Jian Liu is an Assistant Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. He leads the Mobile Sensing and Intelligence Security (MoSIS) Lab, focusing on robust AI, mobile security, computational sensing, and smart healthcare. His research has been published in top-tier venues like S&P/Oakland, CVPR, and IEEE journals, with over 6,400 citations. He holds seven U.S. patents, including two licensed to industry. Education: PhD in Electrical and Computer Engineering from Rutgers University (2019), ME and BE in Communication Engineering from Wuhan University of Technology (China). Research interests include trustworthy AI, federated learning, privacy-preserving technologies, and adversarial machine learning. His recent work includes HarmonyCloak (music copyright protection against generative AI), 3D facial authentication systems, and robust backdoor attack defenses. Notable awards include the University of Tennessee’s Professional Promise in Research Award (2025), Stanford’s World’s Top 2% Cited Scientists, and multiple best paper awards. He teaches Mobile and Embedded System Security (ECE 469/569) and has supervised projects funded by UT Grand Challenges grants. Labs/Teams: MoSIS Lab focuses on AI-driven security solutions, wearable sensing, and healthcare applications. Collaborations involve interdisciplinary projects with UT’s engineering and medical schools.
Felix Gomez Marmol is an Associate Professor at the University of Murcia's Faculty of Informatics, Department of Information and Communication Engineering. His research focuses on cybersecurity, artificial intelligence, network security, and IoT security. He holds a PhD in Computer Science from the University of Murcia (2010), supervised by Dr. Gregorio Martínez Pérez. Key research interests include adaptive intrusion detection systems, dark web analysis, and AI-driven cybersecurity frameworks. He leads the Intelligent Systems and Telematics research group and previously contributed to the Sistemas Inteligentes group. His work emphasizes practical applications such as the SCORPION Cyber Range platform for cybersecurity training and gamification. Recent projects involve detecting hate networks on social media, optimizing malware defense using transfer learning, and developing SIEM systems for IoT environments. His contributions span technical papers on cybersecurity education, ethical hacking fundamentals, and blockchain-based security solutions. Prof. Gomez Marmol has collaborated on initiatives like the COBRA framework for simulating advanced persistent threats (APTs) and the COnVIDa dashboard for pandemic-related data analysis. His research bridges theoretical advancements with real-world cybersecurity challenges.
Prof. Dr. Ahmet ÖZMEN is a Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Software Engineering. He has held various administrative positions including Head of the Software Engineering Department (2019-2028) and Director of the Computer Research and Application Center (2019-2022). With extensive experience in academia since 1991, he has made significant contributions to computer vision, traffic monitoring systems, and sensor technologies. Sakarya University: Professor (2019-present), Associate Professor (2011-2019) Dumlupınar University: Assistant Professor (2001-2011), Research Assistant (2000-2001, 1993-1998) Istanbul Technical University: Research Assistant (1991-1993) Prof. ÖZMEN's research spans computer vision applications for traffic monitoring, indoor air quality systems, parallel computing, and sensor technologies. His work bridges theoretical computer science with practical engineering applications, particularly in developing vision-based systems for nighttime vehicle detection, traffic flow monitoring, and environmental sensing. His interdisciplinary approach combines machine learning, image processing, and embedded systems to solve real-world problems in transportation and environmental monitoring. His publication record shows a clear evolution from parallel and distributed systems in his early career to computer vision and sensor applications in recent years. The majority of his recent work focuses on traffic monitoring systems using computer vision techniques, particularly for nighttime conditions, and indoor air quality monitoring systems using sensor networks. His research demonstrates strong industry and societal relevance, with applications in smart transportation, environmental protection, and educational technology. TÜBİTAK Publication Awards (2006, 2008, 2009, 2010) Physical implementation award from TÜBİDER (2008) Microsoft Certified Professional Certificate (2005) YÖK overseas study scholarships (1993, 1998) Elginkan graduate scholarships (1990, 1991) Prof. ÖZMEN has supervised numerous graduate students across multiple institutions, with a focus on practical engineering problems. His research has been supported by various projects including TÜBİTAK projects, institutional research grants, and industry collaborations. He has led significant research initiatives in traffic monitoring systems, indoor air quality monitoring, and educational technology platforms. His administrative leadership has included directing research centers and shaping curriculum development in software engineering. His work has involved establishing research teams focused on computer vision applications, sensor network development, and educational technology. These teams have produced numerous publications, developed practical systems, and trained the next generation of computer engineers. Current research directions include advanced traffic monitoring systems using deep learning and multi-camera setups for urban planning applications.
