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Robert WoodView profile

Professor

• Robotics
• Materials Science
• Mechanical Engineering
• +7 more

Robert Wood is the Harry Lewis and Marlyn McGrath Professor of Engineering and Applied Sciences at Harvard University, affiliated with the School of Engineering & Applied Sciences. He holds a PhD in Electrical Engineering and Computer Sciences from UC Berkeley. His research focuses on robotics, particularly bio-inspired systems and soft robotics applications in natural environments and biomedicine. He emphasizes interdisciplinary approaches, combining engineering with biological insights to advance robotic design and functionality. Wood teaches courses such as 'How Music Works: Engineering the Acoustical World,' 'Microrobotics and Bio-inspired Autonomous Robotic Systems,' and 'Advanced Topics in Robotics Research.' He advocates for hands-on learning and the value of iterative failure in education, stating, 'Making mistakes and learning from them is an absolutely essential part of the learning process.' His lab, the Microrobotics Lab, explores topics like compliant actuators, bioinspired locomotion, and soft robotic systems. While no formal scientific awards are listed, Wood’s contributions to robotics have been highlighted through his work on projects like RoboBee and the Cetacean Translation Initiative (Project CETI). He directs graduate studies in his department and has advised students across his research and teaching activities. His lab’s current and future work includes advancements in soft wearable sensors, modular robotic systems, and biomimetic mechanisms for medical and environmental applications.

Chunxu LiView profile

Senior Lecturer

• Motion planning
• Human-robot interaction
• Cybernetics
• +3 more

Dr. Chunxu Li is a Senior Lecturer in Mechanical Engineering at Swansea University's School of Aerospace, Civil, Electrical and Mechanical Engineering. He holds a PhD from Swansea University (2019) and has extensive experience in robotics, including expertise in ROS, C++, Python, and MATLAB. He has published over 40 academic papers, with 33 indexed in SCI/EI, and has been recognized with awards such as the Best Student Paper Award at IEEE conferences. His research focuses on motion planning, human-robot interaction, cybernetics, and soft robotics. Dr. Li's research interests include advanced control systems for robots, fault-tolerant manipulation, and the development of intuitive human-machine interfaces. His work integrates machine learning, neural networks, and sensor fusion to enhance robotic autonomy and precision. Notable projects include the Blue Hand soft robotic hand and studies on trajectory capture for KUKA iiwa robots. He has secured significant funding, including a £1.013 million grant for intergenerational technology co-creation. His teaching includes modules on electromechanical control and systems engineering. Awards include being an Associate Fellow of the Higher Education Academy and membership in IEEE. Dr. Li supervises PhD students in areas like neural network control for unmanned aerial vehicles and human-machine interaction systems. He collaborates on projects such as wearable rehabilitation robots and sensor fusion platforms for localization, demonstrating a strong commitment to interdisciplinary robotics research.

Olov AnderssonView profile

Assistant Professor

• Autonomous Systems
• Robotics
• Artificial Intelligence
• +5 more

Olov Andersson is an Assistant Professor and WASP Fellow in AI for Autonomous Systems at KTH Royal Institute of Technology, leading the Division of Robotics, Perception and Learning. His research focuses on Embodied AI for autonomous robots and vehicles, combining advancements in Vision-Language Models (VLM), Large Language Models (LLM), and real-world navigation challenges. Key projects include the DARPA SubT Challenge-winning team CERBERUS and the EU H2020 Heron project for robotic road repair. He supervises multiple PhD students and postdocs, including Timon Homberger, Finn Lukas Busch, and Jesper Eriksson. Research interests emphasize full-stack autonomy in dynamic environments, including planning, mapping, and navigation. Notable contributions include the OneMap real-time open-vocabulary mapping system and self-supervised scene flow methods like Seflow. He has been recognized for technical leadership in autonomous systems through awards like the WASP Fellowship. Professional activities include co-chairing the 2024 IROS workshop on robot perception in dynamic environments and advising the Swedish Prime Minister’s AI initiative. Teaching roles span multiple graduate courses in machine learning, robotics, and systems engineering at KTH.

