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John ClarkView profile

Professor

• Cybersecurity
• Software Engineering
• Artificial Intelligence
• +5 more

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.

Matthew JensenView profile

Professor

• Computer-Aided Decision-Making
• Human-Computer Interaction
• Knowledge Management
• +6 more

Matthew L. Jensen is the W.P. Wood Presidential Professor of Management Information Systems at the University of Oklahoma's Price College of Business, where he also co-directs the Center for Applied Social Research. He holds a Ph.D. from the University of Arizona (2007). His research focuses on decision-making processes in mediated environments, with emphasis on online credibility assessment, cybersecurity training efficacy, and deception detection. He has secured over $9.7M in grants from NSF, Air Force Office of Scientific Research, and other agencies. Education: Ph.D., Management Information Systems, University of Arizona, 2007 Research explores how individuals evaluate information credibility in AI-driven interactions, phishing susceptibility mitigation through gamified training, and ideological messaging on extremist websites. His work appears in top journals like MIS Quarterly and Information Systems Research. Recent projects include developing AI tools for duplicate comment detection in regulatory processes and analyzing phishing vulnerability across industries. Key achievements include a $9.7M grant portfolio and leadership in interdisciplinary teams investigating digital deception and cybersecurity collective action. His training games have advanced bias mitigation strategies in both organizational and educational contexts.

Matt GarrattView profile

Professor

• Robotics
• Swarm Robotics
• Unmanned Aerial Vehicles
• +5 more

Professor Matt Garratt is a faculty member at the University of New South Wales (UNSW Canberra), School of Engineering and IT, serving as AI theme lead for the Defence Trailblazer Universities initiative with over $200 million in funding. His primary research focuses on sensing, guidance, and control for autonomous systems within robotics and unmanned aerial vehicles. Garratt's research spans robotics, swarm intelligence, and autonomous systems with emphasis on bio-inspired navigation techniques and adaptive flight control. His work addresses critical challenges including terrain following using vision systems, landing UAVs on moving platforms, and developing self-organizing swarms. He integrates artificial intelligence, computer vision, and machine learning to advance unmanned systems capabilities in complex environments. Analysis of his recent publications reveals strong trends in bio-inspired UAV navigation (particularly honeybee behavior modeling) and swarm robotics applications. His work increasingly incorporates deep learning for perception tasks while addressing real-world challenges like gas plume detection and adversarial robustness in 3D vision systems. The research demonstrates consistent progression toward practical implementation of autonomous systems in dynamic environments. Professor Garratt has secured over $7.7 million in external research funding as Chief Investigator on 33 grants. He actively mentors graduate students with scholarships available for Masters and PhD research in robotics and AI, focusing on: UAV path planning and adaptive control systems Swarm robotics collective motion optimization Bio-inspired autonomous navigation techniques Computer vision for robotic perception He co-founded the UNSW Canberra AIR (AI and Robotics) Group (AIR Lab), which drives research in trusted autonomy, swarm intelligence, and AI integration for defense applications. The lab develops practical solutions for autonomous systems operating in complex, real-world environments while maintaining ethical AI frameworks.

• AI-enabled communications
• Green and energy-efficient communications
• Online optimization and machine learning
• +6 more

E. Veronica Belmega is a Full Professor at ESIEE Paris (Université Gustave Eiffel) and a researcher at the LIGM laboratory in Marne-la-Vallée, France. Previously, she served as an Associate Professor at ENSEA graduate school and Deputy Director of the ETIS laboratory in Cergy. She holds an Engineer Degree from the University Politehnica of Bucharest, M.Sc. and Ph.D. from Université Paris-Sud 11, and an HDR habilitation from Université de Cergy-Pontoise. Her research focuses on AI-driven communication systems, energy efficiency, online optimization, and cyber-physical security, with a strong emphasis on applications in smart grids and IoT. Her work spans securing wireless communications against adversarial attacks, optimizing resource allocation in cognitive radio networks, and leveraging machine learning for GNSS localization and MIMO systems. Notable contributions include game-theoretic frameworks for PMU deployment and energy-efficient NOMA systems. Belmega has received prestigious awards such as the 2021 CY Alliance Award and the L’Oréal-UNESCO fellowship, and serves as an Area Editor for IEEE Trans. on Machine Learning in Communications and Networking. Current projects include a CEA LETI postdoc position on AI localization and a PEPR 5G project. She actively contributes to special issues like the EURASIP JASP on sustainable wireless communications. Belmega’s advising includes PhD student S. Maleki, co-author of her 2024 IEEE SmartGridComm Best Paper Award-winning work.

