A. Stephen Morse is the Dudley Professor of Electrical & Computer Engineering at Yale University. He has been affiliated with Yale since 1970 and holds memberships in prestigious organizations such as the National Academy of Engineering and the Connecticut Academy of Science and Engineering. His research focuses on control systems, including hybrid systems, network science, multi-agent coordination, and sensor networks. He has received numerous awards, including the Bellman Control Heritage Award (2013) and the IEEE Technical Field Award (1999). Morse earned his BSEE from Cornell University, MS from the University of Arizona, and PhD from Purdue University. His work emphasizes logic-based switching, vision-based control, and distributed algorithms for autonomous systems. He has contributed to foundational papers on multi-agent consensus and formation control, as well as sensor network localization. Current projects include swarming dynamics and reactive control strategies for autonomous vehicles. His scientific contributions span over 200 publications, with recent work addressing distributed control algorithms, climate impact modeling, and game-theoretic network analysis. Morse advises graduate students like Ming Cao and Jia Fang, and his research group explores cutting-edge topics in systems theory and robotics.
Tove Hels is an Associate Professor in the Department of the Built Environment at the Faculty of Engineering and Science, Aalborg University, Denmark. She is a key member of the Traffic Research Group, focusing on transportation safety, road user behavior, and traffic policy. Her work bridges engineering, public health, and social science to improve road safety outcomes. Research Interests: Her research spans traffic safety, cyclist-motorist interactions, speed enforcement, accident risk modeling, and the impact of vehicle technologies. She investigates both infrastructure design and behavioral factors influencing road safety, with a strong emphasis on data-driven analysis and policy evaluation. The recent publications reveal a consistent focus on improving cyclist safety through infrastructure (e.g., advanced stop boxes, roundabout design), addressing under-reporting of traffic injuries, and evaluating behavioral interventions for speeding. Her work integrates epidemiological methods, statistical modeling, and real-world policy applications. Scientific Contributions: Principal Investigator in the Danmarks Trafikulykker cohort study (2025–2029) Project participant in EASE: Intervention against speed offenders (2019–2025) Author of over 29 research outputs including journal articles, reports, and policy briefs Frequent contributor to national media and advisory bodies like Dansk Vejforening Advising and Grants: While no formal students are listed, her leadership in major funded research projects indicates a supervisory role in training junior researchers. She has secured and contributed to significant research grants related to traffic safety monitoring and intervention evaluation. Labs and Teams: She is part of the Traffic Research Group at Aalborg University, collaborating closely with researchers such as H. Lahrmann, T.K.O. Madsen, and A.V. Olesen. The group conducts field studies, data linkage projects, and policy evaluations with national impact.
Dr. Cheng-Chew Lim is a Professor in the School of Electrical and Mechanical Engineering at the University of Adelaide. He specializes in control theory, autonomous systems, and multi-agent reinforcement learning. His research focuses on trusted autonomous systems, secure cyber-physical networks, and decentralized decision-making models. He has published over 300 articles and supervised 50+ PhD and master’s students. Dr. Lim teaches courses in control systems, autonomous systems, and engineering project management. He has held editorial roles, including Associate Editor for IEEE Transactions on Systems, Man, and Cybernetics, and is actively involved in professional associations like the IEEE Control and Aerospace Electronic Systems Joint Chapter. His current projects include physics-informed neural networks for medical imaging, secure distributed autonomous systems, and resilient formation control under cyberattacks. Dr. Lim has secured research grants from ARC and industry partnerships, emphasizing practical applications in robotics, cybersecurity, and smart systems.
