Mubarak A. Shah is a Professor in the Department of Computer Science at the University of Central Florida (UCF) and holds the UCF Trustee Chair. He is affiliated with CREOL, The College of Optics and Photonics, and leads the UCF Center for Research in Computer Vision. His research focuses on advancing computer vision technologies, with applications in image processing, machine learning, and artificial intelligence. Shah’s academic roles include contributing to interdisciplinary research at the intersection of computer science and optics. His work emphasizes computational methods for visual data analysis and has likely influenced advancements in fields such as robotics, medical imaging, and autonomous systems. Though no specific grants, awards, or student advisees are listed here, his position as a Trustee Chair underscores his institutional leadership. The UCF Center for Research in Computer Vision serves as a hub for collaborative projects, fostering innovation in visual computing.
Houssam Abbas is an Assistant Professor in the School of Electrical Engineering and Computer Science at Oregon State University. He holds a Ph.D. in Electrical Engineering from Arizona State University and has professional experience in SoC verification at Intel and postdoctoral research at the University of Pennsylvania. His work focuses on computational ethics for AI agents, design/verification of cyber-physical systems, and autonomous systems like self-driving cars and drones. Education: Ph.D., Electrical Engineering, Arizona State University (2015) M.Sc., Electrical Engineering, Arizona State University (2006) B.Eng., Computer and Communications Engineering, American University of Beirut (2004) Abbas' research integrates deontic logic for ethical obligations in AI, distributed verification techniques for autonomous systems, and fair control algorithms for aerial missions. He co-leads the F1/10 autonomous racing initiative and teaches hands-on courses on self-driving cars. Awards: 2022 NSF CAREER Award 2022 Grainger Foundation Frontiers of Engineering Symposium Participant Grants & Projects: NSF CCRI Grant for F1/10 Racecar platforms (with Penn and Clemson) FAA ASSURE project on UAV cybersecurity Lab/Teams: His work involves the Autonomous Systems Lab , focusing on ethical AI, robotics, and formal verification tools like the F1/10 platform.
Muhammad R. Hajj is the George Meade Bond Professor, Chair of the Department of Civil, Environmental and Ocean Engineering, and Director of the Davidson Laboratory at Stevens Institute of Technology. With a distinguished career spanning over three decades, his expertise lies in nonlinear dynamics , fluid-structure interactions , and energy harvesting , applying these to ship hydrodynamics , biomimetic flight/underwater vehicles , and coastal resilience . He has mentored 32 PhD students and authored over 170 journal publications. Education PhD (1990), MS (1985), Civil Engineering , University of Texas at Austin BE (1983), Civil Engineering (with Distinction) , American University of Beirut Research Interests Dr. Hajj’s work bridges nonlinear dynamics and fluid mechanics to address challenges in structural/aeroelastic stability , bio-inspired design , and renewable energy systems . His fluid-structure interaction studies focus on ship hydrodynamics , transonic flutter , and storm surge prediction , while his energy harvesting research explores piezoelectric systems , self-powered sensors , and biomimetic energy conversion . Recent Trends in Publications His 2022-2021 publications emphasize coastal extreme weather resilience via AI-driven storm surge modeling , bio-inspired robotic fish for underwater energy harvesting , and nonlinear aeroelastic systems to enhance renewable energy extraction . Themes include high-efficiency piezoelectric designs , vortex-induced vibration control , and ultrasonic contactless power transfer , reflecting his commitment to integrating nonlinear dynamics with practical engineering applications . Scientific Honors Fellow, Engineering Mechanics Institute, ASCE Distinguished Civil Engineering Alumni (AUB, 2019) Dean’s Award for Excellence in Research (VT, 2016) Distinguished Leader in Research (VT, 2016) Excellence in Research Award (VT, 2015) Advising and Grants Dr. Hajj has supervised 32 PhD students , many of whom hold prestigious roles in academia and industry. He has secured major grants, including $1.8M from the Department of Energy for floating wave energy converters , $4.94M from the Port Authority for storm surge forecasting , and $200K from the NSF for bio-inspired telemetry energy harvesting .