Tijay Chung is an Associate Professor at the College of Engineering , Virginia Tech , specializing in Internet Security and Internet Measurement . His work bridges theoretical and applied aspects of cybersecurity, focusing on secure communication protocols and infrastructure. Education Ph.D., Computer Science and Engineering, Seoul National University (2015) B.S., Computer Science and Engineering, Pohang University of Science and Technology (2009) Research Interests Chung's research centers on improving certificate revocation mechanisms, DNSSEC, and TLS security. He explores vulnerabilities in web encryption, develops decentralized cryptographic solutions, and analyzes internet governance protocols like BGP and RPKI. His work also extends to privacy in contact-tracing technologies and understanding content distribution dynamics in peer-to-peer systems. Recent publications highlight trends in : Enhancing TLS and DNSSEC operational security Decentralized cryptographic accumulators for revocation Longitudinal studies of PKI and certificate ecosystems Privacy guarantees in Bluetooth Low Energy (BLE) systems Advising No student names were explicitly listed in the provided materials.
Bing Yan is an Assistant Professor in the Department of Electrical and Microelectronic Engineering at Rochester Institute of Technology (RIT), affiliated with the Kate Gleason College of Engineering. She holds a B.S. in Information Management from Renmin University of China (2010), and M.S. and Ph.D. degrees in Electrical Engineering and Statistics from the University of Connecticut (2012–2017). Prior to RIT, she was an Assistant Research Professor at the University of Connecticut. Dr. Yan’s research focuses on power system optimization , including grid integration of renewables (wind/solar), microgrid operations, distributed energy systems, and manufacturing scheduling. She has published over 30 peer-reviewed articles and secured grants from the National Science Foundation (including a CAREER Award), Department of Energy, and industry partners like Brookhaven National Laboratory and ABB. Her work emphasizes mixed-integer linear programming and machine learning applications in energy systems. Notable contributions include stochastic unit commitment models for wind farms, voltage control via deep reinforcement learning, and multi-layer weather models for PV prediction. She advises on projects involving grid resilience, smart manufacturing, and data-driven optimization. Awards: National Science Foundation Faculty Early Career Development (CAREER) Award Multiple NSF grants, DOE grants, and industry contracts Teaching: Courses include Circuits I , Electric Power Transmission & Distribution , and Advanced Power Systems . She also mentors students through co-op programs and independent studies. Labs/Teams: Leads the Intelligent Lab of Power and Manufacturing (ILPM), focusing on multidisciplinary solutions for energy and manufacturing systems. The lab emphasizes hands-on training and innovation in smart grid technologies and sustainable energy systems.
Soteris Demetriou is a Senior Lecturer of Computer Systems Security at Imperial College London's Department of Computing, within the Faculty of Engineering. He leads the Applications, Platforms, and Systems Security (APSS) Research Lab and directs the Academic Centre of Excellence in Cyber Security Research (ACE-CSR). His research focuses on securing mobile, IoT, and cyber-physical systems through techniques like explainable AI, reverse engineering, and trusted computing. Notable contributions include tools for privacy preservation in machine learning models, detection of LiDAR spoofing attacks, and securing Android's middleware. Education: PhD and MSc in Computer Science (University of Illinois at Urbana-Champaign), Diploma in Electrical and Computer Engineering (University of Patras). Research Interests: Mobile/IoT security, AI security, trusted computing, and vulnerability analysis. Key areas include privacy in generative models, adversarial attacks on autonomous systems, and large-scale distributed systems. Publications: Over 50 peer-reviewed papers in top venues like NDSS, CCS, and SOSP. Recent work addresses privacy in speech generation, LiDAR security for autonomous vehicles, and hyperscale serverless architectures at Meta. Awards: Distinguished Paper Award at NDSS 2018, Best Paper at SafeThings 2024, and multiple travel grants. Served on technical committees for PETS, CCS, and AutoSec. Grants & Collaborations: SPRITE+ grant for Bio-IoT security, collaboration with Meta on distributed systems, and leadership in ACE-CSR. Labs: APSS Lab focuses on systems and AI security, with interdisciplinary projects in healthcare and autonomous systems.
