Giovanni Camurati is a postdoctoral researcher at ETH Zurich in the System Security Group under Prof. Srdjan Capkun. Previously, he earned his PhD at Sorbonne Université, conducted at EURECOM, and visited UC Louvain. His research focuses on system security at the physical layer , particularly targeting UWB , GNSS , and mixed-signal chips in wireless devices. Key research areas: Side-channel attacks, Covert channels, Firmware analysis, Automotive network security Awards: Distinguished Paper at USENIX Security 2024, Runner-up PhD Award from GDR Sécurité Informatique (2020), 3rd place at CSAW Europe 2018 Article trends show expertise in distance reduction attacks (Ghost Peak, Time for Change), EM leakage exploitation (Noise-SDR, Screaming Channels), and security testing frameworks (Inception, MCRank). His work bridges theoretical analysis with practical attacks on commercial systems like Apple U1 chips and Google Eddystone beacons. Contact: camurati@eurecom.fr
Professor Semra Yiğitaslan is a distinguished faculty member at Eskisehir Osmangazi University, Faculty of Medicine, Department of Medical Pharmacology. She has held academic positions including Lecturer (2014-2016) and Research Assistant (2004-2009), and currently serves as Program Coordinator (2023-present) and Ethics Committee Member (2015-present) within the same institution. Her academic journey began with undergraduate studies (1996-2003) followed by Expertise in Medicine (2004-2009), both completed at Eskisehir Osmangazi University. Professor Yiğitaslan's research spans multiple domains within pharmacology, with particular focus on Medical Pharmacology and Toxicology , Clinical Pharmacology , and Pharmacology and Clinical Pharmacology . Her work frequently investigates drug effects on various organ systems, with significant contributions to understanding chemotherapy-induced toxicities, neuropharmacology, and the therapeutic potential of natural compounds. Her research methodology predominantly employs animal models to explore drug mechanisms and protective interventions. Analysis of her publication record reveals a strong emphasis on experimental pharmacology with consistent output across multiple high-impact journals. Her research trajectory shows sustained focus on understanding drug mechanisms, particularly regarding cyclophosphamide-induced toxicities, oxidative stress pathways, and neuropharmacological effects. The breadth of her work spans from basic medicinal chemistry to clinical applications, demonstrating translational research capabilities. Professor Yiğitaslan has actively contributed to academic service through roles including Publication Committee Member for the Turkish Medical Students Research Journal (2021-present) and Foreign Language Redactor for Osmangazi Medical Journal (2019-2022). She serves as an Associate Member of the Clinical Research Ethics Committee (2014-present) and is a member of the Turkish Pharmacology Association (2005-present). Her supervisory record includes mentoring Master's students M. KIRCADERE (2020) and M. CEMİL (2019). Professor Yiğitaslan has led numerous research projects, particularly focusing on gastrointestinal mucositis, testicular damage, and cardiotoxicity related to chemotherapy agents. Her active participation in scientific conferences and peer review activities demonstrates her engagement with the broader pharmacological community.
Pasquale Malacaria is a Professor of Computer Science at Queen Mary University of London, affiliated with the School of Electronic Engineering and Computer Science. He serves as a faculty member in the Centre for Fundamental Computing and AI and is part of the Leadership Team for academics. His research interests span the theoretical foundations of computer science and their practical applications, with particular focus on information theory, logic, and game theory applied to understanding information transformation and leakage in computational processes. He has made significant contributions to program analysis and the use of model-checkers for detecting and quantifying information leakage in programs and side channels. Analysis of his recent publications reveals a strong trend toward cybersecurity decision support , with emphasis on quantitative methods for risk assessment, security investment optimization, and attack graph analysis. His work bridges theoretical information theory with practical security applications, particularly in areas like smart home security, healthcare cybersecurity, and industrial control systems. The research demonstrates a consistent evolution from foundational work on information flow to applied cybersecurity frameworks. Research funding includes significant grants from major organizations: "Unrestricted donation: Formal verification of privacy properties" from Meta Platforms Inc (£58,029, 2022-2025) "CHAI: Cyber Hygiene in AI enabled domestic life" from EPSRC (£329,505, 2020-2023) "Optimal Cybersecurity Investment" from EPSRC (£388,777, 2017-2021) Professor Malacaria teaches Logic in Computer Science at the postgraduate level, covering propositional logic, temporal logics, predicate logic, and program logics with practical applications using SAT solvers and model checkers. He also teaches Object-Oriented Programming at the undergraduate level, focusing on core concepts like classes, objects, methods, and inheritance in practical software development contexts.
