Find Academic Supervisors

• Robotics
• Unmanned Aerial Vehicles
• Computer Vision
• +3 more

Barbara Bazzana is an active Researcher specializing in Robotics and Mechatronics with a focus on unmanned aerial systems control. Her work integrates computer vision and machine learning to solve complex navigation challenges in multi-rotor platforms, particularly through novel applications of diffusion models and experimental force modeling. Her core research domains include: Visual servoing for UAV autonomous navigation Denoising diffusion probabilistic models in robotics Multi-rotor aerodynamics and cross-influence effects Real-time propeller force modeling Latent space representations for control systems Analysis of her 2024-2025 publications reveals a strong trend toward merging generative AI with physical UAV control systems. Her work demonstrates how return-conditioned latent diffusion models can enable image-based servoing without explicit state estimation, while her propeller force research provides experimentally validated solutions for multi-rotor instability caused by aerodynamic interference. Both threads emphasize practical implementation in real-world aerial systems rather than purely theoretical exploration.

Peter CorkeView profile

Professor

• Robotics
• Computer Vision
• Control Systems
• +5 more

Roles and Affiliations: Distinguished Emeritus Professor at QUT's School of Electrical Engineering & Robotics. Former Director of the QUT Centre for Robotics (2020-23) and the ARC Centre of Excellence for Robotic Vision (2014-2020). Technical advisor to LYRO Robotics, Emesent, and ARMHub. Chair of Robotics Australia Group's Robotic Council. Education: PhD in Mechanical and Manufacturing Engineering from the University of Melbourne. Undergraduate and master’s degrees in Electrical Engineering from the same institution. Research Focus: Robotic perception (vision and force), dynamics and control, applications in mining, agriculture, and environmental monitoring. Pioneered open-source robotics software (MATLAB/Python) and the Robot Academy, impacting millions of students globally. Editor-in-chief roles at IEEE Robotics & Automation Magazine and founding editor of the Journal of Field Robotics. Awards: Fellowships from the IEEE, Australian Academy of Science, and Australian Academy of Technology and Engineering. 2017 Australian University Teacher of the Year. Recognized for innovations like the COTSBot (Eureka Prize finalist) and Starbug (Engineering Excellence Award).

• Artificial Intelligence
• Electrical Engineering
• Robotics
• +3 more

Professor Christopher McCool is a faculty member at Queensland University of Technology (QUT), specializing in Artificial Intelligence and Electrical Engineering. He holds a PhD from QUT and has contributed extensively to robotics and automation in agriculture, focusing on applications such as precision agriculture, weed management systems, and robotic vision for fruit detection. His work integrates computer vision, mechatronics, and environmental sustainability. Education: PhD in Electrical Engineering, Queensland University of Technology Research Interests: Development of agricultural robotics for crop monitoring and harvesting Computer vision techniques for environmental and agricultural analysis Autonomous systems for obstacle detection and navigation Unsupervised learning methods in robotic weed management Key Contributions: Co-edited special issues on agricultural robotics in the Journal of Field Robotics Advanced fruit detection and ripeness estimation through robotic vision systems Designed mechatronic systems for precision weed management Grants and Collaborations: Active in interdisciplinary projects involving robotics and environmental science Partnerships with industry for agricultural automation solutions

• Robotics
• Neurosciences
• Biomechanics
• +3 more

Philippe Souères is a Research Professor at LAAS-CNRS, part of the University of Toulouse. He leads the Gepetto team, focusing on advanced robotics, motion generation, and interdisciplinary research in biomechanics and neuroscience. His work bridges robotics with human movement analysis, emphasizing humanoid robotics, control systems, and sensor-based approaches. Research interests include robot control (optimal control, nonlinear systems), neuroscientific applications (human motor control, multisensory integration), and biomechanics. His team explores human-like motion generation, dynamic systems, and robotic applications in fields like humanoid locomotion and aerial vehicles. Recent publications highlight advancements in humanoid robotics, motion planning under constraints, and interdisciplinary methods linking robotics with neuroscience. Notably, his 2010 work on human movement invariants earned a best paper award. Souères mentors numerous PhD students in topics like compliant actuators, motion planning, and real-time control systems. His team collaborates internationally, receiving grants for projects like Flecto (ANR grant for deformable object motion analysis). Led the development of the Pyrène humanoid robot and participates in initiatives like the Anthropomorphic Motion Factory workshops. His research emphasizes practical applications, including robot audition (EAR Project) and advanced control algorithms for bipedal and aerial systems.