• Laser Doppler Anemometry
• Thermography-Based Diagnostics
• Vision and Photogrammetry in Inspection
• +1 more

Prof. Sławomir Zator holds the position of University Professor at the Department of Safety Engineering and Technical Systems under the Faculty of Production Engineering and Logistics at Opole University of Technology. His research focuses on advanced diagnostics techniques using laser Doppler anemometry, thermography, and vision-based methods for infrastructure and energy systems. He also explores energy management strategies in buildings, emphasizing smart home integration with renewable energy sources like photovoltaics and heat pumps. His work bridges theoretical advancements with practical applications in power line safety, industrial equipment monitoring, and sustainable energy solutions. Research interests include: Laser-based flow measurement innovations Non-destructive evaluation of boiler tubes and power line components Machine vision applications for structural diagnostics Optimization of building energy systems Recent publications highlight trends in smart grid energy scheduling, icing risk mitigation for power infrastructure, and hybrid energy storage integration. His work often features cross-disciplinary approaches combining thermal imaging, computational modeling, and automation technologies. Prof. Zator maintains an active research profile through collaborations with international institutions and contributes to technical education via course development in safety engineering and metrology.

• Artificial Intelligence
• Machine Learning
• Anomaly Detection
• +3 more

Dr. Victoria J Hodge is a Research Fellow in the Department of Computer Science at the University of York, affiliated with the Centre for Assuring Autonomy (CfAA). She holds a PhD in Computer Science from the University of York and has industry experience in software architecture for medical diagnostics and industrial anomaly detection systems. Her research focuses on artificial intelligence (AI), anomaly detection, machine learning, and safety assurance for autonomous systems, particularly in robotics. Her work emphasizes through-life safety assurance of AI-driven autonomous systems, including robotics platforms operating in uncertain environments. She has authored over 70 publications across disciplines like AI, machine learning, robotics, and safety engineering. Notable projects include SCALOFT (drone safety analysis) and ASUMI (UAV safety assurance in mining). Her research trends show a strong emphasis on interdisciplinary applications of AI, with recent focus on autonomous systems in high-risk environments (e.g., mining, healthcare) and real-time decision support systems. Collaboration with industry ensures practical impact in domains like medical diagnostics and industrial automation.

Ioannis StefanakosView profile

Academic

• Formal Verification
• Robotics Safety
• Autonomous Systems
• +3 more

Ioannis Stefanakos is a Research Associate at the Department of Computer Science, University of York, affiliated with the High Integrity Systems research group. His work focuses on formal verification of autonomous systems, safety-critical robotics, and software performance analysis. Current projects include assurance frameworks for drones, adaptive reinforcement learning in healthcare robotics, and probabilistic modeling of software performance. Recent research emphasizes interdisciplinary applications in UAV systems, medical decision support systems, and collaborative manufacturing robots. No academic awards are listed, though his work has been published in top-tier conferences. Advising and grants details are not explicitly stated, but his involvement in doctoral forum papers suggests potential supervision roles in software systems research.

Joel W. BurdickView profile

Professor

• Robotics
• Kinematics
• Mechanical Systems
• +3 more

Joel W. Burdick is the Richard L. and Dorothy M. Hayman Professor of Mechanical Engineering and Bioengineering at the California Institute of Technology (Caltech), and a Research Scientist at the Jet Propulsion Laboratory (JPL). He holds a B.S. from Duke University (1981), M.S. from Stanford University (1982), and Ph.D. from Stanford (1988). His academic roles include Executive Officer for Bioengineering (2006–2007) and Hayman Professor (2012–present). Burdick's research focuses on robotics, kinematics, and control systems with applications in planetary exploration (e.g., Axel/DuAxel rovers), medical robotics (spinal cord therapy), and autonomous systems. His group participates in the DARPA Subterranean Challenge (Team CoSTAR) and develops technologies like the SQUID drone and EELS snake robot. Teaching includes advanced robotics courses (ME/CDS/EE 234ab) and contributions to control systems education. His work bridges robotics engineering with bioengineering, emphasizing interdisciplinary collaboration with institutions like UCLA and JPL.