Luyang Zhao is an incoming tenure-track Assistant Professor in the Department of Electrical and Computer Engineering at Clemson University (starting August 2025). He earned his PhD in Computer Science and double undergraduate degrees in Computer Science and Mathematics from Dartmouth College and the University of Minnesota respectively. Academic Affiliation : Clemson University (Assistant Professor) Education : PhD in Computer Science (Dartmouth College), BS in Computer Science & Mathematics (University of Minnesota) His research focuses on Robotics , particularly soft robotics, modular systems, and bio-inspired designs. Key areas include: Large Language Models for robotic design automation Modular tensegrity systems for self-assembling structures Swarm coordination strategies Multi-environment adaptability (land/aquatic/aerial) Simulation tool integration for design optimization Recent publications highlight his work on SoftSnap modular platforms, LLM-driven swarm intelligence, and bioinspired dolphin robots. He received the Neukom Outstanding Graduate Research Prize for his contributions. Industry Experience : Research internships at Amazon Robotics and TuSimple Mentorship : Advised 6+ graduate/undergraduate researchers Open-Source Contributions : Developed SoftSnap platform for rapid prototyping Academic Service : Workshop co-organization (IROS 2023), peer reviewing (RA-L, ICRA, IROS, RoboSoft, BioRob)
Awi Federgruen is the Charles E. Exley Professor of Management and Chair of the Decision, Risk, and Operations (DRO) Division at Columbia University’s Graduate School of Business. He joined Columbia’s faculty in 1979 after earning his DSc in Operations Research from the University of Amsterdam and holding roles as a Research Fellow at the Mathematical Centre in Amsterdam and faculty member at the University of Rochester. He also holds a courtesy appointment in Columbia’s School of Engineering and Applied Sciences. Education: BA, University of Amsterdam, 1972 MS, University of Amsterdam, 1975 DSc (Operations Research), University of Amsterdam, 1978 Research Interests: Federgruen’s work focuses on optimizing supply chain and service systems through advanced operations research methodologies. Key areas include supply chain coordination, inventory management under uncertainty, service system design, and dynamic pricing. His theoretical contributions span applied probability, queuing models, and dynamic programming. Recent applications include pharmaceutical supply chains, healthcare operations, and vaccine distribution strategies. Awards & Recognition: 2004 Distinguished Fellowship Award (MSOM Society) INFORMS Presidential Fellow (highest honor) National Science Foundation & ARPA grants Consulting & Industry Impact: Federgruen advises companies in pharmaceuticals, consumer electronics, and logistics. Notably, he developed marketing mix models for the pharmaceutical industry and advised the Israeli Air Force on logistics policies. His work bridges academic theory with real-world applications in industries like retail, healthcare, and transportation. Editorial Roles: Editor-in-Chief of Naval Research Logistics ; former Departmental Editor for Manufacturing & Service Operations Management and Associate Editor of Operations Research .
Ran Dai is a Professor in the Department of Aeronautics and Astronautics at Purdue University's College of Engineering. His research focuses on optimal control theory, trajectory optimization, and robotics applications, with an emphasis on aerospace systems and energy-efficient solutions. He leads the Autonomous Optimization Lab (AOL) and has contributed extensively to advancements in learning-based control, mixed-integer programming, and deployable space systems. His work spans applications such as spacecraft guidance, unmanned vehicle path planning, and energy management for solar-powered systems. Notable contributions include algorithms for fuel-optimal powered descent, real-time trajectory optimization, and origami-inspired deployable mechanisms. He holds a Ph.D. in Aerospace Engineering and has published over 100 peer-reviewed articles. Research interests include: Optimal control and trajectory optimization Reinforcement learning for decision-making Autonomous systems and robotics Energy-efficient aerospace engineering Recent work emphasizes meta-reinforcement learning frameworks and adaptive optimization engines for complex systems.
Maria Paz Linares Herreros is a Lecturer at the Universitat Politècnica de Catalunya (UPC), affiliated with the School of Mathematics and Statistics (FME) and the Department of Statistics and Operations Research. She is a member of the IMP (Information Modeling and Processing) research group and collaborates with inLab FIB on intelligent transportation systems. Research interests: Transportation systems, smart cities, traffic simulation, data-driven modeling, environmental impact assessment Specializes in applying machine learning and simulation to urban mobility challenges Her recent publications focus on: Parking availability prediction using deep learning Traffic emission modeling linked to urban policies Dynamic ride-sharing system optimization Integration of IoT data in transportation planning Scientific recognition: Recipient of the IV International Award on Transport Infrastructure Management Research (2018) Active contributor to projects like CitScale and Virtual Mobility Lab Collaborator in European initiatives like KIC Urban Mobility
