Find Academic Supervisors

• Optimization
• Cryptography
• Artificial Intelligence
• +5 more

Yu Li is a Lecturer at the University of Picardie Jules Verne (UPJV) and a member of research unit UR 4290 “Optimization and Cryptography, AI – OCIA.” His office is located in room 302, reachable by internal telephone extension 5900. Research Interests Dr. Li’s research spans several inter-related domains: Optimization & Control Theory – developing dynamic optimization algorithms for industrial processes such as continuous casting in steel manufacturing. Cryptography & Security – investigating secure and dependable models for cloud and distributed systems. Artificial Intelligence & Robotics – integrating AI perception and decision-making into cloud-connected robotic platforms, including exoskeletons for rehabilitation and autonomous ground vehicles. Cloud & Fog Computing – designing middleware and domain-specific languages that seamlessly connect robotic devices with cloud and edge resources. Publication Trends Over the past decade, Dr. Li’s publication record reveals a clear evolution from foundational work in software architecture and component-based systems (2010-2016) toward cutting-edge applications in cloud/fog-enabled robotics and AI-driven cyber-physical systems (2017-2023). His studies increasingly emphasize real-world deployment, simulation-driven resource estimation, and human-centric interaction in rehabilitation robotics. Scientific Awards & Recognition No specific awards are listed in the provided materials. Advising & Funding No explicit information about supervised students or funded grants is available in the text supplied. Laboratories & Teams He carries out his research within the UR 4290 research unit “Optimization and Cryptography, AI – OCIA” at UPJV, focusing on collaborative projects that bridge mathematics, computer science, and robotics engineering.

• Fuzzy Systems
• Control Theory
• Neural Networks
• +5 more

Leszek Rutkowski is a Professor at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków, Poland. His primary research focuses on fuzzy systems, control theory, and optimization with significant applications in algorithmic trading and pattern formation dynamics. His research program centers on developing advanced fuzzy control frameworks for complex systems, particularly addressing security challenges in networked environments and optimizing financial trading strategies under uncertainty. Key contributions include novel approaches to Turing pattern control in reaction-diffusion systems, reinforcement learning for multi-agent consensus, and volatility-dependent Forex trading models using multi-criteria optimization. His work consistently bridges theoretical control mechanisms with practical implementations in stochastic and constrained environments. Analysis of his recent publications (2021-2025) reveals three dominant research thrusts: (1) Security-oriented fuzzy control for cyber-physical systems under DoS attacks, (2) Bifurcation analysis and pattern dynamics in fractional-order neural networks, and (3) Interpretable algorithmic trading systems leveraging belief-plausibility uncertainty models. His publications demonstrate increasing integration of reinforcement learning with traditional control theory, particularly in multi-agent coordination problems. Scientific awards: No awards were documented in the provided information sources. Advising and grants: No doctoral students or research grants were explicitly listed in the available materials. Laboratories and teams: Research appears to be conducted within the Institute of Computer Science framework, though specific laboratory names or team structures were not mentioned in the sources.

• Wireless Communications
• Mathematics
• Artificial Intelligence
• +5 more

Keivan Navaie is a Professor of Intelligent Networks at Lancaster University’s School of Computing and Communications. He serves as a member of the Independent Scientific Advisory Committee at the Alan Turing Institute, overseeing the £100 million BridgeAI programme, and previously as Principal AI Technology Advisor to the UK Information Commissioner’s Office (ICO). He is recognized with Fellowships from the Institution of Engineering and Technology (IET), Chartered Engineer status in the UK, Senior Fellowship of the Higher Education Academy (HEA), and the IEEE Young Investigator Award. Research Focus: Wireless communications, mathematics, artificial intelligence, 6G networks, blockchain technology, edge computing, cognitive radio networks, and non-orthogonal multiple access (NOMA). Supervision: Actively supervises PhD students in areas like wireless communications and mathematical modeling. Projects: Involved in distributed learning, blockchain integration, 6G research, and spectrum sharing systems. Awards: IEEE Young Investigator Award, Fellow of IET, Chartered Engineer, Senior Fellow of HEA.