Andrew BuckView profile

Assistant Professor

• Machine Learning
• Intelligent Agents
• Autonomous Drones
• +2 more

Andrew Buck is an Assistant Research Professor in the Department of Electrical Engineering and Computer Science at the University of Missouri . His work focuses on machine learning , intelligent agents , autonomous drones , computer vision , and 3D visualization . Education: PhD, MS, BS in Computer Engineering, and BS in Electrical Engineering from the University of Missouri Andrew Buck's research involves the development of photorealistic synthetic datasets (e.g., HiFiAerial), explainable AI frameworks for drone autonomy, and human-agent teaming dynamics (e.g., trust modeling). He has pioneered multidisciplinary simulation platforms like Mizsim for AI training and evaluation, and contributed to real-time 3D reconstruction techniques combining classical algorithms with deep learning. His work on uncertainty quantification in depth estimation and fuzzy voxel maps demonstrates his interest in probabilistic approaches to perception. A key theme in his publications is the evaluation of AI performance in partially observable environments , including applications in explosive hazard detection and cooperative game scenarios.

Adyasha MohantyView profile

Assistant Professor

• Robotics
• Machine Learning
• Autonomous Systems
• +5 more

Adyasha Mohanty is an Assistant Professor of Engineering at Harvey Mudd College, where she teaches courses such as Introduction to Engineering Design and Manufacturing (E4) and State Estimation for Robotics (E205). She leads the Machine Learning and Autonomy for Diverse Domains Lab, focusing on robotic perception and localization across ground, air, and space platforms. Her work emphasizes safe and reliable autonomy through algorithmic innovation. Her research interests lie at the intersection of robotics and machine learning, particularly in developing robust perception systems for autonomous agents operating in complex environments. She is passionate about mentoring students through teaching, research, and Clinic projects, and values a dynamic academic environment that encourages pedagogical and research risk-taking. While no publications are listed in the provided text, her research direction suggests strong engagement with algorithm development for autonomous systems, with potential applications in aerospace, terrestrial robotics, and intelligent navigation. Her lab likely involves interdisciplinary collaboration across engineering and computer science domains. No scientific awards mentioned in the source text. She mentors students through classroom instruction, research supervision, and participation in Harvey Mudd's Clinic program, which connects student teams with real-world engineering challenges. Though specific grants are not listed, her lab activities suggest active pursuit of research funding to support her work in machine learning and robotics. Adyasha leads the Machine Learning and Autonomy for Diverse Domains Lab at Harvey Mudd College, where she and her students develop algorithms for safe and reliable operation of autonomous robots in diverse environments including ground, aerial, and space domains.

Timothy I MachinView profile

Assistant Professor

• Autonomous Systems
• Navigation Systems
• Belief Space Planning
• +5 more

Maj Timothy I. Machin is an Assistant Professor in the Department of Electrical Engineering at the Air Force Institute of Technology (AFIT), part of Air University, Wright-Patterson Air Force Base, Ohio. He holds a Ph.D. and M.S. in Electrical Engineering from AFIT and a B.S. from Purdue University. Ph.D., Electrical Engineering, AFIT (2023) M.S., Electrical Engineering, AFIT (2016) B.S., Electrical Engineering, Purdue University (2014) His research focuses on autonomous navigation systems, particularly in GNSS-denied environments. Key areas include belief space planning, vision-aided navigation, and real-time implementation for small UAVs. His work integrates robotics, control theory, and sensor fusion to enhance autonomy under uncertainty. The recent publications reflect a strong trend in autonomous systems, with emphasis on planning algorithms, navigation robustness, and real-time embedded solutions. Topics span from theoretical frameworks like planning taxonomies to practical implementations in fixed-wing UAVs using monocular vision and inertial systems. No scientific awards are listed in the provided text. There is no public information available on student advising or research grants. However, his role as an Assistant Professor suggests involvement in mentoring graduate students and leading research projects within AFIT’s engineering programs. While specific lab affiliations are not mentioned, his research aligns closely with AFIT’s Autonomous Navigation and Robotics research groups, likely involving collaboration with the Department of Electrical Engineering’s UAV and navigation laboratories.