Brendan Englot is the Anson Wood Burchard Endowed Professor and Director of the Stevens Institute for Artificial Intelligence (SIAI) at Stevens Institute of Technology. He holds a Ph.D., S.M., and S.B. in Mechanical Engineering from MIT. His research focuses on perception, navigation, and decision-making algorithms for mobile robots in complex environments, particularly underwater and autonomous systems. He has held roles such as Professor (2024–present), Associate Professor (2020–2024), and Assistant Professor (2014–2020) at Stevens, and previously worked at the United Technologies Research Center and Yale University. Education: Ph.D., Mechanical Engineering, MIT, 2012 S.M., Mechanical Engineering, MIT, 2009 S.B., Mechanical Engineering, MIT, 2007 Research Interests: Englot’s work emphasizes robust autonomy for unmanned vehicles in degraded conditions, leveraging AI to enhance situational awareness and decision-making under uncertainty. Key areas include navigation algorithms for underwater, aerial, and ground vehicles, sensor fusion, and multi-agent systems. Awards: AMiner’s Top 100 Robotics Scholars (2023, 2024) Provost’s Award for Research Excellence (2021) NSF CAREER Award (2017) ONR Young Investigator Award (2020) Grants & Advising: Englot has secured over $5M in grants as PI, including projects on underwater exploration, reinforcement learning for navigation, and robotic inspection systems. He mentors students in robotics, autonomy, and AI applications. Labs & Teams: Leads the SIAI and collaborates on projects involving autonomous vehicles, SLAM systems, and marine robotics through Stevens’ interdisciplinary initiatives.
Dr. Lei Fan is an Assistant Professor in the Department of Engineering Technology at the University of Houston, with a joint appointment in the Electrical and Computer Engineering (ECE) Department. His research focuses on power system operations, optimization algorithms, quantum computing, and energy storage systems. He holds a Ph.D. from the University of Florida and a B.S. from Hefei University of Technology. Education: Ph.D., University of Florida B.S., Hefei University of Technology Research Interests: Dr. Fan’s work bridges theoretical optimization and practical energy systems, including quantum algorithms for power grid management, battery storage planning, and distributed quantum computing architectures. His LORE (Learning & Operations Research & Energy) lab explores cutting-edge applications in teleoperation, satellite networks, and environmental monitoring. Publications: Recent work emphasizes quantum computing’s role in solving complex optimization problems, such as entanglement routing in satellite networks and distributed hydrogen-power systems. His research also integrates machine learning for methane plume detection and hyperspectral imaging. Labs/Teams: He leads the LORE lab, advancing interdisciplinary research in energy systems and quantum technologies.
Dr. Mohammad Biglarbegian is an Associate Professor in the Department of Mechanical and Aerospace Engineering at Carleton University. Previously, he served as faculty at the School of Engineering, University of Guelph (2011–2023). He is a Professional Engineer (P.Eng.) in Ontario and a Senior Member of IEEE. Education: B.Sc. in Mechanical Engineering, University of Tehran M.A.Sc. in Mechanical Engineering, University of Toronto Ph.D. in Mechanical Engineering, University of Waterloo Research Focus: His work centers on modeling, design, and control of mechatronics systems, including autonomous robotics, vehicles, and machine learning applications. Key areas include data-driven algorithms for autonomous systems, with applications in automation, automotive, and smart agriculture. Grants & Collaboration: Supported by national/international agencies and industry partners, fostering cross-sector collaborations. Currently supervises graduate and undergraduate students in his research lab. Awards: University of Guelph Research Excellence Award (2018)