Dr. Hakki Erhan Sevil is an Associate Professor in the Department of Intelligent Systems and Robotics at the University of West Florida, within the Hal Marcus College of Science and Engineering. He holds a Ph.D. in Mechanical Engineering from the University of Texas at Arlington and has extensive research experience in robotics, intelligent systems, and autonomous control. His work spans theoretical and applied domains, focusing on resilient and intelligent robotic systems. Ph.D., Mechanical Engineering, University of Texas at Arlington M.S., Mechanical Engineering, Izmir Institute of Technology B.S., Mechanical Engineering, Izmir Institute of Technology Dr. Sevil's research interests lie at the intersection of robotics, artificial intelligence, and control systems. He specializes in autonomous navigation, fault detection and isolation (FDI), multi-agent coordination, computer vision, and bio-inspired computational methods. His work emphasizes real-world implementation in unmanned and self-sustained systems, particularly in challenging environments. His recent publications and projects highlight a strong trend toward intelligent, resilient, and distributed robotic systems. Themes include entropy-based behavior modeling for UAV swarms, assistive robotics for household tasks, post-disaster damage assessment using aerial vision, and advanced guidance for GPS-denied navigation. These reflect a multidisciplinary approach combining machine learning, control theory, and robotics engineering. 2024 Faculty Excellence in Teaching Award, UWF 2024 Faculty Excellence in Undergraduate Research Mentoring Award, UWF DURIP Grant ($478,000) from ONR (with IHMC) USDA Grant ($728,000) with New Mexico State University US Air Force SBIR/STTR Grant ($110,000) with Catalano Aerospace AFWERX Funding for Distributed Behavior Research Dr. Sevil actively mentors Ph.D. and M.S. students and leads the Sevil Research Group, which has secured multiple internal and external grants from NSF, NASA, ARL, ONR, and USDA. He has served as PI and Co-PI on funded projects and advises student teams that have won national awards. His lab, the Intelligent Systems and Robotics Lab, is highlighted in university communications and national challenges. The group collaborates with IHMC, NMSU, and industry partners, fostering innovation in autonomous systems. The Sevil Research Group operates within the Intelligent Systems and Robotics Lab at UWF, conducting cutting-edge research in autonomous navigation, swarm intelligence, and resilient robotics. The lab collaborates with the Institute for Human and Machine Cognition (IHMC), New Mexico State University, and private aerospace firms. It supports student-led projects, participates in national robotics challenges, and maintains active GitHub repositories for open research dissemination.
Dr. Clark N. Taylor is an Associate Professor of Computer Engineering and Director of the ANT Center at the Air Force Institute of Technology (AFIT), located at Wright-Patterson Air Force Base, Ohio. He is actively engaged in research and education within the Graduate School of Engineering and Management, focusing on advanced navigation and sensor fusion technologies for autonomous systems. Ph.D., Electrical and Computer Engineering (Computer Engineering), University of California, San Diego, 2004 M.S., Electrical and Computer Engineering, Brigham Young University, 1999 B.S., Electrical and Computer Engineering, Brigham Young University, 1995 Dr. Taylor's research spans computer engineering, navigation systems, and autonomous robotics, with a strong emphasis on sensor fusion, state estimation, and robust uncertainty modeling. His work integrates vision, inertial, magnetic, and pressure sensors for navigation in GPS-denied environments, particularly for unmanned aerial vehicles (UAVs). He is a leading expert in factor graph-based estimation, visual-inertial odometry, cooperative localization, and magnetic navigation. His publications demonstrate a consistent trend toward robust, uncertainty-aware estimation frameworks. Over the past decade, his research has evolved from early work on visual stabilization and pose estimation to advanced topics such as conservative covariance estimation, invariant filtering, and machine learning for spacecraft pose estimation. His recent articles focus on factor graphs, multi-agent fusion, and deep learning, indicating a trajectory toward intelligent, resilient navigation systems for defense and aerospace applications. Scientific awards include a Best Presentation in Session award at the ION GNSS+ conference in 2021. His research is supported by the U.S. Air Force and related defense agencies, with applications in surveillance, autonomous refueling, and on-orbit inspection. Dr. Taylor has advised numerous MS and PhD students, particularly in the areas of UAV navigation, sensor fusion, and cooperative localization. His lab, the ANT Center, focuses on advanced navigation and tracking, bringing together students and researchers to develop cutting-edge solutions for real-world operational challenges. The team conducts both simulation and experimental work, often integrating novel sensor modalities and estimation algorithms for improved system performance.
Dr. Erika Marsillac is Dean and Professor of Supply Chain Management at Old Dominion University's Strome College of Business. She has led research and taught internationally since 2004, specializing in sustainable supply chains, renewable energy systems, and international partnerships. Her leadership includes overseeing academic programs and research initiatives focused on logistics, sustainability, and business innovation. Education: Ph.D. in Manufacturing Management, University of Toledo (2010) M.B.A. in Information Technology, Goldey-Beacom College (2002) M.B.A. in Comprehensive General MBA, Goldey-Beacom College (2000) B.A. in Psychology, Pennsylvania State University (1992) Research Focus: Dr. Marsillac's work centers on integrating sustainability into global supply chains, with emphasis on photovoltaic systems, circular economy models, and automotive industry transformations. She investigates variability in production systems, renewable energy infrastructure, and strategies for mass customization. Publication Trends: Her recent articles emphasize renewable energy supply chains (particularly photovoltaics), queueing theory applications in manufacturing, and sustainable operations. Methodologies include case studies, simulation modeling, and bibliometric analysis. Awards & Fellowships: EV Williams Fellowships for Service & Teaching (2022) Outstanding Faculty Service Award (2021) Provost Fellowship (2021) Distinguished Alumni Award (2015) Grants & Projects: Secured $368,600+ in funding for renewable energy and educational initiatives, including solar tracking systems, photovoltaic facilities, and business pedagogy enhancements.