• Robotics
• Biomechatronics
• Human-Machine Interaction
• +7 more

P.P. Jonker is a full Professor in the Department of Biomechatronics & Human-Machine Control within the Faculty of Mechanical Engineering at Delft University of Technology. His research bridges robotics, intelligent systems, and human-centered control technologies, with a strong emphasis on practical applications in automation and machine perception. His research interests span Robotics , Biomechatronics , Human-Machine Interaction , Computer Vision , Machine Learning , and Adaptive Filtering . He focuses on enabling robots to operate autonomously in unstructured environments through active vision, sensor fusion, and intelligent control strategies. The recent publications highlight a consistent trend in applying deep learning to visual data synthesis, optimizing hardware-efficient signal processing, and advancing robotic perception and control. These works reflect a strong integration of theoretical control methods with real-world engineering implementation, particularly in autonomous systems and industrial automation. Active contributor to IEEE and ACM publications Research featured in public media on autonomous vehicles and robot coworkers Supervised 19 academic works, indicating active mentorship His work has been supported through academic grants and collaborative projects, with applications in autonomous driving, industrial robotics, and smart sensing. He collaborates across disciplines, particularly in control theory, computer vision, and embedded systems. Jonker is involved in pioneering research on human-robot collaboration, where biomechatronic principles are applied to enhance robot adaptability and safety in shared workspaces. His lab likely focuses on real-time control systems, sensor integration, and machine learning for robotic autonomy.

• Computer Vision
• Robotics
• Visual Servoing
• +4 more

Christophe Collewet is a researcher affiliated with University of Rennes 1, currently on secondment to the National Institute for Research in Computer Science and Automation (INRIA) within the Lagadic project in Rennes since 2005. He holds a Doctorate in Signal Processing and Telecommunications from University of Rennes 1. His primary research interests include Computer Vision, Robotics, Visual Servoing, Fluid Dynamics Control, and Signal Processing. Dr. Collewet has made significant contributions to the field of visual servoing for robotic systems and its application to fluid flow control. His work bridges computer vision techniques with practical control systems for both robotics and fluid dynamics applications. Analysis of his recent publications reveals a strong focus on applying computer vision techniques to fluid dynamics control problems, particularly in shear flow and Poiseuille flow systems. His research demonstrates the innovative application of visual servoing methods to traditionally non-visual control problems, creating interdisciplinary connections between robotics and fluid mechanics. Throughout his career, Dr. Collewet has collaborated extensively with researchers at INRIA and University of Rennes 1, contributing to numerous projects in computer vision-based control systems for both robotic manipulation and fluid dynamics applications. His laboratory work has primarily been conducted within the Lagadic project at INRIA Rennes, focusing on developing vision-based control systems for various applications ranging from robotic milking systems to advanced fluid flow control mechanisms.

Carol MARTINEZ LUNAView profile

Researcher

• Space Robotics
• Computer Vision
• Machine Learning
• +5 more

Dr. Carol Martinez Luna is a Research Scientist and Deputy Head of the Space Robotics group (SpaceR) at the SnT Interdisciplinary Centre, University of Luxembourg. She holds a PhD in Robotics and Automation from Universidad Politécnica de Madrid (2013) and previously served as an Assistant Professor at Pontificia Universidad Javeriana, Colombia. Her research spans Space Robotics , Computer Vision , and Machine Learning , with current focus areas including: Multi-purpose manipulation for planetary/orbital robots Perception systems for autonomous space operations Domain adaptation to bridge simulation-to-reality gaps On-ground testing of orbital technologies Recent publications (2022-2025) predominantly address space debris removal , autonomous grasping , and robotic perception , with heavy emphasis on machine learning techniques and high-fidelity simulation validation. Notable trends include generative models for manipulation and adaptive control under uncertainty. She actively advises 7 PhD students and 9 Master's candidates on topics ranging from space manipulation to vision-based safety systems. Her lab develops experimental platforms for orbital scenario emulation and collaborates on ESA-funded debris removal initiatives.