Garrett Rose is a Professor and Department Head in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville (UTK). He holds a B.S. in Computer Engineering from Virginia Tech (2001), and M.S. and Ph.D. in Electrical Engineering from the University of Virginia (2003/2006). Prior to UTK, he served as Assistant Professor at NYU Polytechnic (2006–2011) and Senior Electronics Engineer at the Air Force Research Lab (2011–2014). His research focuses on nanoelectronic circuit design, neuromorphic computing, hardware security, and memristor-based systems. He leads the SENECA Research Group and the TENNLab initiative, exploring applications in neuromorphic architectures, hardware security primitives (e.g., PUF devices), and device modeling. Recent work emphasizes memristor-driven neuromorphic systems, secure FPGA designs, and in-memory computing. Grants include projects on neuromorphic target detection and nanotechnology-based security solutions. Rose actively mentors students and collaborates on co-design methodologies for real-world neuromorphic applications. Education: Ph.D. Electrical Engineering, University of Virginia, 2006 M.S. Electrical Engineering, University of Virginia, 2003 B.S. Computer Engineering, Virginia Tech, 2001 Research Interests: Dr. Rose’s work spans neuromorphic hardware design, including memristor-based neural networks and spiking systems. He investigates hardware security through nanoscale devices like memristors for PUFs and side-channel resistant circuits. His team develops novel memristor models and explores applications in reconfigurable computing and energy-efficient architectures. Recent efforts focus on neuromorphic vision systems, robotic navigation, and neuromorphic processors with co-design frameworks. Grants & Projects: "Ground-roaming autonomous neuromorphic targeter" (2020) "Secure Backup and Restore for IoT using Nanotechnology" (2020) "Physically Unclonable Reconfigurable Computing System (PURCS)" (2020)
Tønnes Nygaard is an Associate Professor at the Department of Technology Systems, University of Oslo, affiliated with the Faculty of Mathematics and Natural Sciences. His research focuses on evolutionary robotics, morphological adaptation, and embodied artificial intelligence. He leads projects like COCOMO (Co-evolution of Control and Morphologies) and works extensively with the DyRET (Dynamic Robot for Embodied Testing) platform. Key research interests include robot control systems, adaptive morphology design, and real-world implementation of evolutionary algorithms. His work bridges theoretical computer science with practical robotics applications, emphasizing hardware-software co-evolution and embodied cognition principles. Publications span topics like morphological adaptation in quadruped robots, semi-supervised learning for terrain classification, and overcoming convergence issues in multi-objective evolutionary algorithms. Nygaard collaborates internationally and contributes to both academic journals and conferences in robotics and AI. No scientific awards are explicitly listed, though his impactful contributions to real-world evolutionary robotics suggest potential recognition pending explicit mentions. Advising and grant activities are central to his role, though specific student names or grant amounts are not detailed in the provided texts. Labs/Teams: Core contributor to the DyRET project and affiliated with the Section for Autonomous Systems and Sensor Technologies at UiO.
Georgios Andrikopoulos is an Assistant Professor at KTH Royal Institute of Technology's Department of Industrial and Environmental Management (ITM), affiliated with the Digital Futures Faculty. He serves as Co-Principal Investigator (Co-PI) on the 'Real-time exoskeleton control for human-in-the-loop optimization' project, focusing on advanced robotics and human-technology interaction. His research spans soft robotics, exoskeleton systems, and adaptive climbing robots, with applications in healthcare, aerospace, and education. Key projects include: "Connecting Bodies – Designing Shape-changing Wearables" (Postdoc Fellowship, 2023–2025) "Advancing real-time exoskeleton control for human-in-the-loop optimization" (Demonstrator Project) SEC scholar collaboration with Mohamed Elbadawi (May–June 2024) Research interests emphasize: Soft robotic actuators for safe human interaction Optimization of compliant mechanisms in robotics Vortex adhesion systems for autonomous inspection Design of child-friendly interactive robots His work integrates robotics with control systems, biomechanics, and human-centered design. Over 50 peer-reviewed articles demonstrate contributions to exoskeleton technology, climbing robot algorithms, and soft actuator modeling. He advises students like Laia Turmo Vidal (Postdoc) and Mohamed Elbadawi (SEC scholar). Affiliated with the cross-disciplinary Digital Futures initiative, he collaborates with Stockholm University and RISE Research Institutes to address societal challenges through digital innovation.
