Luc Jaulin is a Professor at the University Bretagne Occidentale and affiliated with Lab-STICC (UMR 6285) and ENSTA Bretagne. His research focuses on robotics, control systems, underwater navigation, and interval analysis. He leads projects in autonomous systems, such as robotic exploration (Robex) and underwater vehicle control. He has extensive teaching experience in robotics, including courses on mobile robotics, Kalman filtering, and nonlinear control. His work integrates theoretical methods with practical applications, emphasizing reliable state estimation and set-based approaches. Education and Affiliations: Professor at University of Western Brittany (ENSTA Bretagne) Laboratory: Lab-STICC, UMR 6285 Participates in the Master SDS program at Angers, focusing on robotics and automation research. Research Interests: Autonomous robotics and underwater vehicle navigation Interval analysis and set-membership methods Control systems and real-time algorithms Robot localization and SLAM Algorithm development for marine robotics Advising and Grants: Supervised over 100 students in robotics-related stages and theses. Contributed to projects like ANR ElectroKarst (underwater exploration) and Robotic Spacecraft design. Collaborates with industries (e.g., Thales, FORSSEA Robotics) and academic institutions globally. Labs and Teams: Core member of Lab-STICC and the Robex (Robotics Exploration) team, focusing on innovative robotics solutions.
Dr. İsmail Bayezit serves as an Assistant Professor in the Department of Aeronautical Engineering at Istanbul Technical University (ITU), Turkey, with active research since 2007. His work bridges aerospace and marine engineering domains, focusing on unmanned systems and control technologies. With an h-index of 8 and 321 Scopus citations across 33 research outputs, he has secured 6 major research projects including VTOL system development and marine craft autonomy initiatives. His research fingerprint reveals dominant expertise in Quadcopter Engineering (100%), Motion Control (81%), and Unmanned Aerial Vehicle systems (80%). He specializes in advanced control methodologies including extremum-seeking control, LQR techniques, and distributed control strategies. Current work extends into AI-integrated navigation systems and energy-optimized flight performance, with significant crossover applications in marine craft control and underwater acoustics. Recent publications (2024-2025) demonstrate three converging trends: optimization of electric multirotor performance through energy-aware control, neural network-assisted navigation for GPS-denied environments, and cross-domain applications of control theory to both aerial and marine systems. His work increasingly integrates artificial intelligence with traditional control frameworks while maintaining strong experimental validation through physical prototypes. Bayezit has supervised 21 students and led 6 research projects from 2017-2025, including EU-funded initiatives on VTOL systems and national projects on UAV education sets. His project portfolio shows consistent progression from fundamental control theory (2017-2019) toward applied AI integration (2023-2025), with recent work focusing on autonomous marine craft instrumentation and next-generation UAV performance optimization.
Professor Khaled Hayatleh is a Professor of Electronic Engineering at the School of Engineering, Computing and Mathematics, Oxford Brookes University. His research focuses on Biomedical Engineering, Autonomous Vehicle Navigation Systems, and Radio Frequency Design. He teaches advanced electronics modules and supervises PhD/Master’s students in these areas. His research projects include AI-based artefact minimization in biomedical systems, autonomous vehicle navigation, and electrical impedance tomography. He has published extensively in journals like International Journal of Electronics and Journal of Circuits, Systems, and Computers . Professor Hayatleh serves as an Associate Editor for Journal of Circuits, Systems and Computers and International Journal of Electronics and Communications , and chaired the Oxford Circuits and Systems Conference (OXCAS 2017). He holds a BEng and PhD in Electronic Engineering.
