Find Academic Supervisors

• Mobile Communications
• Wireless Sensor Networks
• Computer Vision
• +4 more

Dr. Wafa Elmannai is an Associate Professor in the Department of Electrical and Computer Engineering at Manhattan College, where she has been since 2018. She holds a Ph.D. in Computer Science and Engineering from the University of Bridgeport, following M.S. and B.S. degrees in Computer Science from the University of Bridgeport and College of Electronic Technology in Libya. Her research focuses on mobile communications, wireless sensor networks, computer vision, health assistive technologies, and quantum computing. She has received numerous awards including the AAUW grant for assistive device research, and the Best Paper Award at the 2020 IEEE Canadian Conference on Electrical and Computer Engineering. Dr. Elmannai's educational background includes a Ph.D. (2018) from the University of Bridgeport, with earlier degrees from the same institution (M.S. 2015) and Libya (B.S. 2005). Her professional roles include leadership in academic societies such as IEEE and AAUEAA, and committee positions at Manhattan College including the Diversity Committee and ABET accreditation coordination. Her research interests emphasize practical applications of technology for accessibility and healthcare, including frameworks for visually impaired navigation, emergency response systems, and robust sensor networks. She has published extensively in journals like IEEE Transactions and conference proceedings, with a focus on interdisciplinary solutions merging computer engineering and biomedical systems. Award recognition highlights her contributions to assistive technologies, cybersecurity, and academic leadership, including the UPE Outstanding President Award (2018) and multiple engineering achievement awards from the University of Bridgeport. She actively contributes to academic governance and serves as a reviewer for journals such as IEEE Access and Transactions on Neural Systems & Rehabilitation Engineering.

Jürgen SchönwälderView profile

Professor

• Computer Networks
• Distributed Systems
• Embedded Systems
• +1 more

Prof. Jürgen Schönwälder is a Professor of Computer Science at the School of Computer Science and Engineering, Constructor University Bremen gGmbH. His research focuses on computer networks, distributed systems, embedded systems, and computer security. He has held positions at TU Braunschweig, University of Twente, and Bell Labs. He leads the Computer Networks and Distributed Systems research group, which addresses challenges in robust network infrastructure and distributed systems resilience. Education: Doctoral Degree in Computer Science, Technical University Braunschweig (1996) Diploma in Computer Science, Technical University Braunschweig (1990) Research Interests: Design of scalable and resilient network services Security in distributed systems Measurement of network performance and behavior IoT and constrained device management Standardization of network protocols (e.g., NETCONF, YANG) Funded Projects: EU Horizon 2020 Concordia (2019-2023) EU FP7 Flamingo (2012-2016) Industry-funded projects in network management and security Key Contributions: Over 100 publications in top venues (IEEE/ACM Transactions, SIGCOMM) and co-chair roles in IETF working groups (NETMOD, ISMS). His work on network configuration (NETCONF), flow analysis, and IPv6 transition mechanisms has shaped modern network management practices.

Volker SkwarekView profile

Professor

• Cybersecurity
• Distributed Systems Security
• IoT and Sensor Networks
• +3 more

Prof. Volker Skwarek is a Professor for Technical Informatics at the Department of Industrial Engineering and Management, Hamburg University of Applied Sciences. He leads the research group DLT³-Hamburg and heads the research and transfer center for digital business processes. His work focuses on cybersecurity in distributed systems, IoT security, and blockchain applications in industrial environments. He has held leadership roles including Deputy Head of the Department HWI and coordinates the graduate focus area 'Information Science'. Research interests include ultra-low-power IoT systems, self-sovereign identity frameworks, and secure blockchain-sensor integrations. Prof. Skwarek has authored over 30 peer-reviewed articles, 2 books, and multiple patents. He actively contributes to international standardization of blockchain technologies and serves on editorial boards for distributed ledger journals. His projects span smart grid security, decentralized energy trading systems, and forensic blockchain analysis. Notable projects include WaterGridSense 4.0 (smart grid resilience), LegalBlock (legal frameworks for smart contracts), and TrustedCamApp (secure video streaming in sensor networks). He emphasizes practical applications alongside theoretical advancements, collaborating closely with industry partners to address real-world challenges in digital security and automation. Prof. Skwarek holds national/international awards for research and education innovation. His teaching includes courses on technical informatics, programming in C, and cybersecurity fundamentals. He advocates for continuous professional development through academic-industry partnerships and standardization initiatives.