Rohan TabishView profile

Assistant Professor

• Real-Time Systems
• Embedded Systems
• Multicore Processors
• +5 more

Rohan Tabish is an Assistant Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC), specializing in real-time systems, embedded systems, and cybersecurity. His work focuses on developing predictable and secure software frameworks for multi-core and heterogeneous architectures. Education: Ph.D. in Computer Science and Engineering Master's in Computer Science and Engineering B.Sc. in Electrical Engineering with Telecommunications specialization Research Interests: Real-Time Task Scheduling Fault Tolerance in Embedded Systems Inter-Core Communication Frameworks Memory Bandwidth Management Cyber-Physical Systems Scratchpad-Centric Operating Systems Awards: Outstanding Paper & Best Paper Award (RTSS 2020) Outstanding Paper & Best Student Paper Award (RTSS 2020) Best Presentation Award (RTAS 2016) Nominated for Best Paper Award (ECRTS 2019) Teaching: CS 431: Embedded Systems (Instructor, 2015-2018) CS 424: Real-Time Systems (Instructor, 2019) CS 438: Communication Networks (TA, 2019) Labs/Teams: Active member of the Real-Time Systems Lab (RTSL) at UIUC, focusing on safety-critical embedded systems and real-time software frameworks.

Fenglong MaView profile

Associate Professor

• Data Mining
• Health Care Informatics
• Machine Learning
• +5 more

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.

Charles GillanView profile

Senior Lecturer

• High Performance Computing (HPC)
• Artificial Intelligence (AI) in Healthcare
• Quantum Computing
• +4 more

Charles Gillan is a Senior Lecturer at Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science, affiliated with the High Performance and Distributed Computing department and the Institute of Electronics, Communications & Information Technology. His research bridges HPC systems, AI applications in healthcare, and computational physics. Key projects include managing ICU patient care via neural networks, exascale-ready mathematical packages, and edge computing architectures. Research interests focus on high-performance computing (HPC), quantum computing, real-time data analytics, and electron-molecule scattering simulations. Notable contributions include developing microserver architectures for edge analytics and advancing AI-driven clinical decision support systems. Gillan has collaborated on interdisciplinary projects like food authenticity testing using spectroscopy and improving ventilator management in intensive care units. Publications span AI in healthcare, HPC system design, and computational methods for physics problems. He has secured funding for initiatives such as the KTP partnership with Foods Connected Ltd and the HANDHELD olfactory detection project. Gillan's work emphasizes practical applications of advanced computing across healthcare, engineering, and cybersecurity domains.

Mitchell L. NeilsenView profile

Professor

• Cyber-Physical Systems
• Distributed Systems
• Scientific Computing
• +7 more

Mitchell L. Neilsen is a Professor in the Department of Computer Science at Kansas State University's College of Engineering, where he also serves as the graduate program director. He holds the Warren and Gisela Kennedy - Carl and Mary Ice Keystone Research Scholar position and maintains an active research program with multiple ongoing projects. His educational background includes a Ph.D. in Computer Science (1992), M.S. in Computer Science (1989), and M.S. in Mathematics (1987), all from Kansas State University, plus a B.S. in Mathematics Education from the University of Nebraska-Kearney (1982). After beginning his career as an assistant professor at Oklahoma State University, he returned to K-State in 1996. Research Interests: Cyber-Physical Systems: Design, Analysis, Verification of systems integrating computing, networking, and physical processes Distributed Systems: Algorithms, design, and analysis of distributed computing systems Scientific Computing: Computational Fluid Dynamics, Finite Element Analysis, High Performance Computing, and Simulation Application Areas: Agriculture technology, Dam safety analysis, Mobile applications, Natural resources management, and Real-time Embedded Systems His research program shows clear evolution toward agricultural technology applications, particularly high-throughput phenotyping, while maintaining strong foundations in cyber-physical systems and scientific computing. Recent publications indicate increasing integration of machine learning and computer vision techniques into traditional research areas. Research Funding: National Science Foundation U.S. Department of Agriculture Sandia National Laboratories Department of Homeland Security Private industry partners Dr. Neilsen has mentored numerous graduate students through their M.S. and Ph.D. programs, with recent advisees focusing on applications in agricultural technology, dam safety, and embedded systems. His advising approach emphasizes practical applications of theoretical computer science concepts. Current Teaching (Fall 2024): CIS 450 - Computer Architecture and Operations CIS 625 - Concurrent Software Systems CIS 720 - Advanced Operating Systems

Latifur KhanView profile

Professor

• Data Mining
• Cybersecurity
• Machine Learning
• +2 more

Dr. Latifur Khan is a Professor in the Department of Computer Science at the University of Texas at Dallas' Erik Jonsson School of Engineering and Computer Science. He directs the Database and Data Mining Laboratory and conducts research in data mining, cybersecurity, and semantic web technologies. Research domains include: Large language models for threat detection Fairness in machine learning Vulnerability analysis in software systems Graph-based information retrieval Recent publications focus on AI security applications in transportation systems, political conflict analysis using NLP, and federated learning for IoT security. His work consistently bridges theoretical algorithms with practical cybersecurity implementations. Research grants include funding from NSF, NASA, Raytheon, Nokia, and SUN Microsystems. Teaching includes courses in Plant Breeding (PBG 450/550) and Breeding Clonal Crops (PBG 551).

