Martin Wulf Gerdes is an Associate Professor at the Department of Information and Communication Technology, University of Agder, Norway. With a Ph.D. in eHealth and over two decades of experience in telecommunications and healthcare technology research, he focuses on developing user-friendly, interoperable eHealth solutions using ICT and IoT. His career spans roles at Ericsson Eurolab and academic leadership in Norway. Education: M.Sc. equivalent in General Electrical Engineering (1998) from RWTH Aachen, emphasizing ICT. Ph.D.: Information and Communication Technologies with eHealth specialization (2019) from University of Agder. Research Interests: Gerdes explores AI-driven decision support systems, distributed eHealth infrastructure, telemedicine, and assistive technologies for chronic disease management. His work bridges IoT, data privacy, and user-centered design in healthcare robotics. Teaching: Since 2014, he has taught at bachelor's and master's levels, currently leading courses in Communication & Cooperation, Technology Understanding, and seminar projects in eHealth. Scientific Publications: His 15 most recent articles (2020-2024) span AI in dental radiology, blood glucose prediction, digital twins, and ethical considerations in healthcare algorithms. Topics include IoT integration, data privacy, and pandemic analytics.
Kris Luyten is a Researcher at Hasselt University 's Expertise Centre for Digital Media in Belgium. He specializes in Human-Computer Interaction , Wearable Technology , and Interactive Systems through extensive collaborations with institutions like ACM, Springer, and interdisciplinary teams. Focus on haptic interfaces , telerobotics , and delay-invariant interaction Contributions to multimodal interface design and predictive usability models His recent work explores AI-Spectra dashboards for model transparency and ViRgilites for VR haptics. Publications span journals like Proc. ACM Hum. Comput. Interact. and conferences such as CHI , EICS , and VRST . While no student advising or awards are explicitly listed, his editorial roles (e.g., PACMHCI editorials) demonstrate leadership in interactive systems research.
Dr. Kelly P. Westlake serves as Professor in the Department of Physical Therapy and Rehabilitation Science at the University of Maryland School of Medicine, with secondary appointments in Diagnostic Radiology Nuclear Medicine and Neurology. As Director of the PhD and DPT/PhD program in Physical Rehabilitation Science, she leads advanced training initiatives while maintaining thirty years of clinical and research expertise focused on neurological disorders and age-related mobility decline. Her educational foundation includes a Physical Therapy degree from McGill University, M.Sc. and Ph.D. degrees in Rehabilitation Sciences from Queen's University, followed by postdoctoral training at Stanford University/Palo Alto VA (CIHR Clinical Research fellowship) and University of California, San Francisco (American Heart Association Fellowship). This trajectory established her dual expertise in clinical neurorehabilitation and advanced neuroscience methodology. Dr. Westlake's research program investigates sensorimotor-cognitive mechanisms underlying movement impairments in stroke, Parkinson's disease, and mild cognitive impairment through an integrative approach combining biomechanics (kinematics/kinetics), neuroimaging (fMRI/EEG/MEG), and psychophysiological assessments (HRV/GSC). Her distinctive work explores sleep-based motor learning consolidation via targeted memory reactivation and cognitive-motor interactions in reactive fall recovery, driving development of task-oriented robotic rehabilitation devices for clinical translation. Recent publications reveal strong trends toward home-based and self-managed rehabilitation solutions for stroke recovery, with growing emphasis on cognitive-motor interactions in aging populations and biomechanical analysis of perturbation responses for fall prevention. These studies consistently prioritize patient-centered, evidence-based interventions leveraging technological innovation to enhance accessibility and efficacy. Her scientific recognition includes: CIHR Clinical Research fellowship American Heart Association Fellowship Dr. Westlake currently leads $10+ million in grant funding including a 2025-2026 Maryland Industrial Partnerships Grant for FES treatment of shoulder adhesive capsulitis and multiple NIH awards (NIDILRR, NIA, NINDS) focused on stroke rehabilitation, fall prevention in older adults, and neuromotor training. She mentors PhD candidates and postdoctoral fellows through the Physical Rehabilitation Science PhD Program and UMANRRT fellowship, while developing clinical practice guidelines as Leader of the Balance and Falls in Neurological Conditions group for the APTA Academy of Neurologic Rehabilitation. The Neuromechanisms of Movement and Learning (NeuMo) Laboratory, directed by Dr. Westlake, features state-of-the-art capabilities including fMRI/EEG/MEG neuromonitoring, Vicon kinematics, Bertek force platforms, ActiveStep balance perturbation system, custom Balance boardwalk (patent pending), and Kinereach virtual reality systems. The lab maintains active collaborations with the UM Sleep Lab and UM Rehab for clinical-home integration studies, supported by academic-industry partnerships advancing rehabilitation technology development.