Dr. Ben Swift is a Senior Lecturer at the School of Cybernetics, ANU, specializing in AI, computational art, and cybernetics. He leads the Cybernetic Studio, an interdisciplinary collective exploring cybernetic systems through hardware/software/people collaborations. As a livecoding artist, he performs globally and co-founded the ANU Laptop Ensemble. His research spans generative AI, open-source tools like Extempore, and UX design. Education: PhD in Computer Science (ANU) Projects: Australia's Digital Economy (2022), The Augmented Web (2019) Research focuses on AI creativity, biofeedback interfaces, and computational music. His work bridges technical innovation with artistic expression, evident in projects like TSPNet and adversarial camera systems. Key contributions include Extempore’s development and studies in live coding disruption. Awards unspecified but recognized internationally for interdisciplinary impact.
Dr. Yiran Chen is the John Cocke Distinguished Professor at Duke University's Department of Electrical and Computer Engineering, leading the NSF AI Institute for Edge Computing (Athena) and the Duke Center for Computational Evolutionary Intelligence (DCEI). A global leader in neuromorphic computing, emerging memory systems, and edge AI, he holds prestigious roles including IEEE Fellow and Editor-in-Chief of IEEE Transactions on Circuits and Systems for AI. His research spans machine learning accelerators, security-hardened hardware, and co-design of EDA tools with LLMs. With over 700 publications and 96 patents, he has been awarded 15 paper awards and 17 nominations, including rare Technical Achievement Awards from IEEE societies. He advises over 60 PhD students and 4 postdocs, many of whom hold academic positions worldwide. His work bridges academia and industry, contributing to startups and venture capital through his board roles. Education: B.S. (Tsinghua, 1998) → M.S. (Tsinghua, 2001) → Ph.D. (Purdue, 2005). Career path: Assistant/Associate Professor at University of Pittsburgh (2010–2014) → Duke since 2014. Awards include the ACM SIGDA Outstanding New Faculty Award (2014), NSF CAREER Award (2013), and the Stansell Family Distinguished Research Award (2022). Research focuses on innovations in: (1) Non-volatile memory architectures for AI acceleration, (2) Hardware-software co-design for edge computing, (3) Security in neuromorphic systems, and (4) Large-scale ML for EDA. His group pioneered ReRAM-based accelerators like ReBNN and MARC, and introduced novel edge AI frameworks like Ecco and Prosperity. These works address scalability, energy efficiency, and real-time performance challenges. Key initiatives include the NSF IUCRC for Alternative Sustainable & Intelligent Computing (ASIC), advancing sustainable computing through novel materials and architectures. His leadership in standard-setting bodies like the IEEE Circuits and Systems Society ensures cutting-edge research translates into industry practices. Grants: Lead PIs for multiple NSF AI Institutes and industry partnerships. Labs: Directs the Athena Institute and DCEI, fostering collaboration between academia and industry. Current projects include quantum computing placement algorithms (QPlacer), federated learning frameworks (FedGPT), and neuro-symbolic architectures.
Dr. Pradip Sharma is an Associate Professor of Cybersecurity & AI at the University of Aberdeen, UK, within the School of Natural and Computing Sciences, Department of Computing Science. He is a globally recognized academic and researcher with expertise in Cybersecurity, Artificial Intelligence, Blockchain, and Edge Computing. His research interests span multiple domains including Cybersecurity, Blockchain, Edge Computing, Software-defined Networking, and IoT Security. Dr. Sharma's work focuses on developing innovative solutions for security challenges in emerging technologies, with particular emphasis on privacy-aware AI systems, secure data sharing frameworks, and intelligent network security mechanisms. His interdisciplinary approach bridges theoretical foundations with practical implementations across healthcare, smart mobility, and consumer electronics domains. Senior Fellowship Advance HE (SFHEA) IEEE Senior Member (SMIEEE) Dr. Sharma actively supervises doctoral researchers and is accepting new PhD students in Computing Science. His funded research portfolio exceeds £1M from sources including EPSRC, Innovate UK, and international agencies. Current projects include 'Secure, Privacy-aware, and Trusted Data Share in Smart Mobility' (EPSRC, £200K), 'ZECURE Data Exchange Platform' (Innovate UK, £236K), and 'Quantum-resistant Cybersecurity' (Royal Embassy of Saudi Arabia, £73K). He also serves as an editor for leading journals and is a regular keynote speaker at international conferences.