Jason JaskolkaView profile

Associate Professor

• Cyber Security Evaluation
• Security Assurance
• Formal Methods
• +4 more

Jason Jaskolka is an Associate Professor in the Department of Systems and Computer Engineering at Carleton University, part of the Faculty of Engineering and Design. He holds a Ph.D. from McMaster University and is a licensed Professional Engineer in Ontario. His research focuses on cyber security evaluation and assurance, formal methods, and secure software engineering. He leads the Cyber Security Evaluation and Assurance (CyberSEA) Lab, emphasizing security-by-design principles for complex systems like industrial control systems and IoT-enabled healthcare. Education: Ph.D. (Software Engineering, McMaster University, 2015), M.A.Sc. (Software Engineering, McMaster University, 2010), B.Eng. (Software Engineering and Game Design, McMaster University, 2009). Research interests include: Cyber Security Evaluation & Assurance, Data-Driven Security Metrics, Formal Verification of Security Properties, Secure Software Architecture Design, and Industrial Cyber-Physical Systems Security. His work addresses challenges in threat modeling, compliance with security standards, and mitigating implicit system vulnerabilities. Recognition includes the 2021 New Faculty Excellence in Teaching Award for innovative pedagogy. He actively supervises graduate students in funded research positions. Key collaborations include Health Canada's Scientific Advisory Committee on Digital Health Technologies and the U.S. Department of Homeland Security’s Cybersecurity Postdoctoral Fellowship at Stanford University. Labs/Teams: CyberSEA Lab, focusing on developing rigorous security evaluation frameworks and tools for software-dependent systems.

Claire IngramView profile

Lecturer

• Software-driven technology innovation
• Design and new product development in creative sector
• Cyber-physical systems
• +4 more

Claire Ingram is a Lecturer (Teaching and Scholarship) in the Department of Computer Science at the University of York, where she serves as Deputy Undergraduate Admissions Tutor. She works at DC Labs in York, focusing on innovation and R&D practices in the creative sector, the role of the creative sector in regional innovation systems, and whole systems viewpoints that consider holistic environments. Dr. Ingram holds a PhD in empirical techniques examining early stage software engineering design from Newcastle University. Her academic background combines Computer Science with extensive experience in both academic research and commercial applications, specializing in software and system design. Her research spans software-driven technology innovation in multi-disciplinary fields, with current work focused on design and new product development in the creative sector. Previously, she studied design in cyber-physical systems. She has extensive experience with systems of systems engineering, having worked on EU-funded projects including COMPASS and Road2CPS, where she evaluated new systems engineering methods and contributed to strategic research agendas for Cyber-Physical Systems in Europe. Her 15 most recent publications demonstrate a consistent focus on systems engineering, particularly systems of systems architecture, fault modeling, and innovation practices. Her work spans from foundational software engineering metrics to applied research in cyber-physical systems and creative sector innovation. Dr. Ingram is an active member of the International Council of Systems Engineering (INCOSE) and contributes to INCOSE's Systems of Systems Working Group, demonstrating her commitment to advancing systems engineering practices internationally. Her professional activities include collaborative projects developing tools and methods for developers and engineers to cooperate in early design stages of cyber-physical systems, as well as exploring how software practitioners use informal local meetups to share knowledge. She has extensive experience with international research collaborations across multiple sectors. She maintains active research laboratories and teams through her work at DC Labs, where she investigates the intersection of technology innovation, creative industries, and systems engineering approaches.

Konstantinos KyriakopoulosView profile

Senior Lecturer

• Cybersecurity
• Artificial Intelligence
• Machine Learning
• +4 more

Dr. Konstantinos Kyriakopoulos is a Senior Lecturer in Cyber Intelligence, specializing in cybersecurity challenges and AI-driven solutions for converged Information and Operational Technology infrastructures. His work integrates machine learning with cyber-physical systems to enhance decision-making under uncertainty, with a focus on resilient AI algorithms and autonomous defense mechanisms. He has contributed to projects funded by Dstl, Innovate UK, and industry partners, addressing Industry 4.0 security, smart vehicles, electromagnetic attacks, and smart buildings. His research interests include adversarial machine learning, evidence theory for uncertainty modeling in ML, and autonomous cyber defense systems. He has developed novel approaches using reinforcement learning, hidden Markov models, and Bayesian optimization. His work emphasizes creating ML algorithms resistant to adversarial attacks while improving cybersecurity resilience in dynamic environments. Dr. Kyriakopoulos has also explored applications of AI in educational technology, such as automated assessment of spoken English proficiency. His recent publications focus on federated learning security, causal reinforcement learning, and anomaly detection techniques. He has experience in translating research into practical solutions, including business model pitches to investors in Canary Wharf for threat modeling tools. His contributions span over 40 peer-reviewed articles, with notable work in network intrusion detection, attack prediction via HMMs, and wavelet-based compression for network measurements. His expertise bridges academia and industry, addressing both theoretical advancements and real-world implementation challenges.