Prof. Fabio Galasso is a Full Professor in the Department of Computer Science at Sapienza University of Rome, where he heads the Perception and Intelligence Lab (PINLab). His research focuses on fundamental innovation in computer vision and machine learning, with particular emphasis on distributed intelligent systems, perception frameworks, and general intelligence within sustainable and interpretable AI contexts. His research interests span multiple domains of computer vision including video segmentation , motion forecasting , distributed intelligent systems , and shape reconstruction . Galasso's work emphasizes sustainable AI approaches that operate within constrained computational resources while maintaining interpretability and verifiability. His research bridges theoretical foundations with practical applications across retail, smart cities, and industrial settings. His recent publications demonstrate a clear progression toward increasingly complex human motion understanding and forecasting, with a strong emphasis on real-world applications. The research trajectory shows movement from foundational video segmentation techniques toward sophisticated motion prediction systems and anomaly detection frameworks that integrate multiple modalities. Key themes include temporal consistency, computational efficiency, and practical deployability in resource-constrained environments. His scientific achievements have been recognized with prestigious awards: 2019 IoT/WT Innovation World Cup 2019 Digital Champions Award 2018 Deutscher Digital Award Galasso has coordinated significant research initiatives including a Marie Sklodowska-Curie Actions project (Horizon 2020) and served as Principal Co-Investigator in multiple German-funded projects from the Ministry of Education and Ministry of Economics. His industry experience includes founding and directing OSRAM's Computer Vision Department in Munich, where he led R&D efforts connecting AI research with smart lighting applications, resulting in successful innovation transfers like the award-winning VISN product. He leads the Perception and Intelligence Lab (PINLab) at Sapienza University of Rome, fostering research that spans fundamental computer vision techniques to practical implementations in retail, smart cities, and industrial applications. The lab maintains strong connections with both academic institutions (including previous collaborations with University of Cambridge and Max Planck Institute) and industry partners.
Sangyoung Park is an Assistant Professor of Smart Mobility Systems at the Faculty of Mechanical Engineering and Transport Systems, Technical University of Berlin, and is co-affiliated with the Einstein Center for Digital Future. His research focuses on two main areas: enhancing vehicle safety through digitalization and connectivity, and advancing the electrification of the transport sector with emphasis on electric vehicle battery systems design and management. He leads the Chair of Smart Mobility Systems at TU Berlin, where his team investigates how vehicle connectivity can improve energy efficiency, traffic flow, and safety in autonomous vehicle systems. Dr. Park completed his PhD in Electrical Engineering and Computer Science at Seoul National University in Korea, where he focused on energy management techniques for hybrid energy storage systems in electric vehicles. Before joining TU Berlin in 2018, he conducted postdoctoral research at the Technical University of Munich, working on energy management for smartphones in collaboration with Google and studying battery aging processes. His research interests span smart mobility systems, electric vehicle battery management, energy consumption optimization, vehicle connectivity, and autonomous driving systems. Park's work bridges the gap between design engineers and software engineers, investigating how different energy storage components (fuel cells, supercapacitors, lithium-ion batteries) should be interconnected and managed together for maximum efficiency. His research also addresses the design of charging infrastructure for electric vehicles. Analysis of Dr. Park's recent publications reveals a strong focus on digital twin technology for teleoperated driving, battery management systems for electric vehicles, and vehicle connectivity for improved safety and efficiency. His research increasingly integrates cybersecurity aspects of connected vehicles and explores novel approaches to extend battery lifespan through advanced cell balancing techniques. The interdisciplinary nature of his work connects electrical engineering, computer science, transportation systems, and urban infrastructure planning. Dr. Park supervises multiple doctoral students, including Philipp Kremer, Ongun Türkçüoglu, Kil Young Lee, Maria Claudia Miguel de Priego, Muzaffer Citir, Andrea Reindl, Subhendu Bhadra, and Hueseyin Türkyilmaz. His research is supported by various funding sources including the ECDF grant, DAAD projects (ide3a), and government scholarships. He collaborates with institutions including OTH Regensburg and Siemens Mobility. His laboratory, the Smart Mobility Systems group, focuses on developing system-level approaches for measuring, analyzing, and balancing energy consumption in battery-powered mobile systems. The team investigates how direct communication among autonomous vehicles can enable control scenarios that improve energy efficiency, traffic flow, and safety beyond what human drivers or isolated autonomous vehicles can achieve.