Murtuza Jadliwala is an Associate Professor in the Department of Computer Science at the University of Texas at San Antonio (UTSA), where he also serves as Graduate Advisor of Record for the Cybersecurity Science MS program. Previously, he held positions at Wichita State University and Swiss Federal Institute of Technology (EPFL). His research focuses on cybersecurity, privacy-enhancing technologies, adversarial machine learning, and distributed systems security, with funding from NSF, Air Force Research Lab, NASA, and others. He received the NSF CAREER Award in 2020. Education: Ph.D. in Computer Science, State University of New York at Buffalo (2008) M.S. in Computer Science, State University of New York at Buffalo (2004) B.E. in Computer Engineering, Mumbai University (2000) His research interests span mobile/IoT security, blockchain technology, incentive mechanisms for security, and usability of privacy-preserving systems. Notable contributions include ScooterID (user authentication via mobility scooters) and Light Ears (smart light-based privacy leaks). He has published over 60 papers in top venues like IEEE S&P, NDSS, and USENIX Security. Awards: NSF CAREER Award (2020), Dwane & Velma Wallace Excellence in Teaching Award (2017), and multiple industry and conference recognitions. Teaching: Courses include Cybersecurity Fundamentals, Practical Attack & Defense Techniques, and Bitcoins & Cryptocurrencies. He leads the Machine Learning & Deployment Thrust at UTSA's MATRIX AI Institute.
Wenjie Xiong is an Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. He leads the BEARHW (Building Efficient and Resilient Hardware) lab focused on hardware security, leveraging hardware features to enhance system security and mitigate vulnerabilities. His research spans secure architectures, side-channel attacks, cryptographic co-design, and PUF-based security solutions. Xiong holds a Ph.D. from Yale University (2020) and has received notable awards including the 2024 Dean's Award for Outstanding New Assistant Professor. He has published extensively in top venues like ASPLOS, HPCA, and IEEE Transactions on Computers. Research Interests: Hardware Security & Privacy Computer Architecture Side-Channel Attacks & Mitigations PUF-Based Authentication Federated Learning Privacy Transient Execution Defense Grants & Awards: Dean's Award 2024 (Virginia Tech) Featured Paper in IEEE TC (2021) Best Student Paper Finalist (HOST 2017) Microsoft Research Fellowship (2015) Lab: BEARHW Lab focuses on secure hardware design, PUF implementations, and efficient security co-design. Current openings for postdocs/PhD students in hardware security.
Farinaz Koushanfar is a Professor at the University of California, San Diego (UCSD), with a former affiliation at the University of California, Berkeley. Her research focuses on advancing security, machine learning, and hardware design through interdisciplinary approaches. Key areas include adversarial defense mechanisms, cryptographic systems, federated learning, and zero-knowledge proofs. She has collaborated extensively with institutions and researchers globally, contributing to over 360 publications. Her work emphasizes practical security solutions, such as watermarking for intellectual property protection and methods to counteract adversarial attacks in neural networks. Recent trends in her publications highlight innovations in cache compression, robust watermarking for large language models, and securing wireless communication systems against modality-agnostic attacks. Collaborations with industry and academia underscore her commitment to real-world applications of theoretical advancements. Awards and grants are not explicitly listed here, but her prolific publication record and leadership in high-impact projects indicate significant recognition in her field. Advising and mentoring students and junior researchers are central to her academic contributions, though specific student names are not detailed in the provided text. Her lab’s work often intersects with emerging technologies like blockchain, edge computing, and privacy-preserving machine learning.