Rui Duan is an Assistant Professor in the Department of Computer Science and Information Technology at the University of Missouri-Kansas City (UMKC), within the School of Science and Engineering. He leads the SAIM Lab (Secure AI & Intelligent Media), focusing on trustworthy and human-centered multimedia AI. Research Interests: His research lies at the intersection of AI Security, Machine Learning, and Human-Computer Interaction. He investigates adversarial audio attacks in real-world applications, their human impact, and mitigation strategies. His work extends to Network Security, Internet of Things (IoT), and Federated Learning, aiming to build robust and secure AI systems. Publication Trends: His recent publications demonstrate a strong focus on adversarial attacks in multimedia systems, particularly targeting audio and music copyright detection, speaker recognition, and federated learning frameworks. These works are published in top-tier venues like IEEE S&P, NDSS, ACM CCS, CVPR, and ICML, reflecting high impact in both security and machine learning domains. Scientific Awards: Student Travel Grant from IEEE S&P 2024 Student Travel Grant from ACM CCS 2022 Advising and Grants: Dr. Duan is actively recruiting self-motivated Ph.D. students interested in trustworthy ML & AI, IoT design, and human-computer interaction. While specific grants are not listed, his publication record and lab activities suggest active research funding, particularly in AI security and trustworthy systems. Labs and Teams: He leads the SAIM Lab (Secure AI & Intelligent Media) at UMKC, which focuses on developing secure and intelligent multimedia AI technologies. The lab is actively engaged in cutting-edge research on adversarial attacks, federated learning, and IoT security.
Onur Mutlu is a Professor of Computer Science at ETH Zurich, affiliated with the Department of Information Technology and Electrical Engineering. He also holds adjunct professorships at Carnegie Mellon University and Bilkent University. His research focuses on computer architecture, systems security, bioinformatics, and energy-efficient computing. He has pioneered work on memory-centric computing paradigms, RowHammer security vulnerabilities, and bio-inspired computing systems. He teaches courses such as Digital Design & Computer Architecture and supervises the SAFARI research group, which explores cutting-edge topics in memory systems, AI accelerators, and genomics. Recent activities include keynote talks at ISCA, HiPEAC, and IEEE conferences, emphasizing emerging hardware-software co-design principles. Key contributions include foundational work on memory reliability, cross-layer system design, and accelerating genomic data analysis. His research has been showcased in over 200 publications and industry collaborations with tech leaders like Intel, Huawei, and Micron.
Dr. Gowri Sankar Ramachandran is a Senior Lecturer in the School of Information Systems at Queensland University of Technology (QUT), specializing in cybersecurity and distributed systems. She holds a PhD from KU Leuven (Belgium) and a postdoctoral position at the University of Southern California (USC). Her research focuses on open-source software security, runtime threat detection, blockchain applications, and IoT vulnerabilities. Notable contributions include the FUSE tool for detecting malicious packages and the discovery of hyperlink hijacking vulnerabilities affecting millions of domains. Research interests span software supply chain security, metadata-based risk analysis, and generative AI for cyber risk modeling. Awards include Best Paper Awards at ACM CBSE (2016), Mobiquitous (2017), and BigMM (2019). Collaborations include projects with CSIRO, the City of Los Angeles, and the University of São Paulo. She teaches courses on cybersecurity, database management, and network security, and actively supervises PhD students in cybersecurity and blockchain domains. Recent publications address blockchain-based data governance, quantum-resilient IoT protocols, and decentralized identity systems. Her work bridges academic research with real-world impact, addressing critical challenges in digital systems security and privacy.