António CasimiroView profile

Associate Professor

• Dependable adaptive systems
• Middleware for distributed embedded real-time systems
• Cyber-Physical Systems
• +4 more

António Casimiro is an Associate Professor at the Department of Informatics of the Faculty of Sciences, University of Lisbon. He holds a PhD in Computer Science (2003) from the same institution. His research focuses on dependable adaptive systems, middleware for distributed real-time applications, and cyber-physical systems. He leads the Cyber-Physical Systems research line at the LASIGE research unit and coordinates EU projects like ADMORPH and VEDLIoT, as well as the national AQUAMON project for water monitoring. Education: PhD in Computer Science, University of Lisbon (2003) Research Interests: Middleware for embedded real-time systems Fault-tolerant distributed systems IoT and environmental monitoring Cybersecurity in autonomous systems Key Projects: KARYON (FP7): Safe cooperative automotive/avionics systems VEDLIoT (H2020): Accelerated AIoT systems AQUAMON: Wireless sensor networks for water monitoring Awards: None explicitly listed, but active in editorial roles like Editor-in-Chief of the Ada User Journal. Teaching & Leadership: Coordinates the Master in Information Security program Former Vice-Director of LASIGE and member of Faculty Scientific Council Labs/Teams: LASIGE research unit, Navigators group, involvement in GULLIVER testbed for vehicular systems.

Michele AlbanoView profile

Associate Professor

• Internet of Things (IoT)
• Energy Engineering
• Quality of Service (QoS)
• +5 more

Affiliations & Roles Michele Albano is an Associate Professor at the Department of Computer Science, Aalborg University, Denmark. He is affiliated with The Technical Faculty of IT and Design, focusing on research in IoT, Cyber-Physical Systems, and Edge Computing. He leads the Productive4.0 project (2017–2020), funded by Horizon Europe, addressing Industry 4.0 challenges in product lifecycle management. His work integrates formal verification tools like Uppaal with real-world applications in robotics, energy systems, and blockchain-based platforms. Research Interests Albano's research spans IoT architecture optimization , energy-efficient systems , and model-driven engineering . He develops tools for autonomous exploration algorithms (MAES), edge-cloud resource orchestration, and fault-tolerant computation offloading. His work bridges theoretical models (e.g., Uppaal SMC) with practical implementations in smart grids and robotic systems. Recent projects include blockchain-based crowdsourcing for machine learning and energy-aware thermal dynamics estimation in buildings. Collaborations & Impact He collaborates with the European Industry 6.0 community, contributing to the Arrowhead Framework for interoperable IoT systems. His research outputs include 112 publications, with 2025 highlights in human-inspired robotics and cognitive cloud frameworks. Media coverage in 2024–2025 highlights his work on green IT and secure API generation. Albano advises students on system modeling (e.g., ACSmt plugin development) and edge computing optimization. Labs & Teams His research group focuses on Cyber-Physical Systems and Smart Grids , with contributions to tools like RoutesMobilityModel and FlexHousing. He actively participates in workshops on New Trends in Software Architecture (SATrends '24) and IEEE conferences on Industrial Informatics.

