Adrian Perrig is a Full Professor at the Department of Computer Science at ETH Zürich. He leads research in network security, distributed systems, and internet architecture, focusing on projects like the SCION secure internet architecture and its commercialization through Anapaya Systems. His work emphasizes secure communication, denial-of-service defense, and public key infrastructure (PKI) innovations. Affiliations: ETH Zürich, Institute for Information Security Key Contributions: SCION, SAGE, RHINE, F-PKI Research interests include path-aware networks, cryptographic protocols, and resilient systems. His publications span over 295 results since 2005, with notable awards including the Best Paper Award (CoNEXT 2021) and ANRP 2023. He has contributed to foundational work in secure routing, DNS security, and GPU attestation. Scientific awards include Best Paper Awards at CoNEXT and ACM SIGCOMM, as well as recognition for applied networking research. His work bridges academia and industry, addressing challenges in global network security and scalability.
John Clark is a Professor of Computer and Information Security at the University of Sheffield since 2017 and Director of the Siemens Digital MINE. Previously, he held roles as Professor of Critical Systems at the University of York (1992–2017) and worked at Logica in security R&D. He studied Mathematics and Applied Statistics at the University of Oxford. His research focuses on cybersecurity, software engineering, and AI applications, particularly in threat modeling, intrusion detection, quantum cryptanalysis, and secure autonomous systems. Clark leads the Security of Advanced Systems research group and has secured grants totaling over £36 million. Notable projects include the EPSRC-funded DAASE (2012–2019) and the Active Building Centre (2018–2022). His work on phishing detection (e.g., analyzing user behavior) and malware analysis has been widely recognized. He has been awarded the Royal Society Wolfson Merit Award (2013), GEECO medals (2005, 2013), and multiple best-paper prizes. Clark’s research spans theoretical and applied domains, including evolutionary computation for cryptanalysis, robotic system security, and smart grid protection. His labs explore areas like digital twin authentication and privacy-aware energy theft detection. He has supervised numerous grants and maintains active collaborations with industry and academia.
Babak Akhgar serves as Professor of Informatics and Director of CENTRIC (Centre of Excellence in Terrorism, Resilience, Intelligence and Organised Crime Research) at Sheffield Hallam University's College of Business, Technology and Engineering, with additional affiliation to the Culture and Creativity Research Institute. Recognized as a Fellow of the British Computer Society (FBCS), he maintains active leadership in security informatics research and education. His academic foundation includes a Software Engineering degree from Sheffield Hallam University, complemented by a Master's degree with distinction in Information Systems in Management and a PhD in Information Systems. This academic trajectory followed substantial industry experience as a Strategy Analyst and Methodology Director for multiple organizations. Professor Akhgar's research program bridges theoretical knowledge management with practical security applications, focusing on cyber security, counter-terrorism, intelligence frameworks, and big data analytics for national security. His scholarly output demonstrates consistent evolution from foundational knowledge management systems toward contemporary security challenges including cryptocurrency tracing, AI accountability in law enforcement, and smart city security frameworks. Recent work shows particular emphasis on ethical considerations, citizen acceptance of security technologies, and practical implementation of security solutions. Fellow of the British Computer Society (FBCS) Co-editor of influential security publications including 'Intelligence Management: Knowledge Driven Frameworks for Combating Terrorism and Organised Crime' Member of editorial boards for three international journals Chair and program committee member for numerous international security conferences As a doctoral supervisor, Professor Akhgar has guided research on cyber situational awareness, digital music ontology, and e-government services. His leadership extends to major EU-funded security initiatives including the MIICT project for migrant integration and development of the AP4AI accountability framework for artificial intelligence in security contexts. Through CENTRIC, he directs a research ecosystem that connects academic inquiry with real-world security challenges while addressing ethical, legal, and societal implications of security technologies.
Christopher Brooks is an Assistant Professor at the University of Michigan's School of Information, specializing in educational technologies and data science education. He directs the Educational Technology Collective (etc), a multidisciplinary research group focused on learning analytics, educational data mining, and collaborative learning systems. His work bridges computer science and education, with a focus on improving teaching methods through AI-driven tools and platforms. Research Interests: Development and impact assessment of educational technologies Predictive modeling for student success Data science pedagogy Privacy in smart home technologies Publications reflect a focus on learning analytics, MOOC design, and educational AI, with notable contributions to conferences like CHI, LAK, and AIED. Awards include multiple best paper recognitions. Teaching includes applied data science courses at UMich and Coursera. He leads the Master of Applied Data Science (MADS) program and collaborates with institutions like Microsoft to build AI-driven educational tools.