Professor Subhajit Basu is a leading academic at the University of Leeds , holding the position of Professor of Law and Technology within the School of Law . His work bridges Law, Artificial Intelligence, Big Data, and Emerging Technologies , with a focus on the Global South . He has authored influential books including Privacy and Healthcare Data (Routledge, 2016) and Global Perspectives on E-Commerce Taxation Law (Ashgate, 2008). PhD, Liverpool John Moores University LLB, Calcutta University Called to the Bar in 1998, specializing in Corporate Law in India Research Interests span Regulation of Emerging Technologies, AI Governance, Health Data Privacy, Autonomous Systems, and Online Harm . His recent projects include CoR: Sextortion in the Age of Blockchain and Deepfakes (Naif Arab University, 2025–2026) and Autonomy and Moral Agency in Bioethics (WBNUJS, 2024–2025). He previously led EU Horizon projects like PASCAL (2019–2023) on Connected and Autonomous Vehicles. Scientific Awards include the Hind Rattan (Jewel of India, 2020) and fellowships from the Royal Society of Arts and Higher Education Academy . His editorial leadership includes Editor-in-Chief of the International Review of Law Computers and Technology and associate roles on five journals. Notable Grants include funding from Naif Arab University (Saudi Arabia), EU Horizon 2020, EPSRC, and the Atlantic Philanthropies. He has provided consultancy to the National Cybercrime Research Centre (Poland), the Government of Saudi Arabia on AI frameworks, and The Dialogue (India) on IT Rules.
Yiannis Karayiannidis is a Senior Researcher (equivalent to Associate Professor/Research) with the Division of Systems and Control (SYSCON), Department of Electrical Engineering at Chalmers University of Technology. He maintains a significant affiliation with the Department of Robotics, Perception and Learning at KTH Royal Institute of Technology, demonstrating his cross-institutional impact in the Swedish robotics community. Dr. Karayiannidis earned his Diploma in Engineering in 2004, followed by a Ph.D. in Engineering in 2009, and achieved Docent status in 2017. His academic journey has focused on robotics and control systems, establishing him as a leading researcher in these fields. His primary research interests span robot control, robotic manipulation in human-centered environments, dual arm manipulation, force control, robotic assembly, control of physical human-robot interaction, multi-agent robotic systems, adaptive control and nonlinear control systems. Dr. Karayiannidis has made significant contributions to the understanding of deformable object manipulation, contact-rich robotic tasks, and human-robot collaboration. His work bridges theoretical control systems with practical robotic applications, particularly in scenarios requiring precise physical interaction. Analysis of his recent publications reveals a strong focus on advanced manipulation techniques, particularly for deformable linear objects, and human-robot collaborative tasks. His research increasingly incorporates machine learning approaches, especially reinforcement learning, to address complex manipulation challenges. There is also a clear emphasis on practical applications in industrial settings, with several projects related to robotic assembly and cable routing. Dr. Karayiannidis serves as Associate Editor for the IEEE Robotics and Automation Letters, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), and the European Control Conference. He is also the treasurer of the IEEE Robotics Chapter in Sweden and a WASP-affiliated researcher. He has served as Principal Investigator for multiple research projects including DARMA and DARMA_bridge (funded by WASP), CHROMA (funded by VR), and the H2020 SARAFun project. His current projects include "Learning & Understanding Human-Centered Robotic Manipulation Strategies" (2020-2025), "Computer Vision and Machine Learning for Robot Systems" (2019-2021), and "ViMCoR" (2019-2021) in collaboration with Volvo Group. Dr. Karayiannidis is actively involved in the robotics research community through his editorial roles and project leadership. His work connects theoretical control systems with practical robotic applications, particularly in industrial and human-robot collaborative settings.