Mujahid AbdulrahimView profile

Assistant Professor

• Aerospace Engineering
• Aircraft Design
• Flight Control Systems
• +7 more

Mujahid Abdulrahim is an Assistant Professor in the School of Science and Engineering at the University of Missouri-Kansas City (UMKC), where he contributes to aerospace engineering education and research. Education: Ph.D. in Aerospace Engineering, University of Florida, 2007 M.S. in Aerospace Engineering, University of Florida, 2004 B.S. in Aerospace Engineering, University of Florida, 2003 His research focuses on key areas in aerospace systems, including Aircraft Design , Flight Control Systems , Autonomy and Guidance , Pilot Modeling , and Aircraft Structures . His work integrates theoretical and applied aspects of flight dynamics and control, with relevance to both manned and unmanned aviation systems. He is also a Certified Flight Instructor (2023), demonstrating a strong commitment to practical aviation training and education. There are no scientific awards listed in the available information. He advises students in aerospace engineering, though specific advisees are not listed. There is no mention of grants or funded research projects. No information is available about leadership in labs or research teams.

Randy FollettView profile

Associate Professor

• Electrical Engineering
• Computer Engineering
• Unmanned Aerial Systems
• +9 more

Randy Follett is an Associate Professor in the Department of Electrical and Computer Engineering at Mississippi State University (MSU), where he has been a faculty member since 1984. He earned all his academic degrees—bachelor's, master's, and doctoral—at MSU and has remained deeply integrated into the institution's academic and administrative life. He teaches a wide range of courses and serves as a key faculty adviser for student engineering teams. His research and educational interests center on electrical and computer engineering applications in autonomous and vehicular systems. He has led the university's Unmanned Aerial Systems team since 2004, focusing on surveillance and target identification, and became lead faculty adviser for the EcoCar 3 team, which works on improving the power and fuel economy of a 2016 Chevrolet Camaro. His teaching philosophy emphasizes the importance of lifelong learning and adaptability in engineering education. Randy Follett is also actively engaged in university governance, having served 12 years on the Robert Holland Faculty Senate, including a one-year term as president. He views the Faculty Senate as an indispensable check-and-balance mechanism within the university. His leadership extends to fostering innovation through student design projects and interdisciplinary collaboration at MSU's Center for Advanced Vehicular Systems. He has made significant contributions to engineering education and student development, though specific scientific awards or publications are not mentioned in the provided text. In terms of advising and grants, Follett has long supported student competition teams, which often involve external funding and industry partnerships, particularly through programs like EcoCar 3. While no specific grants or funded projects are detailed, his leadership roles suggest active involvement in sponsored educational and research initiatives. He advises both the Unmanned Aerial Systems team and the EcoCar 3 team, providing mentorship in systems integration, control, and sustainable vehicle design. Follett is affiliated with the Center for Advanced Vehicular Systems at MSU, where the EcoCar 3 team is housed. This lab environment fosters hands-on, interdisciplinary research in advanced transportation technologies, bringing together students and faculty to solve real-world engineering challenges in autonomy, efficiency, and performance.

• Autonomous Navigation for Robots
• Deep Learning
• Artificial Intelligence
• +7 more

Jesús Tordesillas Torres is an Assistant Professor in the Department of Electronics, Automation, and Communications at the School of Engineering, Comillas Pontifical University. He joined the institution in June 2024, bringing extensive experience from postdoctoral research at MIT and ETH Zurich, and prior academic training from MIT and the Polytechnic University of Madrid. Education: PhD in Aeronautics and Astronautics, Massachusetts Institute of Technology (MIT), 2022 MS in Aeronautics and Astronautics, MIT, 2019 MS in Industrial Engineering, Polytechnic University of Madrid, 2019 BS in Industrial Engineering, Polytechnic University of Madrid, 2016 His research focuses on robotics, particularly autonomous navigation, trajectory planning, and optimization under uncertainty. He integrates deep learning and control theory to develop systems capable of safe, fast, and perception-aware navigation in dynamic and unknown environments. His work spans aerial and ground robots, multiagent systems, and challenging terrains, with strong emphasis on real-world deployment and robustness. The recent publications highlight a consistent trend in trajectory optimization, perception-aware planning, and multiagent coordination. His work bridges theoretical advances in optimization and learning with practical robotic applications, especially in safety-critical and communication-constrained scenarios. Scientific Awards: Best Paper Award, IEEE ICRA 2023 1st Place, Urban Circuit, DARPA Subterranean Challenge (2020) 2nd Place, Tunnel Circuit, DARPA Subterranean Challenge (2021) Finalist, Best Paper, IEEE IROS 2019 Jesús Tordesillas Torres has been actively involved in research grants and projects, including the ADS FERRARI WP-2 Project funded by Airbus Defence and Space (2025–2025). He mentors students and collaborates with leading institutions such as MIT, ETH Zurich, and the University of Pennsylvania. He also serves as a reviewer for top-tier journals including IEEE Transactions on Robotics , International Journal of Robotics Research , and IEEE Robotics and Automation Letters , as well as major conferences like ICRA and IROS. He leads and participates in research teams focused on autonomous systems, with affiliations to the Institute for Research in Technology (IIT) at Comillas. His invited talks at ETH Robotics Summer School and University of Pennsylvania reflect his growing influence in the robotics community.