Ales Popovic is a Full Professor of Information Systems at NEOMA Business School, France. He holds a PhD in Management and Information Systems. His research focuses on the value of information systems (IS) in organizations, digitalization, AI, behavioral and organizational issues in IS, and IT in inter-organizational relationships. He has published widely in journals like Journal of the Association for Information Systems and Technological Forecasting and Social Change . Dr. Popovic’s research explores topics such as fake news engagement on social media, blockchain adoption in real estate, and the impact of digital platforms on traditional media. He serves on editorial boards for journals including International Journal of Information Management and Industrial Management & Data Systems . His work bridges theoretical and practical aspects of IS, emphasizing business value creation and ethical considerations in AI. Key contributions include studies on digital transformation, crisis management technologies, and the role of privacy in technology adoption. His research frequently addresses contemporary challenges like misinformation dynamics, gig worker burnout, and healthcare AI applications.
Berk Sunar is a Professor of Electrical & Computer Engineering and the founder of the Vernam Applied Cryptography and Cybersecurity Laboratory at Worcester Polytechnic Institute (WPI). He joined WPI in 2000 after holding postdoctoral and research roles at Oregon State University (OSU) and Trust Inc. His work focuses on applied cryptography, microarchitectural security, AI security, post-quantum cryptography, and homomorphic encryption. Sunar received his BSc from Middle East Technical University (1995) and PhD from Oregon State University (1998). Research interests include vulnerabilities in hardware (e.g., Rowhammer, TPM-FAIL), side-channel attacks, and cryptographic implementations. Notable contributions include discovering flaws in Intel CPUs and TPM chips affecting billions of devices, as well as developing defenses like cuHE (GPU-accelerated homomorphic encryption). Publications highlight breakthroughs in transient execution attacks (e.g., LVI, RIDL), post-quantum signature schemes (Dilithium), and cloud security (Firecracker VMM vulnerabilities). Awards include NSF CAREER (2002) and IBM Pat Goldberg Best Paper (2007). Advised over 30 graduate students, many of whom hold senior roles in academia and industry. Current research addresses AI security, quantum-resistant algorithms, and automated attack detection via machine learning. The Vernam Lab remains a hub for cybersecurity innovation.
Ka Ho Chow is an Assistant Professor in the Department of Computer Science at the University of Hong Kong, part of the School of Computing and Data Science. He holds a PhD from Georgia Institute of Technology and was previously a research scientist at IBM Research. His research focuses on the intersection of machine learning, cybersecurity, and scalable systems, emphasizing trustworthy AI and defense against security/privacy threats in federated learning, large language models, and visual recognition systems. Key achievements include IBM PhD Fellowship (2022) and Croucher Scholarship (2021). Education: PhD in Computer Science from Georgia Tech (2020), advised by Prof. Ling Liu. His work spans algorithmic optimization, infrastructure resilience, and adversarial machine learning. Current research explores attack-resilient solutions for centralized/federated learning and AI system vulnerabilities. Recent articles highlight innovations in federated learning security, gradient inversion attacks, backdoor detection, and privacy-preserving techniques. He has openings for PhD students interested in AI security and trustworthy systems. His lab collaborates on projects involving blockchain fraud detection (ZipZap), facial recognition privacy (Personalized Masks), and graph neural network robustness. Awards: IBM PhD Fellowship (2022), Croucher Scholarship (2021). Active in guiding PhD candidates and advising on microservices cloud migration (Atlas/SCAD systems). Research outputs include over 30 peer-reviewed papers spanning cybersecurity, AI ethics, and distributed learning frameworks.
Fenglong Ma is an Associate Professor at Pennsylvania State University, affiliated with the Institute for Computational and Data Sciences and the Center for Socially Responsible Artificial Intelligence. His research focuses on data mining, healthcare informatics, machine learning, natural language processing, and multimodal learning. He holds a Ph.D. from the University at Buffalo (2019) and degrees from Dalian University of Technology. His work addresses challenges in federated learning, medical AI, adversarial robustness, and multimodal systems. Key contributions include innovations in quantization for large language models, federated knowledge injection, and medical vision-language benchmarking. Recent publications explore topics like collaborative fairness in federated learning, robust medical vision-language models, and adversarial attack mitigation. His research bridges theory and practical applications in healthcare, cybersecurity, and personalized recommendation systems. He leads the PSU Data Science Lab and collaborates on projects involving AI ethics, multimodal data integration, and scalable medical foundation models.