Meng Yuan is a Marie Skłodowska-Curie Fellow at Chalmers University of Technology , affiliated with the Control Engineering department. Previously, he was a Research Fellow at the Rehabilitation Research Institute of Singapore, Nanyang Technological University, and earned his PhD in Electrical and Electronic Engineering from the University of Melbourne. Research Focus: Control theory, energy systems, rehabilitation engineering, robotics, and industrial automation. Notable Projects: Integration of reinforcement learning and predictive control for energy management in smart homes (SmartHOME), funded by the European Commission (EU). His recent publications explore machine learning for industrial load forecasting, deep reinforcement learning in manufacturing optimization, and safety-critical control systems for assistive robots. A 2024 Advanced Engineering Informatics paper highlights his work on steel logistics, while a 2023 IEEE Transactions on Cybernetics article details wheelchair speed control using robust MPC. Awards: Marie Skłodowska-Curie Fellowship Collaborative Networks: Active in smart home energy projects and industrial robotics teams at Chalmers. Supervises research in control algorithm development but no specific students are listed in the provided data.
Kamesh Namuduri is a Professor in the Department of Electrical Engineering at the University of North Texas. He leads the Autonomous Systems Laboratory (ASL), focusing on cooperative decentralized systems, UAV networks, and advanced air mobility solutions. Key Research Areas: Autonomous Systems UAV Networks and Communications Collision Avoidance Strategies Disaster Recovery Applications Digital Twin Airspace Management Recent work examines advanced air mobility through vehicle-to-vehicle communication frameworks, wireless localization challenges, and air corridor traffic control. The ASL investigates mobility, security, and cooperative control in airborne networks with applications to surveillance, planetary exploration, and emergency response. Laboratory Facilities: The Autonomous Systems Laboratory supports research in robotic systems, wireless sensor networks, and decentralized consensus-building algorithms.
Nathir Rawashdeh is an Assistant Professor in the Department of Applied Computing at Michigan Technological University , with an affiliated appointment in Electrical and Computer Engineering . He is a Senior Member of the IEEE and a member of the Institute of Computing and Cybersystems (ICC) and Great Lakes Research Center . Education: Ph.D., Electrical Engineering, University of Kentucky, 2007 MS, Electrical and Computer Engineering, University of Massachusetts, Amherst, 2003 BS, Electrical Engineering, University of Kentucky, 2000 Dr. Rawashdeh's research focuses on unmanned vehicle perception , image analysis , control systems , and mechatronics , with applications in autonomous driving, winter weather adaptation, and industrial automation. His work includes sensor fusion, deep learning, and AI-enhanced manufacturing solutions. Recent publications highlight advancements in winter weather autonomous driving , UV disinfection robotics , and AI-driven industrial inspection systems . His research spans mechatronics curriculum development, industry 4.0 integration, and cross-cultural educational initiatives. Scientific Awards: Senior Member of the IEEE Dr. Rawashdeh has secured over $2 million in funding from organizations including the NSF , Ford Motor Co. , NIST , and the European Commission . His grants support projects like GPU clusters for research, winter weather autonomous driving standards, and UV sterilization robotics. He leads the Mobile Robotics Lab at Michigan Tech, focusing on collaboration and innovation in autonomous systems and mechatronics research.
Annarita De Maio serves as a Researcher in Operations Research (MAT/09) at the Department of Economics, Statistics and Finance (DESF) of the University of Calabria, where she teaches Logistics, Operations Research, and Mathematical Methods for Economics courses across undergraduate and graduate programs including Economics, Data Science, and Management Engineering. PhD in Mathematics and Computer Science (2018), University of Calabria Dissertation: Integrated Logistics and Last-Mile Deliveries (developed with Procter & Gamble) Research periods at P&G Brussels and CIRRELT/Laval University (Quebec) Her research centers on Logistics 4.0 innovations with dual emphasis on sustainable last-mile delivery systems (crowdshipping, autonomous robots, locker networks) and smart tourism applications . Current projects integrate IoT and AI for optimizing pharmaceutical distribution, perishable goods logistics, and urban tourist trip planning while addressing environmental constraints and stochastic demand patterns. Recent publications (2022-2025) reveal three thematic clusters: (1) stochastic optimization for dynamic delivery systems, (2) sustainable urban logistics solutions using multi-modal transport, and (3) data-driven tourism management frameworks. Her work consistently bridges theoretical modeling with industrial case studies involving Italian companies and municipal authorities. As an active member of DESF's Quantitative Methods for Economics, Finance and Management research group, she contributes to regionally and nationally funded projects focusing on mathematical programming applications. Her international conference participation includes speaking and organizing roles at major logistics and operations research events. Dr. De Maio collaborates within the department's research ecosystem through the Quantitative Methods group, which develops computational models for decision-making in finance, actuarial science, and transportation. Current initiatives explore crowdshipping economics, green tourist trip design, and risk-aware inventory systems for perishable commodities.