Shilin Zhu is an Assistant Professor in the Department of Computer Science and Engineering at the University of California, San Diego's Jacobs School of Engineering. Having completed their PhD at UCSD in 2021 with a dissertation titled 'Computing Images with Diverse Illumination Effects,' Zhu has established a prolific research career spanning computer graphics, computer vision, and machine learning. Zhu's research interests center around advanced rendering techniques, autonomous driving perception systems, privacy-preserving technologies, and wireless localization. Their work bridges theoretical computer science with practical applications, particularly in developing robust systems for challenging environments like foggy weather for autonomous vehicles and creating privacy-preserving solutions using smart LED technology. Zhu has made significant contributions to neural rendering, particularly in photon mapping and denoising techniques that improve the efficiency and quality of computer-generated imagery. Analysis of Zhu's publication record shows a clear progression from foundational work in rendering and computer vision during their PhD studies to increasingly applied research in autonomous systems and privacy technologies. Their most recent work demonstrates a growing interest in interdisciplinary applications, including agricultural technology and bioinformatics, while maintaining technical depth in core computer science areas. The research consistently features innovative applications of deep learning to traditional computer graphics and vision problems. Zhu has collaborated extensively with leading researchers in the field, including Zexiang Xu, Hao Su, Ravi Ramamoorthi, and Henrik Wann Jensen, reflecting strong integration within the computer graphics and vision research communities. Their work has appeared in top-tier venues including SIGGRAPH, CVPR, and ACM Transactions on Graphics.
Zikai Alex Wen is an Assistant Professor in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology. Previously, he earned his PhD from Cornell University in 2021 with a dissertation on educational video games and intelligent tutoring systems. His research bridges multiple domains including privacy-preserving technologies, educational technology, cybersecurity, and accessibility. Wen's primary research interests focus on differential privacy, educational technology for students with learning disabilities, phishing detection and prevention, and game design for accessibility. His work uniquely combines theoretical privacy foundations with practical applications in education and security. He has made significant contributions to understanding how privacy mechanisms can be effectively explained to users and how to design systems that protect sensitive data while maintaining utility. His publication record demonstrates consistent output in top venues including IEEE S&P, CHI, ASSETS, and VLDB. Recent work shows increasing focus on generative AI applications for household safety, enhanced differential privacy mechanisms, and continued innovation in educational technology for diverse learners. His research often involves interdisciplinary collaboration across computer security, human-computer interaction, and educational psychology. Wen has received recognition through publications in prestigious venues but specific awards aren't documented in the available records. His work has been supported by research grants focused on privacy technologies and educational accessibility, though specific grant details aren't provided in the source material. He maintains active collaborations with researchers worldwide, particularly with Changyu Dong, Wei Cai, and Shiri Azenkot. His research group focuses on developing practical privacy-preserving systems and accessible educational technologies, with ongoing projects exploring the intersection of AI, security, and inclusive design.
Matthew Hicks is an Associate Professor in the Department of Computer Science at Virginia Tech, serving as the CACI Faculty Fellow in Cyber Security. His research focuses on software, hardware, and embedded system security, particularly in energy harvesting and IoT systems. He holds a Ph.D. from the University of Illinois Urbana-Champaign (2013), an M.S. from the same institution (2008), and a B.S. from the University of Central Florida (2006). His research interests emphasize hardware security mechanisms, defensive routing against malicious designs, and resilient computing in energy-constrained environments. Notable contributions include work on FPGA fingerprinting, compiler-assisted fuzzing, and intermittent computing paradigms. Recent publications explore countermeasures against hardware trojans, energy-efficient buffering, and secure checkpointing in batteryless systems. Dr. Hicks has no listed academic awards but maintains an active publication record in top-tier conferences. His work bridges theoretical computer science with practical hardware implementations, addressing vulnerabilities at both software and physical layers. While no student advisees or grants are explicitly mentioned, his research portfolio demonstrates sustained engagement with cutting-edge cybersecurity challenges.