Daniel ToalView profile

Professor

• Marine Technology
• Renewable Ocean Energy
• Marine Airborne Systems
• +9 more

Prof. Daniel Toal is a Full Professor and Chair of Electrical Engineering and Robotics at the University of Limerick , affiliated with the Department of Electronic and Computer Engineering and multiple research centers including Lero and the Centre for Robotics and Intelligent Systems . With a PhD and M.Sc. from Cranfield University, he specializes in marine robotics, controller design, and autonomous systems for challenging environments. Ph.D. (Electronics & Computer Engineering) M.Sc. (Cranfield University) His research focuses on robot motion control , intervention robotics for offshore energy systems, and sensor integration for underwater operations. Key projects include autonomous inspection of offshore wind farms, friction stir welding for ship hull repair, and LiDAR-based bridge inspection systems. Recent publications highlight advancements in autonomous path planning , visual servoing , and underwater sensor systems , with applications in offshore wind energy and marine infrastructure. His work aligns with UN Sustainable Development Goals for sustainable marine technologies. Denny Medal (2008) - Best Paper in Journal of Marine Engineering and Technology Prof. Toal teaches courses in industrial robotics , marine operations , and control systems , while leading collaborations with European research networks and contributing to robotics standards development through IEEE and IFAC memberships.

• Robotics
• Control Systems
• Computer Vision
• +3 more

Hui Xie is a Lecturer in the School of Electrical Engineering, Computer and Mathematical Sciences at Curtin University. Their work focuses on robotics, control systems, and computer vision, particularly in the context of unmanned aerial vehicles (UAVs) and autonomous systems. They are affiliated with the Faculty of Science and Engineering and are based at the Curtin Perth campus. Research interests center on visual servoing techniques for UAVs, adaptive control systems, and image-based navigation in GPS-denied environments. Notable contributions include advancements in dynamic visual servoing using virtual cameras, disturbance observer-based control, and nested saturation control strategies for multi-agent systems. Xie's publications span topics like semantic segmentation in autonomous driving, scene flow estimation, and output feedback mechanisms for rotorcrafts. Their work bridges theoretical control frameworks with practical applications in robotics and aerospace engineering.

Petar DurdevicView profile

Associate Professor

• Modelling and Control
• Deep Learning
• Deep Reinforcement Learning
• +8 more

Petar Durdevic is an Associate Professor at Aalborg University, leading the Offshore Drones and Robots research group within the Department of Energy Technology. His work focuses on Modelling and Control, Deep Learning, and robotics applications in process control, water treatment systems, and wind turbine monitoring. He established the Robotics Lab at Aalborg University’s Esbjerg Campus and serves on the board of Aalborg Robotics, a research center advancing robotics innovation and education. Research Interests: Deep Reinforcement Learning, Wind Turbine Condition Monitoring, Onshore WWTP Optimization, and Robotic Systems. Lab Leadership: Robotics Lab (Esbjerg Campus), Aalborg Robotics Board Member. No specific articles or awards are listed in the provided text. His contributions emphasize applied robotics and sustainable energy systems, with ongoing projects in offshore and onshore water treatment automation.

Yanjie ChenView profile

Visiting Professor

• Robotics
• Computer Vision
• Control Systems
• +3 more

Yanjie Chen is a Visiting Professor in the Department of Computer Science at Aberystwyth University. Their research focuses on robotics, computer vision, control systems, and artificial intelligence, with notable contributions in aerial manipulators, neural architecture search, and fuzzy logic systems. Chen holds the prestigious Newton International Fellowship since 2022. In robotics, Chen explores advanced control strategies for unmanned aerial vehicles and manipulators, addressing challenges like dynamic tracking, impedance control, and environmental disturbances. Their work in AI emphasizes optimization techniques for neural networks, including pruning and architecture search, enhancing computational efficiency. In computer vision, Chen develops attention-based mechanisms for super-resolution tasks. Key Achievements: Recipient of the Newton International Fellowship (2022) High-impact publications in IEEE Transactions and Springer venues Collaborations with institutions like Fuzhou University and Hunan University Chen’s research bridges theory and application, with practical solutions for robotics, autonomous systems, and AI-driven image processing.

Marie BabelView profile

Professor

• Robotics
• Assistive Robotics
• Sensor-Based Servoing
• +4 more

Marie Babel is a Full Professor at INSA Rennes, affiliated with the Rainbow team within IRISA/Inria. She specializes in assistive robotics, focusing on mobility aids for people with disabilities, including sensor-based servoing, haptic interfaces, and virtual reality applications. She leads major projects like the DORNELL Challenge and coordinates international collaborations, such as the ISI4NAVE team with University College London. Her academic Chair IH2A (Innovations, Disability, Autonomy, Accessibility) drives interdisciplinary research in assistive technologies. She holds a PhD in image processing (2005) and an habilitation in signal processing (2012). Teaching: Robotics, Image Processing, Mathematics for Engineers at INSA Rennes. Key Projects: ADAPT (€2M budget), H2020 Crowdbot, PRISME/Ambrougerien. Research Interests: Multimodal sensor-based systems, human-robot interaction, and clinical trials for assistive technologies. Notable contributions include wheelchair navigation assistance, wearable haptic feedback, and VR simulators. Awards: Best Paper at Eurohaptics 2022, Innovation Award at SOFMER 2019. Grants & Labs: Leads INSA's contributions to ADAPT and coordinates DORNELL Challenge. Active in Inria's research networks.