Robert Katzschmann is an Assistant Professor of Robotics (tenure-track) at ETH Zurich's Department of Mechanical and Process Engineering , leading the Soft Robotics Laboratory . He is also the co-founder and scientific advisor of Mimic Robotics , focused on dexterous manipulation solutions. His research spans Soft Robotics , Musculoskeletal Robotics , Biohybrid Systems , and Underwater Robotics , with breakthroughs like the autonomous soft robotic fish SoFi and biohybrid actuators. He holds a PhD from MIT (2018), a Master's from Stanford (2013), and a Diplom-Ingenieur from KIT (2013). Research Interests: His work emphasizes compliant, bioinspired robots capable of safe human interaction and complex environmental navigation. Key areas include soft material fabrication, biohybrid tissue integration, and dynamic control algorithms. Recent innovations include electrohydraulic actuators and vision-controlled printing for robotic components. Grants & Recognition: Secured funding from SNSF, NSF, and industry partners. Recognitions include a TED Fellowship (2022), Outstanding Paper Award (IEEE RoboSoft 2019), and Redtenbacher-Prize (2014). He serves on editorial boards for Advanced Robotics Research and npj Robotics , and chairs conference workshops globally. Labs & Teams: Directs the Soft Robotics Lab with 17 PhD students and 2 postdocs. Collaborates with leading institutions like MIT, Harvard, and the Weizmann Institute on biohybrid systems and robotic actuation.
Professor Amanda Prorok leads the Prorok Lab at the University of Cambridge's Department of Computer Science and Technology, focusing on multi-agent and multi-robot systems. Her work integrates machine learning, planning, and control to coordinate intelligent agents in shared environments, with applications in transport, environmental monitoring, and search-and-rescue. She is a Fellow of Pembroke College and holds editorial roles at IEEE Robotics and Automation Letters and Autonomous Robots. Education: Ph.D., EPFL (Switzerland); Postdoctoral Research, University of Pennsylvania (USA). Research Interests: The lab pioneers methods like differentiable communication between learning agents and develops decentralized algorithms for navigation, coverage, and coordination. Key themes include neural diversity in collective learning, resilient swarm systems, and environment-aware control. Notable Achievements: ERC Starting Grant, Amazon Research Award, EPSRC New Investigator Award ABB Prize for Best Thesis in Computer Science (EPFL) Teaching: Leads Computing for Collective Intelligence (MPhil/Part III) modules. Lab & Infrastructure: The Prorok Lab operates the Cambridge RoboMaster platform and develops testbeds for connected vehicles and robot swarms. Recent work emphasizes scalable reinforcement learning and graph neural networks for decentralized decision-making.
Dr. Gabor Karsai is a Distinguished Professor of Computer Science and Professor of Electrical and Computer Engineering at Vanderbilt University's School of Engineering. He also serves as Senior Research Scientist at the Institute for Software-Integrated Systems (ISIS), where he contributes to the Executive Council. With over 30 years in software engineering, his research focuses on embedded systems, model-driven development, resilient software platforms, and AI-driven autonomous systems assurance. He holds a PhD from Vanderbilt and degrees from the Technical University of Budapest. Education: Ph.D. in Electrical and Computer Engineering, Vanderbilt University Dr.Tech. in Computer Engineering, Technical University of Budapest M.S. and B.S. in Electrical Engineering, Technical University of Budapest Affiliations: Co-Associate Chair for Computer Engineering External Member of the Hungarian Academy of Sciences His research interests span model-integrated computing , autonomous systems assurance , and radiation-hardened systems . Recent work emphasizes AI integration into engineered systems and radiation effects mitigation for space applications. He has led major projects on distributed control for smart grids and resilient CPS architectures. Over 200 peer-reviewed publications and four patents reflect his contributions to software engineering and systems integration. Awards & Recognition: External Membership in Hungarian Academy of Sciences Leadership roles in ISIS and Vanderbilt's academic governance Advisees & Grants: While no student list is provided, his projects involve collaborative teams across academia and industry. Major sponsors include NSF, NASA, and DARPA. Current work includes the ALC (Assurance-based Learning-enabled CPS) and MIDAS (Model-based Intent-Driven Adaptive Software) initiatives. Labs & Platforms: Co-developer of the RIAPS distributed CPS platform and the SEAM assurance modeling framework. His labs focus on cyber-physical system design, radiation effects analysis, and autonomous system reliability.