David Atienza is a Professor in the Department of Electrical Engineering at the School of Engineering, Swiss Federal Institute of Technology in Lausanne (EPFL), renowned for pioneering embedded systems education and research in ultra-low power computing. His innovative teaching methods, including using Nintendo DS consoles and smartphones to teach embedded systems, earned him the 2015 EPFL Teaching Award in Electrical Engineering. His research focuses on Embedded Systems , Edge AI , and Wearable Healthcare , with breakthroughs in energy-efficient hardware-software co-design for biomedical applications. Key contributions include open-source platforms like X-HEEP and HEEPocrates for ultra-low power edge computing, and frameworks like SzCORE for seizure detection benchmarking. His work bridges computer architecture with real-world healthcare challenges, emphasizing privacy-preserving algorithms and sustainable computing. Recent publications (2023-2025) reveal a dominant trend toward biomedical edge AI and sustainable computing , with 70% of articles targeting healthcare wearables (seizure detection, cough monitoring) and 30% addressing energy efficiency in data centers and edge devices. His research consistently integrates open-hardware principles (RISC-V) with novel algorithm-hardware co-design. Awards include: 2015 EPFL Teaching Award in Electrical Engineering section While specific advising details are unreported, his extensive publication record and leadership in multi-partner projects like Sustainable Textile Electronics (STELEC) indicate active graduate supervision and significant research funding. His group develops open-source hardware frameworks used globally in academia and industry. He leads the Embedded Systems Laboratory at EPFL, driving projects in ultra-low power RISC-V architectures, biomedical wearables, and sustainable computing. Current initiatives include carbon-aware data center frameworks and multi-modal health monitoring systems deployable on commercial wearables.
Tamara Heidi Roth is a tenure-track Assistant Professor in the Information Systems Department at the Sam M. Walton College of Business, University of Arkansas. She previously served as a Post Doctoral Researcher at the Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg and has an interdisciplinary background spanning information systems and educational psychology. Dr. Roth holds two PhDs: one in Information Systems from the University of Luxembourg (2021-2024) and another in Educational Psychology from the University of Bayreuth, Germany (2020-2022). Her educational background reflects her interdisciplinary approach to research that bridges technology adoption with human and organizational factors. Dr. Roth's research focuses on the adoption and integration of emerging technologies, particularly blockchain and digital identity systems, within structured organizational environments such as government agencies and utilities. Her work explores how these technologies can drive innovation while addressing cultural and structural barriers to implementation. Through an interdisciplinary lens, she examines the intersection of technology, organizational behavior, and human-centric innovation. Her research spans multiple domains including public sector technology implementation, responsible innovation, digital identity systems, and the social implications of emerging technologies. Dr. Roth has published extensively in top-tier journals including the Journal of Information Technology, Government Information Quarterly, Journal of the Association for Information Systems, Nature Machine Intelligence, and MIT Sloan Management Review. Her recent work shows a strong focus on blockchain applications in government, digital identity systems, and the social implications of emerging technologies. She has developed a distinctive research trajectory examining how structured organizations adopt and implement blockchain and digital identity technologies, with particular attention to institutional barriers and cultural factors. Excellent Thesis Award, University of Luxembourg, 2024 (awarded to only the top 10% of Science, Technology, and Medicine PhD graduates) Dr. Roth serves as an Associate Editor for major conferences including the International Conference on Information Systems (ICIS) and has provided editorial reviews for numerous prestigious journals such as Journal of Information Technology, Management Information Systems Quarterly, and Journal of the Association for Information Systems. She teaches undergraduate courses at the University of Arkansas on Information Systems, Artificial Intelligence and Technology Ethics, and Introduction to Business Information Systems. Her research activity spans Innovation Management, Behavioral Research, Responsible Innovation, Organizing Visions, Digital Identities, and both Qualitative and Computationally Intensive Research approaches.
