler biasing that multiply output power >150× over conventional full-wave rectifiers, enabling battery-free IoT nodes. Scientific Awards: APCCAS Best Student Paper Award – 2020 IEEK Best Paper Award – 2012 Students & Collaboration: He has mentored numerous doctoral and master’s scholars, including Yirui Su, Chao Guo, Jinghao Ye, Lin Ye, Saki Tajima, and Masaru Oya, many of whom serve as first authors on his high-impact publications, indicating an active and productive advising role. Labs & Teams: While the text does not name a specific laboratory, his continued affiliation with Waseda University’s Faculty of Science and Engineering and his extensive project output imply he leads a research group focused on secure & energy-efficient VLSI systems, collaborating closely with colleagues such as Prof. Masao Yanagisawa and Prof. Nozomu Togawa.