W. Eric WongView profile

Professor

• Software Engineering
• Software Testing
• Software Reliability
• +6 more

W. Eric Wong is a Professor of Computer Science at The University of Texas at Dallas (UTD), affiliated with the Erik Jonsson School of Engineering and Computer Science. He holds a Ph.D. in Computer Science from Purdue University (1993), following earlier degrees from Purdue and Eastern Michigan University. His research focuses on reducing software production costs while enhancing reliability, safety, and quality through program-based and architecture/design-based testing methodologies. Key areas include automated test generation, fault localization, debugging, and software safety analysis. Professional Background: Tenured Professor at UTD since 2002 Prior roles include Senior Scientist at Telcordia Technologies (1995–2002) and Consultant at Texas Instruments (2004–2005) Active in industry partnerships, such as projects with Motorola, Avaya Labs, and Raytheon Research Interests: Software Testing & Debugging Dependable Software Development Security Requirements Engineering Fault Localization Techniques Model-Based Testing Software Reliability Modeling Awards & Recognition: 2007 IEEE COMPSAC Best Paper Award 1997 NASA Quality Assurance Special Achievement Award Recipient of a $404,772 NSF grant for software safety and reliability research (2021) Professional Activities: Editorial roles for journals like Journal of Systems and Software and International Journal of Software Engineering Program Chair for ISSRE 2012, COMPSAC 2010, and multiple ACM SAC conferences Member of IEEE Reliability Society Administrative Committee (2008–2013) IBM System z Curriculum Advisory Panel member Labs & Teams: Leads the Software Engineering Group at UTD, collaborating on projects like eXVanatge (dependable software solutions) and Fault-Prone Module Identification in telecommunications systems. Engages in cross-disciplinary efforts with industry and international institutions.

Houssam AbbasView profile

Assistant Professor

• Computational Ethics
• Artificial Intelligence
• Cyber-Physical Systems
• +3 more

Houssam Abbas is an Assistant Professor in the School of Electrical Engineering and Computer Science at Oregon State University. He holds a Ph.D. in Electrical Engineering from Arizona State University and has professional experience in SoC verification at Intel and postdoctoral research at the University of Pennsylvania. His work focuses on computational ethics for AI agents, design/verification of cyber-physical systems, and autonomous systems like self-driving cars and drones. Education: Ph.D., Electrical Engineering, Arizona State University (2015) M.Sc., Electrical Engineering, Arizona State University (2006) B.Eng., Computer and Communications Engineering, American University of Beirut (2004) Abbas' research integrates deontic logic for ethical obligations in AI, distributed verification techniques for autonomous systems, and fair control algorithms for aerial missions. He co-leads the F1/10 autonomous racing initiative and teaches hands-on courses on self-driving cars. Awards: 2022 NSF CAREER Award 2022 Grainger Foundation Frontiers of Engineering Symposium Participant Grants & Projects: NSF CCRI Grant for F1/10 Racecar platforms (with Penn and Clemson) FAA ASSURE project on UAV cybersecurity Lab/Teams: His work involves the Autonomous Systems Lab , focusing on ethical AI, robotics, and formal verification tools like the F1/10 platform.

Kevin W. HamlenView profile

Professor

• Cybersecurity
• Software Security
• Formal Methods
• +6 more

Kevin W. Hamlen is the Louis A. Beecherl, Jr. Distinguished Professor in the Department of Computer Science at the University of Texas at Dallas. He serves as Executive Director of UT Dallas' Cyber Security Research and Education Institute. His research focuses on language-based security , binary software hardening , cyberdeception , and formal program verification . He has received multiple grants from agencies like AFOSR, NSF, DARPA, and industry partners including Lockheed Martin and Intel. PhD and MS from Cornell University BS from Carnegie Mellon University His research explores automated approaches to software security through techniques like binary disassembly , control-flow integrity , and honey-patching . He has pioneered methods for malware defense and cloud/web/mobile security . Recent work examines adaptive cyberdeception and GPU-based security frameworks . His publications span binary code manipulation , malware mitigation , and blockchain security . Key awards include the NSF IUCRC Technology Breakthrough Award and two CSAW Best Paper 2nd Prizes . He advises numerous PhD students, many of whom now work at Google, IBM, and Microsoft. His book Autonomous Cyber Deception (Springer, 2019) with Ehab Al-Shaer and Cliff Wang provides comprehensive coverage of adaptive cyberdeception strategies.