Prof. Dr. Jens Wagner is a faculty member at HTWK Leipzig (Hochschule für Technik, Wirtschaft und Kultur Leipzig) specializing in Mobile Robotics. He is affiliated with the Faculty of Computer Science and Media, where he contributes to the institution's technical education programs. His research focuses on mobile robotics systems, encompassing navigation, perception, and autonomous operation in various environments. This field sits at the intersection of computer science, mechanical engineering, and artificial intelligence, with applications ranging from industrial automation to service robotics. Prof. Wagner maintains an active teaching and research schedule, with office hours available by appointment. Students are encouraged to contact him via email to schedule meetings regarding academic matters or research opportunities in robotics.
Dr. Al Edwards is a Professor in the Department of Pharmacy within the School of Chemistry, Food and Pharmacy at the University of Reading. His extensive research portfolio spans over two decades, with a clear evolution from immunology and dendritic cell biology in his earlier career to his current focus on microfluidic diagnostic devices and point-of-care testing technologies. Professor Edwards' research interests center on developing innovative diagnostic solutions, particularly in microfluidics and point-of-care testing. His work bridges engineering and clinical applications, with significant contributions to antibiotic susceptibility testing, vaccine delivery systems, and smartphone-based diagnostic platforms. His research has evolved from fundamental immunological studies to highly applied diagnostic device development, demonstrating a strong translational research trajectory. His publication record shows a clear trend toward practical diagnostic solutions with clinical applications, particularly in antibiotic susceptibility testing and point-of-care diagnostics. The integration of microfluidics, 3D printing, and smartphone technology represents the cutting edge of his current research, with numerous publications demonstrating how these technologies can be combined to create accessible diagnostic tools for resource-limited settings. Professor Edwards has been actively involved in mentoring researchers and collaborating across disciplines, as evidenced by his numerous co-authored publications. His work on diagnostic device usability and information design for self-testing demonstrates attention to the practical implementation challenges of diagnostic technologies. His laboratory appears to specialize in developing open-source, low-cost diagnostic platforms using Raspberry Pi systems, 3D printing, and microcapillary technologies. The Cygnus platform for smartphone-based diagnostics and the PiRamid imaging system represent significant contributions to making sophisticated diagnostic technologies more accessible.
Roy Sterritt is a Lecturer in Informatics at the School of Computing, Ulster University. His research focuses on autonomic computing, robotics, machine learning, and cybersecurity. He has contributed extensively to decentralized systems and fault management in autonomous environments. Research Interests: Roy’s work spans autonomic computing, robotics, and AI, with applications in cloud systems, space exploration, and drone fleets. He emphasizes self-adaptation, fault tolerance, and security protocols. Scientific Awards: Highly Ranked Scholar in Autonomic Computing (2024) Multiple Best Paper Awards (2016–2023) Recent Trends: His recent publications highlight autonomic solutions in cloud security, robot swarms, and space systems, leveraging machine learning and adaptive communication protocols. Projects & Collaborations: Roy has led projects like SPAAACE-Ware and DEL CAST AWARD, focusing on autonomic analytics and apoptotic computing. He organizes international conferences on autonomous systems and collaborates globally.
I.V. Ramakrishnan is a Professor in the Department of Computer Science at Stony Brook University. His research spans Artificial Intelligence, Computational Logic, Machine Learning, Information Retrieval, and Computer Accessibility. Ph.D. in Computer Science, University of Texas at Austin (1983) His work focuses on advancing AI and machine learning to solve accessibility challenges for visually impaired users, healthcare informatics, and robotic manipulation. Key contributions include leveraging large language models for multimodal text correction, developing gesture recognition systems for blind users, and applying reinforcement learning to medical data analysis. Recent publications highlight the integration of LLMs in accessibility tools, AI-driven healthcare solutions (e.g., mortality risk prediction, physician attribution), and robotics innovations (e.g., manipulation planning, vertical farming automation). Faculty Service Award (2014) He teaches courses CSE 352 (Artificial Intelligence) and CSE 537 (AI). His research bridges theoretical and applied domains, emphasizing inclusive technology and clinical decision support systems.