Ahmed Farooq is a University Lecturer and Senior Researcher at the Tampere Unit for Computer-Human Interaction (TAUCHI), Tampere University. He holds a PhD in Computer Science and has over 20 years of experience in haptic and multimodal interaction systems. His current role combines academic teaching (e.g., HI 520 Haptic Interaction course) with advanced research in haptic mediation, wearable technologies, and AI-driven interaction systems. Affiliations: TAUCHI Research Group, Tampere Institute of Advanced Studies (TIAS) Positions: Permanent Lecturer (2024–present), TIAS Postdoctoral Fellow (2022–2024), Visiting Researcher at McGill University (2020) and Purdue University (2019–2020) Research Interests: Haptic signal mediation, 3D-printed haptic waveguides, magnetorheological fluid actuators, AI integration in multimodal systems (e.g., TAUCHI-GPT), and applications in automotive UI, VR/XR, and food interaction systems. His work focuses on reducing driver distraction, enhancing tactile feedback in virtual environments, and developing ethical AI tools. Key Projects: Origo Steering Wheel (German Design Award, 2021), Augmented Eating Experiences (AEE), Huawei Haptic Mediation, and TAUCHI-GPT open-source AI framework. These projects involve collaboration with industry partners like Huawei and Bentley University. Publications: Over 60 peer-reviewed articles in top venues (ACM, IEEE, EuroHaptics) focusing on haptic actuation, multimodal interaction, and AI ethics. Recent work explores prompt injection attacks in LLMs and implantable haptic actuators. Awards: TIAS Postdoctoral Fellowship (2022–2024), Finnish Cultural Foundation Mobility Grant (2018). His research has led to 9 patents (e.g., multifunctional haptic actuator, 2024) and 6 granted US/Japan patents.
Javier Bajo is a Full Professor at the School of Computer Engineering, Polytechnic University of Madrid (UPM). He coordinates the Master's Degree in Artificial Intelligence at UPM and previously held roles as Associate Professor and Director of the Data Center at the Pontifical University of Salamanca (2003–2012). He earned a PhD in Computer Sciences (summa cum laude) from the University of Salamanca (2007), a Master’s in E-Commerce (2006), and degrees in Computer Systems Engineering (University of Valladolid, 2001) and Computer Science (Pontifical University of Salamanca, 2003). His research focuses on multi-agent systems, social computing, ambient intelligence, and AI ethics. He has led 11 research projects and contributed to over 50 others, with funding from EU, national, and regional entities. He has authored/co-authored over 300 publications, including 49 in JCR-indexed journals, and co-chaired 30+ international conferences (e.g., ACM SAC, IEEE FUSION). His work bridges theory and practice: developing multi-agent architectures for smart cities, optimizing traffic systems, and addressing algorithmic fairness. He also pioneers gamification in machine learning education and applies AI to healthcare diagnostics and infrastructure management. Key contributions include: Smart waste collection systems with LoRaWAN and route optimization Anti-feromone algorithms for urban rescue robotics Causal models for bias mitigation in AI Multi-sensor fusion for crop irrigation monitoring His educational innovations include challenge-based learning frameworks for computational biology and flipped classrooms for sustainability education.
Gunar Schirner is an Associate Professor of Electrical and Computer Engineering at Northeastern University's College of Engineering . He holds a Ph.D. and M.S. from the University of California, Irvine, and a B.Sc. from Berufsakademie Berlin. His research focuses on embedded systems, cyber-physical systems, and hardware/software co-design, with emphasis on embedded vision and system-level methodologies. Education: Ph.D. & M.S. in Electrical and Computer Engineering, University of California, Irvine (2008, 2005) Bachelor's in Computer Engineering, Berufsakademie Berlin, Germany (1998) Research Interests: Embedded system modeling, real-time AI on edge devices, accelerator-rich computing architectures, and assistive robotics. His work bridges algorithm design with system-level implementation, including projects on neural-controlled prosthetics and marine mammal monitoring via passive acoustic sensing. Grants & Collaborations: Schirner leads/navigate grants totaling over $2M from the National Science Foundation (NSF), U.S. Army, and Office of Naval Research, including a $13M Army contract for distributed sensing research. He co-directs the Embedded Systems Laboratory , advancing heterogeneous platform design and embedded vision systems. Students & Impact: His advisees, including Mo Han and Yagmur Gunay, have won best paper awards at PETRA 2019. He actively integrates industry experience (e.g., Alcatel-Lucent) into teaching, mentoring students in both academia and industry.