Wouter Lueks is a faculty member at the CISPA Helmholtz Center for Information Security in Saarbrücken, Germany. His research focuses on designing secure, practical, and privacy-friendly systems using applied cryptography, anonymous communication, and systems engineering. He leads a lab and actively mentors PhD and PostDoc researchers. Education: PhD in Computer Science (Radboud University, Netherlands), advised by Jaap-Henk Hoepman and Bart Jacobs. Postdoctoral Researcher at EPFL, Switzerland (SPRING Lab). Research Interests: Privacy-preserving systems for humanitarian aid and public health. Cryptography in decentralized networks and anonymous communication. Secure protocols for identity management and voting systems. Key Publications: Recent work includes privacy-preserving digital wallets for aid distribution (IEEE S&P 2025), biometric deduplication systems (IEEE S&P 2024), and decentralized proximity tracing protocols (Commun. ACM 2022). His research emphasizes practical applications of zero-knowledge proofs and attribute-based credentials. Awards: Distinguished Paper Award at IEEE S&P 2023. Runner-up Casper Bowden PET Award 2021 and CNIL-Inria Privacy Award 2021. Advising & Grants: Supervises PhD/PostDoc researchers and collaborates on projects funded by EU and industry grants. Active in open-source contributions, including the zksk library and Lightnion anonymous communication tool. Labs/Teams: Principal investigator at CISPA, collaborates with the SPRING Lab (EPFL) and leads interdisciplinary teams in privacy-enhancing technologies.
Yang Liu is an Assistant Professor in the Department of Electrical and Computer Engineering at the Baskin School of Engineering, University of California, Santa Cruz. Previously, they were affiliated with Harvard University and earned their PhD in 2015 from the Department of EECS at the University of Michigan, Ann Arbor. Their research lies at the intersection of machine learning, fairness, and trustworthy AI, with a strong focus on large language models, federated learning, and causal reasoning. Their research interests include: Machine Learning and Fairness Federated and Privacy-Preserving Learning Large Language Model Safety and Unlearning Causal Inference and Counterfactual Reasoning Anomaly Detection and Robust Forecasting Human-AI Interaction and Ethical AI Recent publications (2024–2025) demonstrate a strong trend in developing methods for machine unlearning, fairness in LLMs, and robustness under label noise and distribution shifts. Their work frequently appears in top-tier venues such as NeurIPS, ICLR, ICML, AAAI, and KDD, often in collaboration with researchers like Zhaowei Zhu, Mingyan Liu, Jiaheng Wei, and Kun Zhang. Themes include algorithmic fairness, model accountability, and human-aligned AI systems. Scientific contributions include: Frameworks for LLM unlearning and model editing Methods for fair classification and recourse Robust time series forecasting under anomalies Test-time adaptation in multimodal models Causal approaches to debiasing and policy learning While no formal advising list is provided, the depth and volume of collaborative work suggest active mentorship of graduate students and postdocs. Their research program is highly active, with numerous ongoing projects in trustworthy and socially responsible AI.
Arun Rai serves as Regents’ Professor and Howard S. Starks Distinguished Chair at Georgia State University's Robinson College of Business, where he co-founded and directs the Center for Digital Innovation. His career spans interdisciplinary research bridging information systems with societal impact through industry-university collaborations across global sectors. His educational foundation includes: Ph.D. from Kent State University MBA from Clarion University of Pennsylvania M.S. from Birla Institute of Technology & Science Rai's research explores digital innovation , AI governance , and societal impacts of technology through investigations of platform ecosystems, supply chain transformation, and digital solutions for poverty and health disparities. His work uniquely connects technical systems design with behavioral and organizational outcomes across contexts from rural India to global corporations. Recent publications (2023-2025) reveal intensifying focus on AI-human collaboration , digital risk assessment , and platform governance tensions , with growing emphasis on healthcare applications and equity implications. The trajectory shows evolution from organizational IT adoption toward complex sociotechnical systems addressing global challenges. His scientific recognition includes: Fellow of the Association for Information Systems Distinguished Fellow of the INFORMS Information Systems Society LEO Award for Lifetime Exceptional Achievement Rai has mentored over 60 doctoral students (30+ as chair) with alumni now holding leadership positions globally. His research attracts major funding from Apollo Hospitals, China Mobile, IBM, Intel, UPS, and federal agencies, enabling real-world implementations like the Global Supply Chain Solutions Program during UPS's digital transformation. Current initiatives focus on generative AI in education and healthcare IT policy impacts. As director of the Center for Digital Innovation, he cultivates cross-sector partnerships advancing digital transformation through collaborative research on AI governance, platform ecosystems, and societal impact measurement.