• Machine Learning
• Cybersecurity
• IoT (Internet of Things)
• +3 more

Eugenio Grippo is a Visiting Assistant Professor in the Computer Science department at Occidental College and an Adjunct Professor in Data Science at Pacific States University. He holds a Ph.D. and M.S. in Electrical Engineering from the University of Southern California (USC), and a degree in Automation and Industrial Control Engineering from Universidad Nacional de Quilmes (Argentina). His research focuses on cybersecurity, IoT systems, machine learning, decentralized finance, robotics, and power grid control, with notable contributions in DDoS attack detection and grid curvature theory applications. Education: Ph.D./M.S. in Electrical Engineering, University of Southern California (USC) Automation and Industrial Control Engineer, Universidad Nacional de Quilmes (UNQUI) Postdoctoral studies in Electrical and Computer Engineering (ECE) at USC Research Interests: Machine learning for cybersecurity and IoT DDoS attack detection and network defense mechanisms Power grid stability and congestion management using mathematical curvature theory Decentralized finance and blockchain-based market systems Robotics and collaborative autonomous systems Publications Trends: Recent work emphasizes cybersecurity in IoT environments, tactical network synthesis for military applications, and power grid optimization using curvature-based models. Key contributions include neural network frameworks for DDoS detection and dynamic automated market makers for decentralized exchanges. Labs & Affiliations: Previously affiliated with USC's ANRG (Autonomous Network Research Group) and ICAROS Lab (Interactive and Collaborative Autonomous Robotics Lab). Current roles include teaching and research at Occidental College and Pacific States University.

Baisravan HomChaudhuriView profile

Assistant Professor

• Optimal Control
• Model Predictive Control
• Connected Vehicle Systems
• +4 more

Baisravan HomChaudhuri is an Assistant Professor in the Department of Mechanical, Materials, and Aerospace Engineering at the Illinois Institute of Technology (Illinois Tech), part of the Armour College of Engineering. His expertise lies in control systems and optimization, with a focus on model predictive control, connected vehicle systems, and motion planning. Education: Ph.D. Mechanical Engineering, University of Cincinnati, 2013 M.S. Mechanical Engineering, University of Cincinnati, 2010 B.E. Electrical Engineering, Jadavpur University, 2007 Research interests emphasize optimal control strategies for autonomous systems, energy-efficient vehicle control, and stochastic reachability analysis. His work integrates machine learning, distributed optimization, and real-time control for applications in robotics, transportation, and smart grids. Recent studies include eco-driving for hybrid vehicles, collision avoidance under uncertainty, and cooperative control of multi-agent systems. His publications highlight advancements in connected vehicle networks, robust MPC frameworks, and safety-critical motion planning. Notable contributions include fuel-efficient control algorithms for urban traffic and distributed optimization methods for resource allocation in cyber-physical systems. Scientific Awards: MMAE Excellence in Teaching Award (2022) Best Student Paper Award at International Conference on Hybrid Systems (2017) His research is supported by grants focused on hybrid systems, smart transportation, and stochastic control. He advises students in applied control systems and collaborates with industry on connected vehicle technologies. Office: Rettaliata Engineering Center 247.