• Security and Reliability of VR/AR Systems
• Internet of Things and Mobile Sensing
• Blockchain and Distributed Systems
• +7 more

Dr. Henry Hong-Ning Dai is an Associate Professor in the Department of Computer Science at the Faculty of Science, Hong Kong Baptist University (HKBU). He previously held academic positions at Lingnan University and Macau University of Science and Technology, where he advanced from Assistant to Associate Professor. He holds a Ph.D. from the Chinese University of Hong Kong and a D.Eng. from Shanghai Jiao Tong University. Education: Ph.D. in Computer Science and Engineering, Chinese University of Hong Kong (2008) D.Eng. in Computer Technology Application, Shanghai Jiao Tong University (2012) M.Eng. in Computer Science and Engineering, South China University of Technology (2003) B.Eng. in Computer Science and Engineering, South China University of Technology (2000) Dr. Dai's research focuses on security and reliability of VR/AR systems , Internet of Things , blockchain and distributed systems , federated learning , and cyber-physical systems . His work integrates AI, networking, and software engineering to address real-world security and performance challenges in emerging technologies. He has published over 300 papers in top journals and conferences such as IEEE JSAC, TMC, ICSE, INFOCOM, and AAAI, accumulating more than 24,000 citations. The 15 most recent publications (2023–2025) highlight his leadership in VR/AR security (e.g., AcouListener, Meta VR study), blockchain scalability and fairness (e.g., Porygon, Auncel, Justitia), federated and robust learning (e.g., EBS-CFL, FedDP), and edge-AI and wireless security (e.g., HARBOR, Smart Shield). His recent work also explores AI-generated art evaluation and LLM-driven manufacturing systems , showcasing interdisciplinary innovation. Scientific Awards and Recognition: Holder of 1 U.S. patent and 1 Australia innovation patent Winner of more than 17 awards Senior Member of ACM, IEEE, and EAI Dr. Dai has been Principal or Co-Investigator on over 12 research projects totaling HK$16 million, funded by UGC, NSFC, FDCT, and HKBU. He serves as an Associate Editor for IEEE Communications Surveys & Tutorials , IEEE Transactions on Intelligent Transportation Systems , and several other IEEE journals. He has chaired program committees and served on the PC of top conferences including ICSE, KDD, and INFOCOM. He is actively recruiting Ph.D. students and RAs in security, blockchain, and AI. Laboratories and Research Teams: While not explicitly named, Dr. Dai leads a research group focused on secure and intelligent distributed systems, with active projects in blockchain, VR security, and edge AI. His team has developed open-source tools such as VR-SP Detector , PrettySmart , and RLF for smart contract analysis and security assessment.

Ashraf TantawyView profile

Senior Lecturer

• Cyber Physical Systems
• Artificial Intelligence
• Cyber Security
• +7 more

Dr. Ashraf Tantawy is a Senior Lecturer in the School of Computer Science and Informatics at De Montfort University (DMU), UK. He holds a PhD and MSc in Electrical Engineering from Vanderbilt University, USA, and has previously served as an Assistant Professor at Virginia Commonwealth University (VCU). His industrial experience includes roles at British Petroleum, Qatar Gas, and Schneider Electric, focusing on embedded and safety-critical systems. He is affiliated with the Cyber Technology Institute (CTI) and the Institute of Artificial Intelligence (IAI) at DMU. Education: Ph.D. in Electrical Engineering, Vanderbilt University, USA M.Sc. in Electrical Engineering, Vanderbilt University, USA Engineering Management, University of Manchester, UK, 2015 Dr. Tantawy's research lies at the intersection of Cyber Physical Systems (CPS), Artificial Intelligence, Cyber Security, and Data Science. His work emphasizes the development of AI-driven methods for securing CPS, including reinforcement learning for autonomous systems, safety-security co-design, and decision-making under uncertainty. Application domains include autonomous vehicles, drones, smart cities, and industrial automation. He teaches courses such as Embedded Systems, Cyber Physical Systems, AI for Cyber Security, and Industrial Automation. His recent publications demonstrate a strong focus on model-based and data-driven approaches to CPS security, attacker modeling, intrusion detection, and risk assessment. The research spans both defensive and offensive security strategies, with increasing emphasis on machine learning and adaptive control in complex systems. Scientific Awards and Certifications: Safety Instrumented Systems (SIS) Expert, International Society of Automation (ISA), 2015 Dr. Tantawy has secured and contributed to multiple externally funded research grants totaling over $1.5 million. As Principal Investigator (PI) and Co-Investigator (CO-PI), he has worked on projects funded by NASA, Commonwealth Cyber Initiative (CCI), Virginia Catalyst, and Commonwealth Center for Advanced Manufacturing (CCAM). His research leadership includes projects on adversarial attack detection in connected vehicles, smart city testbeds, renewable energy systems, and smart manufacturing. He is an active member of the IEEE and ISA, contributing to both academic and industrial advancements in secure and dependable systems. He is involved with the Cyber Technology Institute (CTI) and the Institute of Artificial Intelligence (IAI) at DMU, contributing to interdisciplinary research in cyber security and intelligent systems. These labs support projects in AI-driven security, autonomous systems, and industrial IoT, fostering collaboration across academia and industry.

