Giovanna Di Marzo Serugendo is a researcher affiliated with the University of Geneva (Faculty of Social Sciences, Centre for Informatics) and the Institute of Information Service Science (ISS) . Her work spans semantic technologies, agent-based modeling, and sustainable systems. Research interests focus on Semantic knowledge graphs for regulatory compliance Ontology-driven resource management Self-organizing systems inspired by biological models AI applications in smart grids and urban mobility Digital agriculture platforms for smallholder farmers Recent publications highlight trends in ontology automation using LLMs, agent-based simulations for urban planning, and KG-enhanced compliance frameworks . She leads projects integrating digital twins with smart energy systems and develops bio-inspired coordination paradigms. Supervised works include 17 research projects in these domains. Current technical reports and conference papers explore cybersecurity-safety interdependencies in autonomous vehicles and decentralized event source detection in sensor networks.
Daxin Tian is a prominent professor at Beihang University's School of Transportation Science and Engineering, specializing in intelligent transportation systems and vehicular networks. With over 170 publications spanning from 2006 to 2025, his research has significantly contributed to the advancement of connected and autonomous vehicle technologies. His work appears consistently in top-tier IEEE journals including IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Intelligent Vehicles, and IEEE Internet of Things Journal, establishing him as a leading authority in the field. Professor Tian's research interests encompass several critical areas in modern transportation technology: Connected and Autonomous Vehicle Systems Vehicular Networking and Communication Protocols Vehicle Platooning and Cooperative Driving Algorithms Edge Computing Applications for Transportation Computer Vision for Autonomous Driving Perception Traffic Flow Optimization and Prediction Models Resource Allocation in Vehicular Networks His recent publications demonstrate an increasing sophistication in addressing complex multi-vehicle scenarios while maintaining practical considerations like communication reliability, energy efficiency, and safety constraints. The research trajectory shows a clear evolution from foundational networking and control problems toward more integrated AI-driven solutions that combine computer vision, natural language processing, and advanced control theory for next-generation transportation systems. Professor Tian maintains extensive international collaborations, particularly with researchers at Canadian institutions including Victor C. M. Leung's group, while leading a substantial research team at Beihang University. His work frequently bridges theoretical advances with practical transportation challenges, resulting in numerous high-impact publications that address real-world implementation barriers in intelligent transportation systems.
Devki Nandan Jha is a researcher specializing in Internet of Things (IoT) , Cloud/Edge Computing , and Cybersecurity . His work focuses on runtime monitoring, security frameworks, and deployment optimization in heterogeneous environments. Collaborations include institutions across Europe and Asia, with frequent co-authorship with Rajiv Ranjan, David Wallom, and David Blundell.
Claire Dune is an Assistant Professor at the University of Toulon, affiliated with the COSMER Laboratory (Mechanical and Robotic Systems Design Laboratory). Her research focuses on robotics, computer vision, and underwater systems, with applications in environmental monitoring and human-robot interaction. She teaches computer science, numerical methods, image processing, and visual servoing. Institution: University of Toulon Laboratory: COSMER (Mechanical and Robotic Systems Design Laboratory) Academic Rank: Assistant Professor Email: claire.dune@univ-tln.fr Her research centers on perception for robot control, particularly in underwater robotics and computer vision. Key interests include visual servoing, SLAM, gesture recognition for diver-robot interaction, and autonomous capabilities in real-world marine environments. She applies deep learning and sensor fusion techniques to enhance underwater visual perception and navigation. The recent publications demonstrate a strong trend in underwater robotics, with focus areas including tether dynamics (catenary modeling), ROV localization using umbilicals and IMUs, long-term visual localization in deep-sea environments, and color restoration in underwater imagery. Her work bridges theory and real-world application, contributing datasets like 'Eiffel Tower' for benchmarking and advancing multi-agent SLAM systems. Claire Dune has contributed to leading journals such as IEEE Robotics and Automation Letters, Ocean Engineering, and The International Journal of Robotics Research. Her editorial and survey work highlights her leadership in the domain of deformable object manipulation. Retrieval of benthic habitat abundance and bathymetry from hyperspectral data (DESIS) in shallow waters ROV localization using ballasted umbilical equipped with IMUs MAM3SLAM: Towards underwater robust multi-agent visual SLAM Eiffel Tower: A Deep-Sea Underwater Dataset for Long-Term Visual Localization Challenges and Outlook in Robotic Manipulation of Deformable Objects Claire Dune actively collaborates with researchers such as Vincent Hugel, Juliette Drupt, and Andrew Comport. She has supervised or co-supervised numerous research projects and publications, particularly in underwater robotics and assistive technologies. Her work involves experimental robotics and system integration, often validated in real marine environments. She leads research in the COSMER laboratory focused on underwater robotics, including projects on tethered ROVs, diver-robot communication via gesture recognition, and environmental monitoring using visual and hyperspectral data. Her team develops practical solutions for marine science and offshore operations, emphasizing robustness and autonomy.