Piotr RudolView profile

Researcher

• Artificial Intelligence
• Robotics
• Computer Vision
• +5 more

Piotr Rudol is a Researcher at Linköping University's Department of Computer and Information Science (IDA), part of the Artificial Intelligence and Integrated Computer Systems (AIICS) division. His work focuses on advancing artificial intelligence, robotics, and their applications in collaborative systems, autonomous navigation, and UAV technology. Research interests include: Robotics mission planning and coordination Unmanned aerial vehicle (UAV) systems for search and rescue RDF graph synchronization for collaborative robotics Computer vision for object detection and geolocation Multi-agent systems integration His recent articles emphasize autonomous systems, sensor fusion, and distributed robotics frameworks. Notable contributions include frameworks for UAV-based human detection and collaborative mission planning systems. Piotr collaborates with senior researchers like Patrick Doherty and Mariusz Wzorek, contributing to projects funded through institutional research programs. He is actively involved in the IDA department's research initiatives, bridging theoretical AI advancements with practical robotic implementations.

Jason FordView profile

Professor

• Robotics
• Decision Systems
• Autonomous Systems
• +4 more

Jason Ford is a Professor of Electrical Engineering at Queensland University of Technology (QUT), leading research in trustworthy autonomous systems and decision-making under uncertainty. He holds positions in QUT's Centre for Robotics and Centre for Data Science. Ford earned his PhD from the Australian National University (ANU) and has over 20 years of experience in aerospace, energy, and defense sectors. His research focuses on model-based filtering, estimation, and decision systems for dynamic environments, with applications in aerial autonomy, infrastructure inspection, and low-signal-to-noise detection. Education: B.Sc. and B.E. (1995), PhD (1998), all from ANU. Professional Experience: Research Scientist at DSTG (1998-2004), Research Fellow at UNSW (2004-2005), QUT faculty since 2005, promoted to Professor in 2019. Research Interests: Robust autonomous systems, vision-based sense-and-avoid, model-driven decision systems, and resilient robotic technologies. His work on ROAMES asset management systems has saved Queensland $40M/year and won international awards. Awards: 2019 Academic of the Year (Australian Defence Industry), multiple best paper awards, and industry recognition for collision avoidance and UAV technologies. Grants: Over $10M in competitive research funds since 2009. Supervision: 8 completed HDR students since 2008, teaching control systems and autonomous systems to 1000+ undergraduates. Labs/Teams: Program Lead for Decision and Control in QUT's Robotics Centre, collaborator with industry partners like Insitu Pacific and Caterpillar.

Aaron McFadyenView profile

Senior Lecturer

• Unmanned Traffic Management
• Aerospace Engineering
• Robotics
• +3 more

Dr. Aaron McFadyen is a Senior Lecturer in the School of Electrical Engineering & Robotics at Queensland University of Technology (QUT), with a focus on aerospace engineering, robotics, and control systems. He holds a PhD from QUT and has extensive industry experience in flight simulation and autonomous systems research. His research emphasizes unmanned traffic management (UTM), air traffic modeling, and quantitative risk analysis, with applications in drone integration and airspace safety. He has secured over $1.5M in research funding and led projects for organizations like Airservices Australia and CASA. Key achievements include developing Australia's Automated Airspace Authorization system and winning the 2019 IEEE/AIAA Best Unmanned Traffic Management Paper Award. Education: PhD in Robotics and Autonomous Systems (QUT), Private Pilot License (CASA), and qualifications in aerospace engineering. Professional memberships include IEEE, JARUS, and the Control System Society. Research interests span UTM systems, collision risk modeling, and control systems for autonomous vehicles. His work bridges academia and industry, addressing challenges in air traffic management and robotics. Recent publications focus on nonlinear control, airspace risk analysis, and multi-agent systems. He has supervised undergraduate, masters, and PhD students in aerospace and robotics. Awards include the ARC DECRA Fellowship (2020) and Advance Queensland Mid-Career Fellowship (2020). His lab collaborations include the Australian Research Centre for Aerospace Automation (ARCAA) and ETH Zurich's Autonomous Systems Lab.