• Wireless Networks
• Mobile Networks (5G)
• Quality of Service
• +3 more

Mauricio Iturralde is a Researcher-Lecturer at CESI, specializing in Networking and Computer Science. He holds a PhD in Networking and Computer Science from the Institut National Polytechnique de Toulouse and ENSEEIHT (2012), and a Master's in Systems and Networking Security from Télécom SudParis and Paris EST (2009). His research focuses on wireless networks, 5G mobile networks, Quality of Service (QoS), Digital Twins, Industry 5.0, and Cyber Security. He teaches courses on Networking, Cyber Security, System Administration, and Research Methodology to undergraduate and master's students. His work includes optimizing LTE and 5G networks through resource allocation strategies, interference mitigation, and reinforcement learning for energy-efficient protocols. He has contributed to maritime communication systems, railway transportation networks, and social engineering defenses in cybersecurity. His publications span flagship conferences like IEEE PIMRC, WCNC, and journals such as Springer Telecommunication Systems. Notable contributions include Mobile Relays for Urban Rail Systems (2020), Location-Aware Sleep Strategies for 5G (2019), and encryption mechanisms for mobile devices (2015). His research bridges theoretical frameworks (e.g., cooperative game theory) with practical applications in heterogeneous networks and IoT. He is part of the Engineering and Numerical Tools research team at CESI La Rochelle Campus, addressing challenges in digital transformation and Industry 5.0 security. His work emphasizes interdisciplinary approaches, integrating machine learning and network science to solve real-world communication problems.

• Blockchain Technology
• Deep Learning
• Cybersecurity
• +4 more

Yuhang Ye is an Assistant Lecturer in the Department of Computer and Software Engineering at the Technological University of the Shannon: Midlands Midwest. Their research focuses on blockchain technology, cybersecurity, video streaming optimization, and deep learning. Key areas include smart contract-based systems, adversarial machine learning, and network security. Research Interests: Blockchain applications (e.g., payment channels, decentralized agents), cybersecurity (e.g., backdoor attacks, anomaly detection), and video processing (super-resolution techniques). Recent work explores efficient neural architectures and defense mechanisms against adversarial AI. Publications (2021–2025) highlight contributions to blockchain scalability, video super-resolution algorithms, and AI security. Notable collaborations include studies on Ripple transaction networks and IoT security. No awards or grants explicitly listed. No student advisees identified in provided data. Research aligns with UN Sustainable Development Goals related to innovation and infrastructure (SDG 9).

Alessio IovineView profile

Researcher

• Control Systems
• Power Systems
• Cyber-Physical Systems
• +4 more

Alessio Iovine is a CNRS researcher at the Laboratory of Signals and Systems (L2S) affiliated with CentraleSupélec (Paris-Saclay University). His research focuses on control systems for cyber-physical applications, including energy systems (e.g., microgrids, renewable integration) and transportation (e.g., autonomous vehicles, traffic control). He holds a European Doctorate in Information Science and Engineering from the University of L’Aquila and CentraleSupélec, with postdoctoral experience at institutions like UC Berkeley and Efficacity. Research Areas: Cyber-Physical Systems DC/AC Microgrid Control Autonomous Vehicles & Adaptive Cruise Control Predictive Grid Management Multi-Agent Systems Publications Trends: Recent works emphasize mesoscopic control approaches for vehicular systems, distributed control for multi-agent networks, and predictive algorithms for power grid congestion management. Over 20 peer-reviewed articles since 2017 reflect his expertise in nonlinear control, hybrid systems, and renewable integration. Opportunities: Actively recruiting PhD/Master students for projects in cyber-physical power systems, machine learning for grid identification, and autonomous traffic control. Hosts seminars on energy systems and signal processing at Paris-Saclay. Labs/Teams: Member of L2S’s Modelling and Estimation team, collaborating with groups like ILOCOS (Information, Learning, Optimization & Communication Sciences).

Sorin OLARUView profile

Professor

• Optimization-based control design
• Set-theoretic characterization of constrained dynamical systems
• Numerical methods in optimization and control
• +5 more