Dr. Volkan Dedeoglu is an active researcher at Queensland University of Technology (QUT), specializing in blockchain technology and IoT systems within the School of Computer Science. His work focuses on developing privacy-preserving frameworks and trust architectures for distributed systems. Research Focus: Blockchain applications in IoT and cyber-physical systems Privacy-preserving data sharing and threat intelligence Decentralized trust and reputation management Secure data aggregation and marketplace frameworks His recent work explores cutting-edge applications like CypherChain for privacy-preserving data aggregation in blockchain-based demand response programs and Priv-Share for differential privacy in cyber threat intelligence sharing. These publications demonstrate a consistent focus on bridging theoretical blockchain innovations with practical cybersecurity challenges in IoT ecosystems. Collaborative Research: Dr. Dedeoglu frequently collaborates with QUT colleagues including Raja Jurdak, Salil Kanhere, and Sidra Malik, indicating active participation in QUT's distributed systems and cybersecurity research groups.
Simone Silvestri is a Professor and Director of Graduate Studies in the Department of Computer Science at the University of Kentucky, within the Stanley and Karen Pigman College of Engineering. He has held this position since 2025, having previously served as Associate Professor from 2021-2025 and Assistant Professor from 2017-2021. Prior to his appointment at UK, he was an Assistant Professor at Missouri University of Science and Technology (2014-2017) and held postdoctoral positions at Pennsylvania State University (2012-2014) and Sapienza University of Rome (2010-2012). Dr. Silvestri earned his Ph.D. in Computer Science from Sapienza University of Rome, Italy in 2010, following a Laurea cum Laude in Computer Science from the same institution in 2006. His research focuses on Cyber-Physical-Human Systems, Internet of Things, Smart Grid Security, Terrestrial and Aerial Mobile Networks, and Network Management. His work bridges computer science with practical applications in agriculture, energy management, and disaster response scenarios. His research program has been supported by over $5 million in federal funding, including an NSF CAREER award in 2020. He has published more than 100 papers in top-tier journals and conferences including IEEE Transactions on Mobile Computing, IEEE Transactions on Smart Grids, and ACM Transactions on Sensor Networks. His recent work shows a strong trend toward applying cyber-physical systems to agricultural technology, energy management, and precision livestock farming, with increasing integration of machine learning techniques. NSF CAREER Award (2020) Best Demo Runner-Up Paper - IEEE PerCom (2025) Excellent Editor Award - IEEE Transactions on Network Science and Engineering (2024) Best Editor Award - Elsevier Pervasive and Mobile Computing (2024) Best paper award - IEEE International Conference on Network Protocols (2009) Dr. Silvestri has advised numerous graduate students to completion, including Ph.D. candidates Xu Tao and Ashtuoth Timilsina, and Master's students Josh Guess and Seifalla Moustafa. His research group has secured significant funding from NSF, NIFA, NATO, and other agencies for projects totaling over $6 million. He also created the CSMentor resource, providing guidance for computer science graduate students on academic writing, PhD success, and career development. Dr. Silvestri actively collaborates with researchers across multiple disciplines, particularly in agricultural technology and precision farming applications.
Professor Dingxuan Zhou is a distinguished academic serving as Professor and Head of School of Mathematics and Statistics at The University of Sydney, joining the institution on August 29, 2022. He is also a member of The Net Zero Institute and has held significant editorial positions, including editor-in-chief of the journal "Analysis and Application" of "Mathematical Foundations of Computing" and serving on the editorial boards of over ten international journals. Educational Background: BSc in Mathematics from Zhejiang University, China (1988) PhD in Mathematics from Zhejiang University, China (1991) Professor Zhou's research spans learning theory, neural networks, wavelet analysis, and approximation theory, with his current focus on the theory of deep learning. His work aligns with the Faculty of Science Research Strengths in Complex Systems, Precision and Digital Health, Data and Decisions, and National Security. His research demonstrates a consistent progression from foundational mathematical theory to cutting-edge applications in machine learning and artificial intelligence, with particular emphasis on understanding the theoretical underpinnings of neural networks and deep learning systems. His extensive publication record reveals a strong trend toward distributed learning frameworks, approximation theory for neural networks, and the mathematical foundations of deep learning. Recent work focuses on federated learning, transformers, physics-informed neural networks, and the theoretical analysis of over-parameterized networks, reflecting the evolving landscape of machine learning research with increasing emphasis on theoretical guarantees and practical applications. Scientific Awards: Humboldt Research Fellowship (1993) Fund for Distinguished Young Scholars from the National Science Foundation of China (2005) Highly-cited Researcher by Thomson Reuters/Clarivate Analytics (2014-17) World's Top 2% Scientist by Stanford University (2021, 2022, 2023) Professor Zhou has demonstrated exceptional leadership in research and mentorship, having conducted over 40 research grants as Principal Investigator, supervised more than 20 PhD students, and co-organized over 20 international conferences. His collaborative approach is evident in his extensive co-authorship network across multiple institutions globally. He has also served in significant administrative roles including Head of Department of Mathematics (2006-12), Associate Dean of School of Data Science (2018-22), and Director of the Liu Bie Ju Centre for Mathematical Sciences (2019-22) at City University of Hong Kong.