Jorge Manuel M. C. Pereira Batista is an Associate Professor at the Department of Electrical and Computer Engineering , University of Coimbra, Portugal. He serves as a senior researcher at the Institute for Systems and Robotics (ISR-UC) and leads the Computer Vision Group. His career spans academic roles, research coordination, and industry collaboration. Academic Affiliation: University of Coimbra (Electrical & Computer Engineering Department) Research Institute: Institute for Systems and Robotics (ISR-UC) His research focuses on Computer Vision , Pattern Recognition , and applications of Differential Geometry in these fields. Key subdomains include facial analysis, visual surveillance, real-time vision systems, and machine learning integration. From 2010–2023, his recent publications highlight advancements in probabilistic models , transformer architectures , multi-branch learning , and biomimetic robotics . He has coordinated multiple funded projects such as: STORK : Avian protection systems NeuroCity : Intelligent street lighting 4D Facial Dynamics : Identity recognition iTRAFFIC : BRISA highway traffic monitoring His work bridges theoretical innovation (e.g., Riemannian manifold applications) with practical deployments in transportation, energy, and healthcare sectors.
Dr. Shunqiao Sun is an Assistant Professor in the Department of Electrical and Computer Engineering at The University of Alabama, College of Engineering. He joined the faculty in August 2019 as a tenure-track professor after working at Aptiv’s radar core team in Malibu, California. His research focuses on advanced signal processing, machine learning, and optimization for automotive and MIMO radar systems in autonomous vehicles. Ph.D. : Electrical and Computer Engineering, Rutgers University, 2016 M.S. : Electrical Engineering, Fudan University, 2011 B.S. : Electrical Engineering, Southern Yangtze University, 2004 Dr. Sun's research lies at the intersection of statistical and sparse signal processing , mathematical optimization , and machine learning , with applications in automotive radar , MIMO radar , and autonomous driving . His work emphasizes sparsity-oriented frameworks, AI-powered radar perception, and high-resolution 4D sensing. He leads a dynamic research group focused on next-generation radar technologies for intelligent transportation systems. His recent publications demonstrate a strong trend in deep learning for radar signal recovery , collaborative radar imaging , direction-of-arrival estimation with sparse arrays , and integrated sensing and communication . Several of his papers are among the most downloaded and cited in IEEE journals, including top articles in IEEE Signal Processing Magazine and IEEE Journal of Selected Topics in Signal Processing. Scientific Awards and Honors: NSF CAREER Award (2024) NSF CRII Award (2022) IEEE AESS Robert T. Hill Best Dissertation Award (2016) Best Student Paper Award at IEEE SAM Workshop (2020) Rutgers ECE Academic Achievement Award (2015–2016) University of Alabama Hewson Engineering Faculty Fellow (2025) Dr. Sun is actively involved in academic service and leadership. He is an Associate Editor for IEEE Signal Processing Letters and IEEE Open Journal of Signal Processing . He serves as Vice Chair of the IEEE Signal Processing Society’s Autonomous Systems Initiative and is an elected member of the IEEE Sensor Array and Multichannel (SAM) Technical Committee and the Integrated Sensing and Communication (ISAC) Technical Working Group. He has co-organized numerous workshops and special sessions at ICASSP, EUSIPCO, and IEEE Radar Conference. His lab has secured significant research funding from the National Science Foundation , NXP Semiconductors , MathWorks , and NOAA . He mentors multiple Ph.D. students, several of whom have interned at leading industry labs such as NXP and GM Cruise. He has co-organized the Workshop on Signal Processing for Autonomous Systems (SPAS) at ICASSP and EUSIPCO and delivered invited seminars at institutions including TU Delft, UC Davis, and Lehigh University.