Billy Brumley is a Professor in the Department of Cybersecurity at Rochester Institute of Technology (RIT), holding the Kevin O’Sullivan Endowed Professorship in Cybersecurity. He serves as Director of Research at the Golisano College of Computing and Information Sciences (GCI). His research focuses on system security, cryptography engineering, and side-channel analysis. Brumley earned his Sc.D. from Aalto University (2012) and previously held a Professorship at Tampere University (Finland) for a decade. He is a 2018 ERC Starting Grant Laureate and former Staff Engineer at Qualcomm's Product Security Initiative. Education: Sc.D., Aalto University (2012) Key Roles: Director of Research (GCI), Endowed Professor Brumley’s research addresses vulnerabilities in cryptographic implementations and open-source software security, particularly OpenSSL. His work includes side-channel attack analysis, microarchitectural timing exploits, and countermeasure development. Recent projects include investigating child sexual abuse material dissemination on the Tor network and advancing post-quantum cryptography standards. He teaches courses such as Side Channel Analysis and Open Source Software Security, emphasizing practical mitigation strategies and vulnerability lifecycle management. Awards include the ERC Starting Grant and recognition as an Endowed Professor. Grants: ERC Starting Grant (2018) Labs/Teams: Leads cybersecurity research initiatives at RIT’s ESL Global Cybersecurity Institute
Yukui Luo is an Assistant Professor in the Department of Electrical and Computer Engineering at Binghamton University, SUNY. He earned his PhD in computer engineering (specializing in hardware-oriented security) from Northeastern University in 2023. His research focuses on advancing security in cloud and edge computing, with expertise in FPGA virtualization systems, IoT security, AI acceleration, and hardware accelerators. Education: Bachelor's: Shanghai University of Engineering Science Master's: Illinois Institute of Technology PhD: Northeastern University His research interests emphasize hardware trustworthiness, including FPGA-based virtualization, IoT security, AI acceleration defenses, and secure database systems. Recent work includes frameworks like TBNet for neural network protection in trusted environments and AdAPI for efficient private inference in edge computing. Notable contributions include publications at DAC 2024, ICCAD 2024, and IEEE conferences addressing FPGA vulnerabilities, privacy-preserving machine learning, and adversarial attack mitigation. He advises PhD students focusing on FPGA acceleration, hardware security, and machine learning. His lab explores cutting-edge solutions for secure computing in multi-tenant environments and edge devices. Dr. Luo actively recruits PhD students (starting Fall 2026) with strong technical backgrounds in computer architecture, FPGA design, cybersecurity, or related fields. He emphasizes rigorous application requirements, including academic records and critical engagement with his research papers.
James Chong is a Professor of Cardiovascular Medicine at the University of Sydney and a practicing cardiologist at Westmead Hospital. He serves as Co-Director of the Centre for Heart Research and Head of the Cardiac Regeneration Laboratory at the Westmead Institute for Medical Research. His expertise spans cardiovascular medicine, stem cell therapies, and cardiac regeneration. He holds advanced qualifications including a PhD, MBBS, and FRACP (Fellow of the Royal Australasian College of Physicians). Research interests focus on heart regeneration, stem cell applications, coronary atherosclerosis, and novel therapies for heart disease. Collaborations include work with Prof Charles Murry at the University of Washington. His work has been published in top journals like Nature and Science Translational Medicine, and he has secured major grants including NHMRC/MRFF Investigator awards. Award highlights include the 2024 Jian Zhou Medal and a Fulbright Scholarship. His research explores mechanisms of cardiac repair, including PDGF and peptide mimetics' roles in scar remodeling. He leads projects on stem cell therapies, multi-omics strategies for heart attack analysis, and enhancing pluripotent stem cell-derived cardiomyocyte engraftment. Notable grants include funding for regenerative therapies, scar modulation via Tropoelastin, and gene therapies for arrhythmias. His lab investigates arrhythmia mechanisms and cardiac fibrosis, with clinical focus on acute heart failure and patient care outcomes post-dissection.