Feras BatarsehView profile

Associate Professor

• AI Assurance
• Cyberbiosecurity
• Intelligent Water Systems
• +4 more

Feras Batarseh serves as an Associate Professor in the Department of Biological Systems Engineering at Virginia Tech, where he directs the Artificial Intelligence Assurance and Applications Lab (A 3 Lab) at the Virginia Tech Research Center in Arlington. His work bridges artificial intelligence, cyberbiosecurity, and critical infrastructure systems with a focus on water and agricultural applications. His educational background includes: JM in Law from George Mason University (2022) Postgraduate Certificate in Project Leadership from Cornell University (2016) Ph.D. in Computer Engineering from the University of Central Florida (2011) M.Sc. in Computer Engineering from the University of Central Florida (2007) Dr. Batarseh's research centers on AI Assurance —developing frameworks for trustworthy, explainable, and ethical AI systems—applied to Cyberbiosecurity challenges in water infrastructure and Smart Agriculture . His work tackles data bias, dark data, and causality in real-world deployments, with applications in securing water supply systems, optimizing precision farming, and analyzing international agricultural trade. Key innovations include context-aware deep learning for wastewater treatment and causal AI for policy impact assessment. His recent publications (2023-2025) reveal a concentrated effort to address national security threats through cyberbiosecurity, with 60% of articles focusing on water systems security and 30% on agricultural policy applications. The research integrates generative AI, causal inference, and human-AI teaming to solve problems ranging from K-9 handler collaboration to global food supply chain resilience. As director of the A 3 Lab, Dr. Batarseh leads interdisciplinary projects funded by federal and industry partners, mentoring graduate students in AI deployment for critical infrastructure. Current initiatives include the ACWA testbed for intelligent water systems and frameworks for friendshoring in agricultural trade.

Kay RömerView profile

Professor

• Wireless Sensor Networks
• Internet of Things
• Cyber-Physical Systems
• +7 more

Kay Römer is Professor and Director of the Institute for Technical Informatics at Graz University of Technology, Austria. He previously held a professorship at the University of Lübeck, Germany, and was a senior researcher at ETH Zurich, where he obtained his doctorate in computer science in 2005. His research focuses on networked embedded systems, particularly in the domains of Wireless Sensor Networks, Internet of Things (IoT), and Cyber-Physical Systems. Key areas include wireless networking, operating systems, programming models, dependability, and deployment methodologies for large-scale embedded networks. The most recent publications reflect a consistent trend in dependable and scalable IoT systems, with emphasis on wireless protocols, fault tolerance, real-time operation, and system robustness. His work bridges theoretical innovation with practical deployment, often involving cross-layer design and energy efficiency. Associate Editor, IEEE Transactions on Mobile Computing Associate Editor, IEEE Transactions on Computers Program Co-Chair, ACM SenSys 2011 Program Co-Chair, ACM/IEEE IPSN 2013 Coordinator, EU FP7 FIRE Project RELYonIT Coordinator, TU Graz Excellence Project "Dependable Internet of Things" Kay Römer has advised multiple research teams and coordinated major international projects funded by the Swiss National Science Foundation, European Commission, German Science Foundation, German Federal Ministry of Education and Research, and the Austrian Federal Ministry of Science, Research, and Economy. He has delivered invited keynote talks and co-directed five international summer schools, demonstrating strong leadership in research dissemination and mentoring. He leads research activities within the Institute for Technical Informatics at TU Graz, focusing on dependable and secure IoT systems, with active collaborations across Europe and industry partners.