Emad Samuel Malki EbeidView profile

Professor

• Robotics
• Embedded Systems
• Smart Grids
• +3 more

Emad Samuel Malki Ebeid is a Professor at the Institute of Mechanical and Electrical Engineering, University of Southern Denmark, specializing in robotics, drone technology, and power line inspection systems. His work bridges embedded systems, FPGA acceleration, and smart grid applications. PhD in Computer Science, University of Verona (2014) Postdoc in Electrical and Computer Engineering, Aarhus University (2016) Research interests focus on robotics , UAV autonomy , and power line inspection , with a strong emphasis on embedded systems and magnetic gripper design . Articles highlight trends in mmWave radar , GPU/FPGA acceleration , and drone swarm coordination for infrastructure maintenance. Scientific contributions include: IEEE Senior Member PI and Coordinator roles in EU Horizon Europe projects (Robots4Green, SPADE) Development of AERIAL-CORE and Drones4Safety frameworks Supervision of PhD students V. D. Hoang , N. H. Malle , and F. F. Nyboe Lab and team involvement spans the Aalborg Robotics 10-year seminar and special sessions at the Euromicro DSD conference. Media features include TV 2 News and 2200 News (2025) on drone-based power line maintenance.

Nicolaj Haarhøj MalleView profile

Assistant Professor

• Aerial Robotics
• Unmanned Aerial Vehicles (UAVs)
• Power-line Maintenance and Inspection
• +7 more

Nicolaj Haarhøj Malle is an Assistant Professor at the University of Southern Denmark’s Institute of Mechanical and Electrical Engineering and a member of the SDU Digital and High-Frequency Electronics group. He earned his PhD in Robotics in November 2023 with a dissertation on autonomous power-line perception and continues as a post-doctoral researcher until July 2025. Education PhD in Robotics, University of Southern Denmark (2020–2023) Post-doctoral Researcher in Aerial Robotics for Power-line Maintenance, University of Southern Denmark (2023–2025) Research Interests Malle’s work lies at the intersection of aerial robotics, power-line engineering, and embedded intelligence. He develops fully autonomous drones capable of landing on live overhead cables to recharge, inspect, and maintain critical infrastructure. His research integrates mm-wave radar sensing , computer vision , FPGA-accelerated perception , and machine learning to achieve robust navigation in GPS-denied, high-voltage environments. He also pioneers open-source hardware-software architectures for rapid prototyping of safety-critical drone swarms. Scientific Awards & Recognition Although no formal awards are listed, Malle’s work has received extensive national press coverage, including features in Information , DR Forskerfesten PhD Cup , and international tech media highlighting his “vampire drone” concept. Grants & Projects EU H2020 Drones4Safety (2020-2023) – PhD student participant EU H2020 Aerial Core (2019-2023) – PhD student participant InnoExplorer AIR-Ops (2023-2024) – Project participant Spin-outs Denmark OnGrid Aerial Systems (2024-2025) – Project participant Laboratories & Collaborations Malle collaborates closely with the SDU UAS Center and conducts experimental flights at dedicated drone test sites. He maintains an international network via visiting research stays (University of Zürich, Oct–Dec 2022) and active IEEE membership.