C Giuffrida is an Associate Professor at the Faculty of Science, Vrije Universiteit Amsterdam, with affiliations to the Network Institute and the Systems and Network Security group. His research focuses on computer systems security, hardware vulnerabilities, and software reliability. Giuffrida holds a PhD in Computer Systems from Vrije Universiteit Amsterdam (2014). His academic contributions span multiple areas including transient execution attacks, fuzzing techniques, and hardware-software co-design for security. Research Interests: Hardware Security: Investigating vulnerabilities like Spectre, Rowhammer, and speculative execution risks. Software Security: Focusing on memory safety, compiler optimizations, and exploit mitigation strategies. Systems Research: Developing tools like BinRec for binary analysis and VPS for C++ vulnerability protection. His work has been recognized with awards such as the Distinguished Paper Award in 2021. Giuffrida supervises advanced courses in operating systems and hardware security, and has guided 16 PhD theses to completion.
Milan Abel Lopuhaä-Zwakenberg is an Assistant Professor at the University of Twente, holding dual appointments at the Digital Society Institute and the Formal Methods and Tools research group within the Faculty of Electrical Engineering, Mathematics and Computer Science. His expertise bridges theoretical computer science with practical security applications for critical infrastructure systems. His research focuses on computer security, differential privacy, and formal methods, with specialized work in attack trees, fault trees, and defense trees for modeling security vulnerabilities. He develops quantitative analysis techniques including statistical model checking and integer linear programming to address side channel attacks and risk mitigation in cyber-physical systems. His work demonstrates particular strength in translating formal verification methods into actionable security solutions for smart grids and aerospace systems. Recent publications reveal a clear trajectory toward practical implementation of theoretical security models, with increasing emphasis on real-world case studies in critical infrastructure. His 2024-2025 output shows significant expansion in satellite security applications and gridshield dependencies, while maintaining core contributions to fault tree analysis and differential privacy frameworks. The research consistently integrates quantitative metrics with formal verification to address evolving security challenges. Dr. Lopuhaä-Zwakenberg has received prestigious recognition for his contributions: Best paper award at the 14th International Conference on the Digital Society (2020) Best Paper Award at the 21st International Conference on Software Engineering and Formal Methods (2023) SPIN 2025 Best paper award (2025) As an active researcher within the Formal Methods and Tools group, he collaborates extensively on security analysis projects that combine attack-fault-defense trees with quantitative risk assessment methodologies. His team develops advanced tools for security dependency mapping in critical infrastructure, with current work focusing on satellite mission security and smart grid resilience through the Gridshield framework.
Dean M. Tullsen is a Professor in the Department of Computer Science and Engineering at the University of California, San Diego. He leads the High Performance Processor Architecture and Compilation Lab and focuses on computer architecture, particularly multithreading, multicore processors, secure execution, and energy-efficient design. His research bridges hardware and software for parallel computing, security, and resource optimization. Education: Ph.D. from the University of Washington (1996), B.S. and M.S. from UCLA. Research Interests: Computer architecture, multithreading, speculative execution, hardware security, energy efficiency, and heterogeneous computing. Scientific Awards: Best Paper Awards at USENIX Security Symposium (2024), IEEE S&P (2023), and Distinguished Paper Awards at POPL (2021), ASPLOS (2023), plus the 2020 ACM SIGARCH/IEEE-CS TCCA Influential ISCA Paper Award. Students: Advised 30+ graduate students, including Craig Disselkoen, Mohammadkazem Taram, and Ashish Venkat, who now hold positions at Google, Microsoft, and academia. Lab: Leads the High Performance Processor Architecture and Compilation Lab, advancing techniques in secure execution and parallel computing.