Blair Thornton is a Professor of Marine Autonomy at the University of Southampton's Faculty of Engineering and Physical Sciences. He leads research in autonomous marine robotics, sensing, and AI for marine science, and co-directs the FEPS In situ and Remote Intelligent Sensing (IRIS) Centre of Excellence. His work focuses on developing low-cost robotic platforms, 3D seafloor mapping systems, and AI-driven data interpretation methods. Education: PhD in underwater robotics (University of Southampton, 2006), postdoctoral research at University of Tokyo (2006-2016), and over 55 ocean expeditions (30 as PI). Teaching includes Maritime Robotics and Intelligent Mobile Robotics modules with Python-based practicals. Key Projects: BioCam (NERC), TechOceanS (EU), DriftCam (EPSRC), and Smarty200 (EPSRC). Collaborations include Sonardyne International, National Oceanography Centre, and JAMSTEC. Awards include the Okamura Kenji Prize (2014), Shell Ocean Discovery Xprize (2019), and IEEE Mid-Career Rising Star Award (2022). Active in journal editing (IEEE Oceanic Engineering, Robotics and Automation Letters) and external speaking roles.
Patrizia Di Campli San Vito is a Researcher in the School of Computing Science at the University of Glasgow, focusing on Human-AI Interaction and Assistive Technologies. She holds a PhD from the University of Glasgow and prior degrees from the University of Ulm, Germany. Her current work involves participatory harm auditing of AI systems through the PHAWM project and developing adaptive radio systems (RadioMe) for dementia care. Previously, she contributed to ENTER and RadioMe projects addressing aging populations' needs through multimodal interfaces. Education: PhD: University of Glasgow Master's & Bachelor's: Media Informatics, University of Ulm Research Interests: Human-Computer Interaction (HCI), Assistive Technology for Aging Populations, Thermal/Haptic Feedback Systems, Automotive UIs, and Ethical AI Evaluation. She explores how multimodal interactions (e.g., thermal, haptic, audio) can improve accessibility and safety in healthcare and automotive domains. Key Projects: RADIO-ME: Adaptive radio system with agitation detection and music intervention for dementia patients PHAWM: Tools for non-experts to evaluate AI systems' societal impacts ENTER: Multimodal interaction for older adults Recent Work: Her publications focus on stress detection systems, in-car thermal feedback for navigation, and dementia-friendly calendar interfaces. She collaborates with Prof. Simone Stumpf (GIST Lab) and Prof. Stephen Brewster (Multimodal Interaction Group). Labs/Teams: Active in the Glasgow Interaction Systems Team (GIST) and previously contributed to the Multimodal Interaction Group.