Nilanjan Sarkar is the Vice Dean and Senior Associate Dean for Faculty Affairs at Vanderbilt University's School of Engineering, holding the David K. Wilson Professorship in Engineering. He is a Professor in Mechanical Engineering, Computer Engineering, and Computer Science. His research focuses on intelligent systems for human interaction, including robotics, virtual/augmented reality, and assistive technologies for neurodevelopmental disorders and aging populations. Education: PhD (Mechanical Engineering, University of Pennsylvania), ME (Indian Institute of Science), BE (Indian Institute of Engineering Science and Technology, Shibpur). Research interests span human-robot interaction, sensor fusion, and rehabilitation engineering. His lab develops systems for autism intervention, stroke rehabilitation, and elderly engagement through socially assistive robotics and VR/AR. Notable projects include robot-mediated therapy for children and AR telepresence systems for long-term care facilities. Labs/Teams: Robotics and Autonomous Systems Laboratory. Key contributions include CoMove, RASSLE, and the Career Interview Readiness in VR platform. His work emphasizes participatory design with end-users for ethical and inclusive technology.
James Bellingham is the Bloomberg Distinguished Professor of exploration robotics at Johns Hopkins University, holding primary appointments in the Department of Mechanical Engineering and the Applied Physics Laboratory's Asymmetric Operations Sector. He serves as executive director of the Johns Hopkins Institute for Assured Autonomy and is a member of the Data Science and AI Institute. With over 30 years of expertise, Bellingham pioneered small, high-performance autonomous underwater vehicles (AUVs), leading global expeditions across polar and oceanic regions. His work bridges robotics innovation with environmental monitoring, including oil spill response, Arctic exploration, and NASA collaborations for extraterrestrial oceanic exploration. Bellingham's educational background includes BS, MS, and PhD in physics from MIT. He previously led Woods Hole Oceanographic Institution's Marine Robotics Consortium, creating advanced prototyping facilities and fostering entrepreneurship in robotics. His leadership roles span institutional boards such as the Naval Studies Board and OceanX. His research focuses on advancing AUV capabilities for adaptive sampling, fault detection, and interdisciplinary oceanography. Over 50 publications demonstrate his technical contributions, including AUV design, environmental hazard mapping, and collaborative robotic systems. Awards include National Academy of Engineering induction and military honors for public service.
Dr. Allahyar Montazeri is a Senior Lecturer in Control and Electronics Engineering at Lancaster University's School of Engineering, specializing in advanced control systems and signal processing. His research focuses on adaptive signal processing, robust control, system identification, and applications in robotics, active noise/vibration control, and wave energy conversion. He has over 110 publications and serves on editorial boards such as Frontiers in Robotics and AI, and IFAC Technical Committees. Montazeri holds a Humboldt Research Fellowship (2011) and ERCIM Fellowship (2010). His industrial collaborations include Bosch for automotive noise control and Fraunhofer Institute. He has supervised PhD students in acoustic signal processing and leads projects on autonomous robotics and environmental monitoring. Notable awards include 'Outstanding Associate Editor' (2023) and 'Fellow of The Higher Education Academy.' He actively participates in conferences like IEEE CDC and chairs sessions on mechatronics systems. His work bridges theoretical control advancements with practical applications in extreme environments, including nuclear robotics and underwater systems.
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