Prof. Rolf Findeisen is a Professor in the Department of Control and Cyber-Physical Systems (CCPS) at Technische Universität Darmstadt. His work focuses on advancing control theory and its applications in cyber-physical systems, autonomous systems, and energy storage systems. Key areas include model predictive control (MPC), battery management systems, machine learning integration into control frameworks, and optimization of crystallization processes. He leads research on safety-critical systems, data-driven control methods, and interdisciplinary applications in robotics and biotechnology. His research spans theoretical advancements in MPC stability, stochastic control, and Gaussian process modeling, alongside practical implementations in autonomous vehicles, lithium-ion battery systems, and bioprocess optimization. Notable contributions include frameworks like HILO-MPC for integrating machine learning with control systems, and methodologies for safe exploration in autonomous navigation. Prof. Findeisen's publications emphasize energy-efficient trajectory planning, fault detection in battery systems, and real-time optimization of manufacturing processes. His work bridges academic theory with industrial applications, addressing challenges in scalability, safety, and computational efficiency. His lab collaborates on national projects like IN-Fly-Tec and INFLIGHT, focusing on innovative flight control systems and sensor technologies. Current research trends include hybrid intelligent optimization, cybergenetic control of microbial systems, and safe reinforcement learning for control systems.
Pablo José Fernández Galdo is a faculty member at the University of A Coruña, affiliated with the University College of Industrial Design and the Department of Civil Engineering. His expertise lies in Engineering Projects, with a strong focus on industrial design, product development, and additive manufacturing. He is an active member of the research group 'Observatorio para el diseño e innovación en movilidad, medios de transporte y automoción', contributing to innovation in transportation and mobility systems. His research interests span Industrial Design , Product Development , Additive Manufacturing , Automotive Design , Urban Furniture , and Smart Mobility . He emphasizes design methodology, sustainability, and user-centered innovation, particularly in educational and real-world applications. His work integrates design with engineering principles to solve contemporary mobility challenges. The recent articles and project concepts reflect a strong trend toward future mobility , including autonomous vehicles, electric transportation, shared urban mobility, and habitat vehicles for sports tourism. Many projects are linked to industry collaborations, especially with SEAT/Cupra, indicating applied research with commercial relevance. There is a recurring focus on design for experience , adaptability , and innovation in public and personal spaces . He has supervised numerous final-year and master's theses, mentoring students in advanced design projects. His collaborative work includes publications in engineering education and service-learning practices, highlighting his commitment to pedagogical innovation. His research has been supported through various R&D contracts with entities such as Fundación PRODINTEC, TELEVES S.A., CTAG, and LOREFAR S.L., demonstrating strong industry engagement. He has contributed to books and journal articles, particularly in the domain of design education and applied engineering. He is involved in designing experimental projects, models, and prototypes, often in collaboration with students and other researchers. His work environment fosters innovation through hands-on workshops and real-world design challenges, especially in the context of sustainable and intelligent mobility solutions.