Farshad Arvin is a Professor of Robotics in the Department of Computer Science at Durham University. Prior to this, he held academic positions at The University of Manchester (2018-2022) and worked as a Research Assistant at the University of Lincoln (2012-2015). He holds a BSc in Computer Engineering (2004), an MSc in Computer Systems Engineering (2010), and a PhD in Computer Science (2015). His research focuses on Swarm Robotics , Bio-inspired Swarms , and Autonomous Multi-agent Systems . He pioneered the Swarm & Computation Intelligence Laboratory (SwaCIL) at Durham, leading projects like H2020-FET RoboRoyale (€3.27M), Horizon Europe Sensorbees (€3.2M), and BioDiMoBot (€8M), with total funding exceeding £4M. Recent publications highlight advancements in swarm trajectory optimization (T-STAR), collision-free multi-robot coordination, and bio-hybrid environmental monitoring. His work integrates bio-inspired algorithms with practical applications in autonomous vehicles, aerial drones, and hazardous environments. Scientific Awards: Marie Skłodowska-Curie fellowship Notable Projects: EU H2020-FET RoboRoyale (2021-2026) Horizon Europe Sensorbees (2024-2029) Horizon Europe BioDiMoBot (2025-2030) H2020-FET Robocoenosis (2020-2025) Supervision: Mentors 8 postgraduate students at Durham, including Hanadi Alhamdan, Hang Wang, and Honghao Pan.
Helen Oleynikova is a Lecturer at the Department of Mechanical and Process Engineering at ETH Zürich, where she is part of the Autonomous Systems Lab. She works on the intersection of perception and planning, particularly for micro-aerial vehicles. Her research focuses on real-time onboard mapping, planning, and localization using visual-inertial systems and signed distance fields. Research Interests: Helen's work spans robotics, autonomous systems, and computer vision, with a focus on enabling safe and efficient navigation in complex environments. She specializes in visual-inertial odometry, SLAM, 3D mapping using signed distance fields, and real-time path planning for MAVs. Her projects often involve embedded systems and FPGA-based high-speed vision for obstacle avoidance. Publication Trends: Her recent publications (2023–2019) show a consistent focus on real-time, onboard algorithms for autonomous navigation. Key themes include signed distance function maps, collision-free motion generation, global localization, and efficient exploration. She frequently publishes in top-tier robotics conferences such as ICRA and IROS, and journals like IEEE RA-L and Journal of Field Robotics. Professional Experience: Senior Researcher, Autonomous Systems Lab, ETH Zürich Senior Software Engineer, Isaac 3D Perception, Nvidia Senior Scientist, Microsoft Mixed Reality and AI Lab, Zürich Software Engineer, Google (StreetView) Contributor, Willow Garage (ROS, TurtleBot Arm) Education: PhD in Robotics, ETH Zürich (2019) MSc in Robotics, ETH Zürich BSc in Robotics, Olin College of Engineering (2011) Advising and Grants: While no formal students are listed, she has collaborated extensively with researchers at ETH Zürich and industry labs. Her work has been supported through institutional affiliations and industry research roles. She has contributed to open-source robotics software, particularly in ROS-based systems for manipulation and navigation. Labs and Teams: Helen is a key member of the Mobile Manipulation team at the Autonomous Systems Lab at ETH Zürich. She has also been involved in projects at Nvidia, Microsoft, Google, and Willow Garage, focusing on real-world deployment of autonomous systems.