João Pedro Hespanha is a Distinguished Professor holding dual appointments in the Electrical and Computer Engineering and Mechanical Engineering departments at the University of California, Santa Barbara. He is affiliated with the Center for Control, Dynamical-Systems and Computation (CCDC) and the Institute for Collaborative Biotechnologies, where he leads research at the intersection of control theory, networked systems, and biological applications. Dr. Hespanha has established himself as a leading authority in hybrid systems and networked control with significant theoretical contributions and practical implementations. Dr. Hespanha received his Licenciatura and MS in Electrical and Computer Engineering from Instituto Superior Técnico in Lisbon, Portugal, before earning his PhD in Electrical Engineering and Applied Science from Yale University in 1998. After serving as an Assistant Professor at the University of Southern California from 1999-2001, he joined UC Santa Barbara in 2002 where he has remained ever since, rising to his current distinguished position. His educational background reflects a strong foundation in both theoretical mathematics and practical engineering applications. His research program spans multiple interconnected domains including hybrid and switched systems, networked control systems, cooperative control of autonomous agents, and systems biology. Dr. Hespanha's work on hybrid systems has fundamentally advanced the mathematical frameworks for modeling systems that combine continuous dynamics with discrete logic transitions. His research on networked control systems addresses critical challenges in communication-constrained environments, while his work in cooperative control tackles computational complexity and limited communication in multi-agent systems. His systems biology research applies control theory to model gene regulatory networks using stochastic hybrid systems. Dr. Hespanha's recent publications demonstrate consistent innovation across theoretical foundations and practical applications. His work shows a clear trajectory toward more complex networked systems, with increasing emphasis on security, resilience, and uncertainty quantification. The publications reveal strong interdisciplinary connections between control theory, computer science, and biology, with applications spanning autonomous vehicles, communication networks, and biological processes. Among his numerous accolades: Elevated to IEEE Fellow in 2008 for contributions to stability techniques for switched and hybrid systems Awarded the prestigious Ruberti Young Researcher Prize in 2009 Received the George S. Axelby Outstanding Paper Award in 2006 Honored with the Automatica Theory/Methodology best paper prize in 2005 Named IFAC Fellow in 2016 Received ACM SIGBED HSCC Best Paper Award in 2019 Dr. Hespanha has successfully mentored over 25 PhD students who have gone on to prominent positions in academia and industry. His research has been consistently supported by substantial funding from NSF, NIH, ONR, and other agencies, with current projects including pandemic management decision systems, precision drug delivery, and control of autonomous vehicle networks. He has taught numerous influential courses including Linear Systems Theory and Noncooperative Game Theory, authoring widely used lecture notes published by Princeton Press. Dr. Hespanha leads an active research group within the Center for Control, Dynamical-Systems and Computation, collaborating with researchers across engineering disciplines and biology. His lab maintains strong connections with industry partners working on autonomous systems, communication networks, and biological applications. He has organized major conferences including serving as General Chair for the 9th International Workshop on Hybrid Systems: Computation and Control in 2006, further establishing UCSB as a leading center for control systems research.
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.
Dr. Levent Acar is an Associate Professor in the Department of Electrical and Computer Engineering at Missouri University of Science and Technology. His research focuses on intelligent control systems, neural networks applied to control, hierarchical design of large-scale systems, and distributed computational methods for optimal control. He holds a PhD from The Ohio State University and dual BS degrees in Electrical Engineering and Mathematics from Boğaziçi University. Education: PhD in Electrical Engineering, The Ohio State University MS in Electrical Engineering, The Ohio State University BS in Electrical Engineering, Boğaziçi University BS in Mathematics, Boğaziçi University Research Interests: Intelligent control of functional systems Neural networks applied to control Hierarchical design and control of large-scale systems Optimal and suboptimal control for interconnected systems Distributed computational methods for optimal control Research Trends: Dr. Acar’s recent work emphasizes robotics and sensor integration, particularly in UAV formations, mobile robot formations, and chemical source detection using neural networks. His contributions bridge theoretical control systems with practical applications in environmental and medical engineering. Professional Activities: Member of IEEE, Control Systems Society Member of the New York Academy of Sciences Former Research Associate at NIST’s Intelligent Systems Division