Kevin Heaslip is a Professor and Director of the Center for Transportation Research in the Department of Civil and Environmental Engineering at the University of Tennessee, Knoxville. He joined the university in 2022, bringing extensive experience from his prior role as Professor and CACI Faculty Fellow at Virginia Tech. Education: PhD in Civil and Environmental Engineering, University of Massachusetts Amherst, 2007 MS in Civil and Environmental Engineering, Virginia Tech, 2003 BS in Civil and Environmental Engineering, Virginia Tech, 2002 Dr. Heaslip's research focuses on the intersection of transportation engineering, intelligent systems, and cybersecurity. His work spans future transportation concepts such as electrified and automated vehicles, transportation operations including freeway and transit management, and cybersecurity for transportation and critical infrastructure. He applies advanced data analytics, machine learning, and cyber-physical systems modeling to real-world challenges in mobility and national security. The recent articles highlight a strong trend in leveraging big data and artificial intelligence for transportation mode detection, traffic event identification, and security risk assessment. His work increasingly integrates cybersecurity into transportation systems, particularly in autonomous and connected vehicles, reflecting the evolving technological landscape and national priorities in infrastructure protection. Scientific Awards and Recognitions: Virginia Tech G.V. Loganathan Faculty Achievement Award for Excellence in Civil Engineering Education (2019) Virginia Tech Favorite Faculty Award (2017) Outstanding Alumni, University of Massachusetts Institute of Transportation Engineers Student Chapter (2015) Outstanding Young Alumni, Virginia Tech Department of Civil & Environmental Engineering (2013-2014) USU Civil & Environmental Engineering Teacher of the Year (2014) USU Civil & Environmental Engineering Undergraduate Research Mentor of the Year (2013) USU Civil & Environmental Engineering Outstanding Researcher (2011, 2012) USU College of Engineering Undergraduate Research Mentor of the Year (2011) Dr. Heaslip has secured over $25 million in research grants and contracts from federal and state governments as well as industry partners. He has advised numerous students and mentored undergraduate researchers, receiving multiple awards for teaching and mentorship. His professional service includes membership in the American Society of Civil Engineers (ASCE), Institute of Transportation Engineers (ITE), and Transportation Research Board (TRB), as well as serving as an Appointed Member of the Resilient America Roundtable of the National Academy of Sciences from 2014 to 2020. He leads the Center for Transportation Research at UT Knoxville, a multidisciplinary lab focused on advancing transportation technologies and policies. The lab's research is organized around three thrusts: future transportation systems (electrified, connected, and automated vehicles), transportation operations (freeway, transit, and corridor management), and cybersecurity of transportation and critical infrastructure.
Yuanchao Xu is an Assistant Professor in the Department of Computer Science and Engineering at the University of California Santa Cruz. He earned his Ph.D. from North Carolina State University, advised by Dr. Xipeng Shen and Dr. Yan Solihin, and is a student researcher at SystemResearch@Google since 2021. His research spans computer architecture, security, and ML systems.
Professor Adam Soule is a faculty member in the Department of Marine Geology and Geophysics at the University of Rhode Island's Graduate School of Oceanography. He also serves as the Executive Director of the NOAA-funded Ocean Exploration Cooperative Institute, a collaborative effort involving the Ocean Exploration Trust, URI GSO, WHOI, University of New Hampshire, and University of Southern Mississippi. Education B.A. from Carleton College (Northfield, MN) Ph.D. from the University of Oregon (Eugene, OR) Research Focus Dr. Soule's research investigates submarine volcanic activity and its impacts on ocean chemistry and ecosystems. His work includes: Developing chemical geochronometers to study eruption dynamics Using numerical fluid dynamics simulations Deploying deep submergence tools like submersibles, ROVs, and autonomous vehicles He emphasizes technological innovation for deep-sea exploration, integrating machine learning techniques to analyze complex geological data.
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.
Tony Lindgren is an Associate Professor at the Department of Computer and Systems Science, Stockholm University, affiliated with the Data Science Research Group and Natural Language Processing Research Group. His work bridges data science and NLP , focusing on interpretable models, constraint programming, and predictive maintenance systems. Research interests include: Machine Learning for explainability and fairness Constraint Programming in maintenance optimization Natural Language Processing for risk analytics and troubleshooting Recent publications demonstrate trends in multi-objective optimization (2025 satellite scheduling), conformal prediction (2024 CoPAL), and fault detection (2024 Automotive Nowcasting). His work often integrates domain-specific constraints with scalable algorithms across applications like food safety and autonomous vehicles. Software tools developed by Lindgren include: Example-based Feature Tweaking Rule Indexing Frameworks His research groups focus on AI-driven decision support for high-stakes domains, combining technical innovation with societal impact considerations.
Fengjunjie Pan is a PhD student and research assistant at the Chair of Robotics, Artificial Intelligence and Embedded Systems at the Technical University of Munich since 2021. He holds an M.Sc. in Electrical Engineering from TU Berlin (2019) and a B.Eng. in Electrical Engineering from Hamburg University of Applied Sciences. His research focuses on automotive systems engineering and generative AI applications in model-based engineering. His publications (2022-2025) demonstrate expertise in: LLM integration for automotive software development Containerized architectures for autonomous driving Virtualization technologies in vehicular systems Constraint generation and model transformation He supervises multiple Master's and Bachelor's theses on generative AI applications and privacy-enhancing technologies in automotive contexts, working alongside Prof. Alois Knoll's team.