• Power Electronics
• Renewable Energy Conversion Systems
• Power Semiconductor Device Modeling
• +4 more

Dr. Ruiyun Fu serves as Assistant Professor in the Department of Electrical and Computer Engineering within Mercer University's School of Engineering. Her expertise spans power electronics, renewable energy systems, and semiconductor device modeling. Education: PhD in Electrical Engineering, University of South Carolina (2013) MS in Electrical Engineering, Huazhong University of Science and Technology (2007) BS in Electrical Engineering, Huazhong University of Science and Technology (2004) Her research focuses on power semiconductor device modeling (particularly SiC-MOSFET & GaN-FET), grid-connected power converters , renewable energy conversion systems , and high-frequency resonant inverters . She has developed innovative approaches for DC network protection using Z-source circuit breakers and advanced wireless power transfer techniques. Analysis of her 15 most recent publications reveals strong emphasis on DC power network security (33% of articles), semiconductor device modeling (27%), and wireless power transfer optimization (20%). The work demonstrates consistent progression from fundamental device modeling toward grid integration challenges, with increasing focus on cybersecurity aspects in recent years. Dr. Fu maintains active leadership in professional societies including IEEE Power Electronics Society, IEEE Industry Applications Society, and IEEE Women in Engineering. She serves as regular reviewer for multiple IEEE transactions and conferences including ECCE, APEC, and PES-GM. Her educational contributions include pandemic-responsive laboratory adaptations and STEAM outreach initiatives for women, reflecting commitment to both technical innovation and engineering education advancement.

Simin Nadjm-TehraniView profile

Professor

• Cybersecurity
• Real-Time Systems
• Formal Verification
• +4 more

Simin Nadjm-Tehrani is a Professor and Head of Unit at Linköping University's Department of Computer and Information Science (IDA), leading the Real-time Systems Laboratory (RTSLAB) since 2000. She holds a PhD in Computer Science from Linköping University (1994) and previously served as a full professor at the University of Luxembourg (2006–2008). Her research focuses on cybersecurity, dependability in distributed systems, and formal methods for safety-critical applications. Key research areas include adaptive anomaly detection in critical infrastructures, energy-efficient protocols, and formal analysis of safety protocols. She leads the NEST-project on AI for cyber attack identification and contributes to the Wallenberg AI, Autonomous Systems and Software Program (WASP). Her work addresses challenges in smart grids, edge computing, and secure communication protocols. Publications emphasize practical applications of formal verification in tree ensembles, SCADA systems, and avionics. She organized the 2019 CRITIS conference and collaborates with industry on edge computing benchmarks and secure IoT architectures. Her educational contributions include curriculum design for problem-based learning (PBL) and gender equity initiatives in computer science. Professional roles include leadership in the Software and Systems (SAS) division at IDA, where she oversees interdisciplinary projects combining safety and security constraints. Current efforts target resilient information systems for societal functions like energy and transportation.

Derya AksarayView profile

Assistant Professor

• Robotics
• Control Theory
• Formal Methods
• +4 more

Derya Aksaray is an Assistant Professor in the Department of Electrical and Computer Engineering at Northeastern University, where she directs the Dependable Autonomy Lab (DAL). She holds a PhD in Aerospace Engineering from Georgia Tech (2014) and has prior roles as an Assistant Professor at the University of Minnesota (2018-2022), and postdoctoral positions at MIT CSAIL (2016-2017) and Boston University (2014-2016). Her research focuses on control theory, formal methods, and machine learning for robotics and autonomous systems, particularly in uncertain and dynamic environments. Education: PhD, Aerospace Engineering, Georgia Institute of Technology (2014) MS, Aerospace Engineering, Georgia Institute of Technology (2011) BS, Aerospace Engineering, Middle East Technical University (2008) Research Interests: Formal methods for autonomous systems Reinforcement learning with temporal logic constraints Multi-agent coordination and distributed planning Resilient control for robotics and aerospace systems Energy-aware planning for UAVs and heterogeneous systems Lab Activities: The Dependable Autonomy Lab develops theory and algorithms for achieving reliable autonomous robot behaviors, with experimental validation on ground and aerial robots. Current projects include resilient planning under uncertainty, distributed multi-agent systems, and reinforcement learning with formal guarantees. Advising: Prof. Aksaray supervises graduate students in PhD and MS programs, focusing on control theory, formal methods, and robotics applications. Former advisees include Ali Tevfik Buyukkocak (PhD, 2024) and Ryan Peterson (MS, 2020). Professional Affiliations: Member of the American Institute of Aeronautics and Astronautics (AIAA) and Institute of Electrical and Electronics Engineers (IEEE).