Sabine Roeser is a Full Professor of Ethics at Delft University of Technology, working within the Ethics and Philosophy of Technology Section at the Faculty of Technology, Policy and Management. She has been with TU Delft since 2001 and has held several leadership positions including Head of the Ethics and Philosophy of Technology Section (2015-2020), Head of Department of Values, Technology and Innovation (2021-2024), and Acting Dean of the Faculty of TPM (November 2024-April 2025). As one of six Principal Investigators in the NWO Gravitation project on 'Ethics of Socially Disruptive Technologies' (ESDiT), she co-leads the emotions and art lines of this major research initiative. Her educational background spans multiple disciplines, with degrees in painting (BA, Maastricht Academy of Fine Arts, 1994), philosophy (MA, University of Amsterdam, cum laude 1997), political science (MA, University of Amsterdam 1998), and a PhD in metaethics from Vrije Universiteit Amsterdam (2002). During her PhD studies, she conducted research at the University of Notre Dame and University of Reading. Roeser's research focuses on the intersection of ethics, emotions, and technology, particularly in the context of risk assessment and decision-making. She has developed 'affectual intuitionism,' a metaethical theory combining ethical intuitionism with cognitive theories of emotions. Her work argues that emotions serve as forms of moral cognition that can alert us to ethically relevant aspects of risky technologies. She has published two monographs ( Moral Emotions and Intuitions , 2011; Risk, Technology and Moral Emotions , 2018) and co-edited eight books with major academic publishers. Her research spans multiple technological domains including nuclear energy, climate change, transportation, and public health. Analysis of her recent publications reveals a consistent focus on the role of emotions in ethical decision-making, particularly in technological contexts. Her work increasingly explores how art can scaffold moral-emotional deliberation about risky technologies. She has made significant contributions to engineering ethics education, developing the 'Delft approach' that emphasizes problem-based learning and integration of ethical reflection throughout engineering curricula. More than 200 academic talks, mostly invited Over 100 interviews for popular media Member of various national and international policy advisory committees Former integrity officer of TU Delft (2018-2021) Chair of TU Delft's Human Research Ethics Committee (2014-2019) Roeser has secured competitive funding from organizations including NWO and the EU, leading multiple research projects and supervising numerous PhD candidates and postdoctoral researchers. She has played a key role in developing TU Delft's integrity policy and Code of Conduct. Her leadership has significantly grown both the Ethics and Philosophy of Technology Section and the Department of Values, Technology and Innovation.
Danushka Bollegala is a Professor in the Department of Computer Science at the University of Liverpool, where he leads both the Machine Learning and Natural Language Processing research groups. He previously held a lectureship at the University of Tokyo (2010-2013) and currently serves as an Amazon Scholar for Amazon Search. His research bridges fundamental AI with applications in healthcare, law, and social sciences. Research Focus: Professor Bollegala specializes in developing core NLP methodologies including word embedding techniques, semantic similarity measurement, and domain adaptation. His machine learning research explores privacy-preserving AI, unsupervised parsing, and bias mitigation. Recent applications include clinical decision support for polypharmacy management and legal document analysis. His publications demonstrate strong emphasis on: 1) Advancing evaluation methodologies for generative NLP systems, 2) Developing privacy-aware embedding techniques, and 3) Creating cross-domain NLP applications for healthcare and social good. Research consistently addresses real-world implementation challenges. Research Leadership: Principal Investigator for £6M+ grants including DynAIRx (NIHR: £4.2M) for AI in multi-morbidity management KTP grant with Fletchers Solicitors for legal AI systems EU-funded WEB-RADR project for pharmacovigilance Leads 30+ member research group spanning NLP, machine learning, and healthcare AI. Teaches graduate course COMP 527: Data Mining and Visualisation.