Asta ZelenkauskaiteView profile

Professor

• Social Media Research
• User-Generated Content Analysis
• Emergent Practices Online
• +3 more

Asta Zelenkauskaite is a Professor of Communication and Graduate Faculty Member in the Department of Communication at Drexel University. She is affiliated with the Center for Science, Technology, and Society. Her research focuses on social media dynamics, misinformation, and digital communication practices, employing mixed-methods approaches to analyze emergent online behaviors. She holds a PhD in Mass Communication from Indiana University (2012). Education: PhD in Mass Communication, Indiana University, 2012 Research Interests: Social media research and user-generated content analysis Emergent online practices and ideological influence Disinformation, inauthentic behaviors, and post-truth challenges Macro- and micro-level studies of digital media landscapes Recent Work Trends: Dr. Zelenkauskaite’s recent publications emphasize AI’s role in content analysis, disinformation mitigation strategies, and cross-cultural climate change narratives. Her work bridges social science, information science, and linguistics to address societal challenges like vaccine hesitancy and digital misinformation. Awards/Grants: No specific awards listed, but her research has been supported by interdisciplinary grants focusing on AI ethics and digital media governance. Labs/Teams: Active in Drexel’s Center for Science, Technology, and Society, collaborating on projects addressing technology’s societal impacts. Her work often involves international partnerships, particularly in Eastern European contexts like Lithuania.

Mohamed IbnkahlaView profile

Professor

• Wireless Sensor Networks
• Internet of Things (IoT)
• Cognitive Radio Networks
• +5 more

Dr. Mohamed Ibnkahla is a Full Professor and NSERC/Cisco Senior Industrial Research Chair in Sensor Networks for the Internet of Things (IoT) at Carleton University's Department of Systems and Computer Engineering. He holds a Ph.D. and HDR from the National Polytechnic Institute of Toulouse (INP), France. His research focuses on IoT, wireless sensor networks, cognitive radio systems, and adaptive signal processing, with applications in smart cities, healthcare, energy, and transportation. He has led numerous industry and government-funded projects, including the Carleton-Cisco IoT Testbed. Education: Ph.D. and HDR (INP Toulouse, 1996/1998), Engineering and MSc in Electronics/Signal Processing (INP Toulouse, 1992). He previously served at Queen’s University (2000–2015) and INP Toulouse (1996–1999). Research Interests: IoT security, energy harvesting, cognitive radio networks, smart grid communication, and machine learning for wireless systems. His work spans theoretical contributions (e.g., 5 books on signal processing and IoT) and applied innovations (e.g., sensor network architectures for environmental monitoring). He has published over 150 peer-reviewed papers, 4 books, and supervised ~40 graduate students. Awards include the INP Leopold Escande Medal (1997) and Ontario’s Prime Minister’s Research Excellence Award (2000). His lab develops solutions for IoT trust management, edge computing, and decentralized access control using blockchain. Key Projects: Cisco-funded IoT sensor networks for smart cities, NSF-funded cognitive radio projects, and collaborations on eHealth systems. His research addresses IoT security challenges in healthcare, transportation, and energy grids, emphasizing scalable, energy-efficient solutions.

Girija ChettyView profile

Professor

• Multimodal Systems
• Medical Image Computing
• Computer Vision
• +7 more

Girija Chetty is a Full Professor in Computing and Information Technology at the University of Canberra's School of Information Technology and Systems. She holds a PhD in Information Sciences and Engineering and has over 35 years of experience in academia and research leadership roles, including Head of Software Engineering and Program Director of ITS courses. Her research focuses on multimodal systems, medical image computing, AI, and data science. She leads a dynamic research group comprising PhD students, postdocs, and international collaborators. Education: PhD in Information Sciences (Australia, 2007), MSc and BSc in Electrical Engineering/Computer Science (India). She has held visiting roles at Deakin University and CSIRO. Research interests span computer vision, pattern recognition, and medical diagnostics, with 200+ publications in top journals/conferences. Her work addresses global challenges via AI-driven solutions in healthcare (e.g., pain assessment systems, malaria diagnostics) and sustainability (SDG impact frameworks). Projects include AI for remote ultrasound imaging and smart farming systems. She actively collaborates with industry and global research institutions. Grants/Projects: 12 funded initiatives including AI for extreme environment healthcare, malaria pathogen detection, and big data-driven population health. Awards: Senior IEEE/Australian Computer Society membership, editorial roles in IEEE/Elsevier journals. Labs/Teams: Leads a multidisciplinary research group focused on medical AI and multimodal systems.