Jeffrey F. Kelly, PhD is a Professor and Director of the School of Biological Sciences at the University of Oklahoma. His research focuses on Aeroecology, Ornithology, and the ecological impacts of artificial light at night. He leads projects on climate-driven avian migration patterns, light pollution, soundscapes, and microplastics, funded by NSF, USGS, and The Nature Conservancy. Recent work includes studies on nocturnal migration behavior and radar-based ecological monitoring. Education: Ph.D., Biology, Colorado State University M.S., Biology, Oklahoma State University B.S., Wildlife Biology, University of Maine Key Research Themes: Migratory connectivity and avian behavior Aerial habitat use and conservation Technological innovations in ecological tracking Grants & Awards: National Science Foundation (NSF) U.S. Geological Survey (USGS) The Nature Conservancy Labs/Teams: Aeroecology Research Group Avian Migration Dynamics Lab
Dr. James Bennett is a Post-doctoral Research Fellow in the ARC Centre of Excellence for the Mathematical Analysis of Cellular Systems (MACSYS) at Queensland University of Technology (QUT). He holds a PhD from The University of Queensland (UQ), supervised by Prof. Warwick Bowen, Prof. Halina Rubinsztein-Dunlop (AO, FAA), and Dr. Lars Madsen. His research bridges physics and mathematics, focusing on applying data-driven models to understand complex biological systems. Prior to MACSYS, he specialized in quantum mechanics using optomechanical oscillators and developed magnetic field sensors with applications in navigation and through-earth communication. His academic affiliations include the Faculty of Science and School of Mathematical Sciences at QUT. Bennett teaches Aspects of Computational Science and has prior teaching experience in linear algebra, mechanics, and calculus at Griffith University and UQ. He collaborates with industry partners such as Orica, Defence Science & Technology, and NASA Glenn Research Center on magnetometer technologies for aerospace and mining applications. Education: BSc (Hons I) in Physics, UQ PhD in Physics, UQ Research Interests: Quantum optomechanics Magnetometry for aerospace and environmental applications Mathematical modeling of cellular systems Teaching: Current: Aspects of Computational Science (QUT) Past: Linear Algebra, Mechanics, Calculus (Griffith University) Bennett’s work in MACSYS addresses the interplay between mathematical principles and biological complexity, aiming to uncover foundational biological mechanisms. His publications span optomechanical systems, quantum state manipulation, and sensor technology innovations.
Dr. Pantelis Sopasakis is a Lecturer in the School of Electronics, Electrical Engineering and Computer Science at Queen's University Belfast, Northern Ireland. His research focuses on developing efficient numerical optimization algorithms and model predictive control (MPC) methodologies for uncertain systems, with applications in autonomous vehicles, smart infrastructure networks, and advanced manufacturing. He leads projects on embedded optimization solvers, GPU-accelerated MPC, and stochastic control for systems like water networks and microgrids. His work emphasizes real-time implementation and safety-critical applications in robotics and energy systems. He teaches postgraduate and undergraduate courses in control theory and signals, and is actively involved in supervising PhD students in areas like parallel algorithms and MPC for uncertain systems. Key achievements include the development of the Open-Source Optimization Engine , widely used for embedded MPC. Research interests span distributed embedded intelligence, intelligent uncertain-aware MPC, and biomedical applications of control systems. He collaborates internationally on projects involving risk-averse control, multi-agent systems, and circular economy applications. His interdisciplinary work bridges optimization theory, robotics, and energy systems, with a focus on scalable and real-time solutions. Teaching includes modules on control systems fundamentals and advanced MPC concepts, supported by his textbook Control Systems: An Introduction . Dr. Sopasakis has contributed to over 50 publications, with recent work on conformal prediction for stochastic control, distributed collision avoidance, and thermodynamical material networks. He participates in conferences and editorial activities, and has organized events like the 2025 IEEE UK and Ireland Robotics Conference. His research group is part of the Energy, Power, and Intelligent Systems and Control clusters at Queen's.
Péter Korondi is a Professor at the University of Debrecen in Hungary, affiliated with the Department of Electrical Engineering and Mechatronics . His work spans robotics, control theory, and industrial automation, with a focus on bio-inspired systems and human-robot interaction. Research Interests : Robotics, Mechatronics, Control Theory, Human-Robot Interaction, Industrial Automation, Sensor Fusion Recent Article Trends : Sliding mode control, friction compensation in micro-telemanipulation, path planning for mobile robots, smart industrial systems Collaborations : Co-authored works with Gabor Sziebig, Ferenc Tajti, Géza Szayer, and international researchers in IEEE Transactions , Sensors , and Acta Polytechnica Hungarica . Technological Focus : Development of rehabilitation devices, holonomic drive systems, and ethorobotics models inspired by animal behavior.