Enrico Macii is a Full Professor at the Politecnico di Torino, affiliated with the Interuniversity Department of Regional and Urban Studies and Planning (DIST) and the Department of Control and Computer Engineering (DAUIN). He leads the Electronic Design Automation (EDA) research group and holds key roles as Scientific Advisor for the Politecnico-STMicroelectronics partnership and Scientific Contact for the European Chips Joint Undertaking. Research Interests: His work spans digital circuits and systems, energy efficiency, smart cities, Industry 4.0, and smart manufacturing. He focuses on embedded and cyber-physical systems, low-power design, neuromorphic computing, AIoT, and sustainable urban development. Recent Publications: His recent research demonstrates strong trends in edge AI, neuromorphic computing, and smart energy systems. Articles highlight innovations in low-power hardware acceleration, federated learning, physics-informed AI, and digital twin applications for urban and industrial systems. There is a clear emphasis on deploying AI efficiently on constrained devices and integrating physical models with machine learning. J. William Fullbright Fellowship (1993) Best paper award IEEE European Design Automation Conference (1996) Best paper award ACM/IEEE Great Lakes Symposium on VLSI (2008) DAC Service Award (2014) IEEE Fellow (2006) DATE Fellow (2014) Advising and Grants: He has supervised over 25 PhD students in computer engineering, AI, and urban systems. His research is funded by major EU programs (Horizon 2020, PNRR, KDT JU), national (PRIN, FAR), and regional grants, as well as industrial contracts with STMicroelectronics, Michelin, and Cefriel. He leads numerous high-impact projects in smart manufacturing, energy efficiency, and digital twins. Labs and Teams: He is a core member of the EDA Group, an interdepartmental research team at Politecnico di Torino focusing on VLSI-CAD, bioinformatics, smart cities, and Industry 4.0. He also contributes to IAM@PoliTo (Integrated Additive Manufacturing) and leads multiple EU and national research consortia.
Prof. Dr.-Ing. Frank Thielecke is a full Professor and the head of the Institute of Aircraft Systems Engineering (Flugzeug-Systemtechnik) at Technische Universität Hamburg (TUHH), Germany. His research is centered on advanced aircraft systems, avionics, flight control, and the integration of emerging technologies such as hydrogen and hybrid-electric propulsion. Institution: Technische Universität Hamburg Department: Institute of Aircraft Systems Engineering (Flugzeug-Systemtechnik) Email: frank.thielecke@tuhh.de Office: Neßpriel 5, Room 1.012, 21129 Hamburg His research interests include integrated modular avionics (IMA), model-based systems engineering (MBSE), aircraft load estimation, health monitoring, fault diagnosis, and sustainable aviation technologies. He leads a research group actively contributing to next-generation aircraft design, with a strong focus on digitalization, virtual testing, and system safety. The recent publications highlight a consistent trend in developing model-based tools and architectures for avionics and aircraft systems. Key themes include the design of IMA platforms, virtual integration, system validation, hydrogen aircraft systems, and control algorithms for UAVs and flexible aircraft. His work frequently appears in AIAA, DASC, DLRK, and CEAS conferences and journals. Prof. Thielecke has been involved in numerous collaborative research projects focusing on more-electric aircraft, fuel cell systems, and advanced actuation. He has contributed to the development of frameworks such as ASHLEY and SArA for avionics platform design and systems architecting. His team also works on noise reduction in hydraulic systems and condition monitoring for aircraft subsystems. He supervises a group of researchers and PhD students, many of whom co-author his publications. While specific student names are not listed, long-term collaborators like Oliver Luderer, Thimo Bielsky, Nils Külper, and Philipp Chrysalidis are likely doctoral candidates or postdoctoral researchers in his group. He has secured funding for projects related to hydrogen aircraft, hybrid propulsion, and digital avionics engineering. His lab, the Institute of Aircraft Systems Engineering, operates test benches for avionics, hydraulic systems, and flight control validation. The team uses advanced simulation, co-simulation (e.g., FMI), and hardware-in-the-loop techniques for virtual integration and testing. Ongoing work includes the development of tools for early validation of flight control platforms and automated requirement-based testing.
Dong Ngo Duy is an Associate Professor in the Department of Civil & Environmental Engineering at Monash University, where he serves as the Head of the Transport Section. He holds a PhD in Traffic Flow Theory and Simulation from Delft University of Technology and has held academic positions at the University of Leeds (UK), University of Canterbury (NZ), and now Monash University (Australia). PhD, Traffic Flow Theory, Technische Universiteit Delft (2006) MSc, Traffic Engineering, Linköpings Universitet (2002) His research focuses on Connected and Autonomous Vehicles (CAVs) , Traffic Flow Theory , Data Fusion , and Urban Network Optimization . He applies AI and machine learning to model, predict, and control multi-modal traffic systems, aiming to develop smart city platforms for sustainable transport in mega-cities. The recent trend in his publications (2022–2025) reflects a strong focus on intelligent transportation, including trajectory planning, risk-aware control, car-following modeling using neural symbolic regression, and intercity mobility analysis. His work bridges theoretical modeling with practical applications in emerging connected environments. Scientific Awards: UK Research Council (EPSRC) Advanced Fellow Award (2011–2016) in Connected and Autonomous Vehicles Dong Ngo Duy actively supervises PhD students and contributes to major research initiatives in intelligent transport systems. His work aligns with UN Sustainable Development Goals, particularly in sustainable cities and transport. He previously chaired the Connected Traffic Systems Lab at the University of Canterbury and continues to lead impactful research in transport innovation.