Sorin Olaru is a Professor at CentraleSupélec and a member of the CNRS Laboratory of Signals and Systems (L2S) at Paris-Saclay University, France. Since 2020, he holds the RTE Chair in Energy System Control. His research focuses on optimization-based control design, set-theoretic methods for constrained dynamical systems, and numerical methods in control and optimization. He leads projects in embedded predictive control, fault-tolerant systems, and network control with time-delays. Education & Affiliations: CentraleSupélec (Professor), CNRS L2S (Researcher), Paris-Saclay University (Affiliated). Research Interests: Model predictive control (MPC), invariant set theory, control design for embedded systems, fault diagnosis, and applications in energy storage (e.g., zinc-air batteries) and autonomous navigation. His work bridges theoretical advances with industrial applications in power systems and robotics. Recent Projects: Development of zinc-air battery models for control, MPC-based congestion management in power grids, and symbolic motion planning for autonomous systems. He actively contributes to conferences like CDC, ICCA, and IFAC NMPC, delivering plenary talks on set-theoretic methods and invariance. Students & Collaborations: Supervises PhD/postdoc researchers (e.g., Oumayma Khattabi, Turan Konyalioglu) and collaborates with industries like Renault and RTE. His group has produced over 20 PhD graduates, many now in academia (e.g., Ionela Prodan at Grenoble INP) or industry R&D. Labs & Teams: Heads the SYCOMORE team (Robust and Constrained Control of Complex Systems) at L2S, fostering interdisciplinary work on energy systems, autonomous robotics, and industrial control challenges.

Harini RamaprasadView profile

Teaching Professor

• Real-time Embedded Systems
• Cyber-Physical Systems
• Operating Systems
• +3 more

Harini Ramaprasad is a Teaching Professor and Associate Dean for Undergraduate Programs and Student Success at the University of North Carolina at Charlotte's College of Computing and Informatics. She holds a Ph.D. in Computer Science from North Carolina State University (2008). Her research focuses on real-time embedded systems, cyber-physical systems, and computer science education, with recent work addressing predictable execution on multi-core architectures and cybersecurity education through interactive modules. Dr. Ramaprasad previously served as Director of Undergraduate Programs at the College and was an Assistant Professor at Southern Illinois University Carbondale. She is an active member of IEEE, ACM, and SWE. Her teaching expertise spans operating systems, real-time systems, software design, and database systems. Her recent publications emphasize practical educational strategies (e.g., using classroom games to develop soft skills) and technical advancements in real-time scheduling, embedded system security, and multi-core architecture optimizations. Despite no listed scientific awards, her contributions to pedagogy and real-time systems highlight impactful interdisciplinary work.

• Computer Networks
• Storage Systems
• Multimedia Systems
• +1 more

Narasimha Annapareddy is the J.W. Runyon Professor at Texas A&M University's Department of Electrical Engineering. A former researcher at IBM Almaden Research Center, he specializes in storage systems, computer networks, and multimedia architectures. His research has received significant recognition including the NSF Career Award (1996-2000), Presidential Silver Medal from IIT India, and Texas A&M's Most Outstanding Professor Award. He regularly serves on technical committees for IEEE Infocom and other major conferences. During his 2009-2010 UC3M research stay, he investigated Wardrop routing approaches for network load balancing and energy-aware routing optimization.

Myron HlynkaView profile

Professor

• Queueing Theory
• Applied Probability
• Stochastic Processes
• +3 more

Dr. Myron Hlynka is a Professor and Chair of the Actuarial Science Program in the Department of Mathematics and Statistics at the University of Windsor, part of the Faculty of Science. He holds a Ph.D. in Mathematics from Penn State University. His research focuses on Queueing Theory, Applied Probability, Stochastic Processes, and Operational Research, with notable applications to healthcare systems and disease modeling. He has advised multiple graduate students, including T. Sajobi, D. Chang, and C. Ramasundarahettige. His work explores theoretical queueing models across diverse domains, such as telecommunications, healthcare, and traffic systems. Recent research highlights include modeling medical interventions using game theory and Markov chains, analyzing parking lot dynamics, and studying sleep patterns as stochastic processes. Dr. Hlynka has contributed to software tools for queueing analysis and has published extensively on topics ranging from Laplace transforms to Fibonacci sequence applications. His research emphasizes practical applications of stochastic models to real-world challenges, including optimization of service systems, risk assessment, and performance evaluation. He maintains an active role in academic leadership through his chairmanship and contributions to curricula in actuarial science.

Peter JohanssonView profile

Professor

• Digital Health
• Chronic Disease Management
• Mental Health
• +3 more

Peter Johansson is a Professor at the Department of Nursing and Reproductive Health (Avdelningen för omvårdnad och reproduktiv hälsa), part of the Faculty of Medicine (Medicinska Fakulteten) at Linköping University. He also serves as Research Director at Närsjukvården i Öster, RegionÖstergötland. His roles combine academic leadership with clinical research and education. Education & Career: PhD in Medicine from Linköping University (2008) Guest Researcher at University Medical Center Groningen, Netherlands (2009) Docent in Medical and Health Sciences (2012) Associate Professor (2017) and Professor (2018) at Linköping University Research Interests: Johansson’s work focuses on digital interventions for chronic disease patients, particularly cardiovascular patients, and informal caregivers. His group, Gruppen för digital hälsa och vård , develops internet-based cognitive behavioral therapy (iCBT) programs tailored for depression management in heart disease patients. He also studies stress reduction strategies for healthcare workers via massage and mindfulness, and caregiver support systems leveraging digital tools. Key areas include: Psychological well-being in chronic illness Telemedicine and digital health Healthcare workforce resilience Public health innovations Key Projects: DOHART 2: Evaluates personalized iCBT for cardiac patients. INSERT: Designs support programs for kidney transplant candidates. IKSIT: Targets anxiety in non-cardiac chest pain patients. Digital Support Programs: Pilot studies for informal caregivers. Labs/Teams: Leads the transdisciplinary Forskningsgruppen för digital hälsa och vård , collaborating with nurses, psychologists, and clinicians to advance digital health solutions. Future Work: Expanding caregiver support programs, optimizing iCBT personalization, and exploring AI-driven health monitoring in primary care settings.

Brian MarkView profile

Professor

• Communication Networks
• Wireless Communications
• Network Security
• +6 more

Brian Mark is a Professor and Interim Chair of the Department of Electrical and Computer Engineering at George Mason University since 2000. His research focuses on communication networks, wireless systems, and network security. Prior affiliations include NEC Laboratories America and Télécom Paris. Education: PhD in Electrical Engineering (Princeton University, 1995), B.ASc. in Computer Engineering (University of Waterloo, 1991) Research Interests: Communication networks, 5G/6G wireless, machine learning, stochastic models, network security Awards: NSF CAREER award (2002), Outstanding Research Faculty award (2011) Editorial Roles: Associate Editor, IEEE Transactions on Vehicular Technology (2006-2009) His recent work explores dynamic spectrum sharing in 5G/6G networks, statistical inference for network performance, and security in IoT environments. He applies machine learning to wireless coexistence and object tracking, while also addressing challenges in traffic network optimization and cryptographic offloading. Scientific recognition includes the NSF CAREER award, IEEE Senior Membership, and the Volgenau School's Outstanding Research Faculty award. He has contributed to network tomography, spectrum sensing, and secure device pairing, with 15 recent publications spanning wireless design, AI security, and transportation network optimization.

• Massive MIMO
• Aeronautical Communications
• Optimization Algorithms
• +4 more

Jiankang Zhang is a Senior Lecturer in Computer Science at Bournemouth University, UK. He previously held positions at the University of Southampton (Senior Research Fellow) and Zhengzhou University (Lecturer/Associate Professor). His research focuses on massive MIMO , aeronautical communications , optimization algorithms , and edge computing , with applications to UAV networks, visible light communication (VLC), and physical layer security. Education: PhD in Communication and Information Systems (Zhengzhou University, 2012), BSc in Mathematics and Applied Mathematics (Beijing University of Posts and Telecommunications, 2006) His recent work explores reconfigurable intelligent surfaces (RIS) for secure transmissions, UAV-assisted networks , and multi-agent reinforcement learning for resource allocation in NOMA-V2X systems. He contributes to IEEE journals as an Associate Editor and Guest Editor. Scientific Awards: IEEE Senior Member (2018), Outstanding Associate Editor (IEEE Access, 2020), Workshop Chair (IRSCN), Guest Editor roles His article trends emphasize 5G/6G , secure wireless communication , machine learning-aided network optimization , and UAV mobility , with a focus on balancing security vs. efficiency in next-generation networks.