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Guillaume CaronView profile

Associate Professor

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

Guillaume Caron is an Associate Professor at the Université de Picardie Jules Verne (France) and holds a delegation at the CNRS-AIST Joint Robotics Laboratory (JRL) in Tsukuba, Japan. He leads the Perception team at JRL since April 2021 and co-directs the laboratory since 2022. His academic roles include being an enseignant-chercheur (lecturer-researcher) in robotic vision and habilitated to supervise research. He has collaborated with institutions like AIST, INRIA, and companies such as Kawasaki Heavy Industries and Thales Optronique SA. Research Interests : His work focuses on robotic vision systems, adaptive cameras, visual servoing, and applications in cultural heritage preservation and medical robotics. He develops advanced imaging techniques (e.g., hyperspectral, omnidirectional) and integrates them into robotic systems for tasks like autonomous navigation, object manipulation, and assistive technologies. Recent projects include spherical vision-based wheelchair assistance and teleoperated humanoid robots in nursing contexts. Publications : His most recent work addresses multimodal navigation leveraging large language models, spherical image representations for robotics, and illumination compensation in hyperspectral imaging. He also explores cybernetic avatars for telepresence and modular assistive smart wheelchairs. Responsibilities : He co-organizes workshops on e-Heritage and chairs the IAPR Technical Committee on Computer Vision for Cultural Heritage. He serves on the CNRS-AIST JRL steering committee and the AFRIF administration board. His educational roles include leading the RVI professional license program at UPJV until 2019. Labs/Teams : Active in the MIS laboratory (Amiens) and the CNRS-AIST JRL, working on projects like the Coalas neuro-rehabilitation system and the MuSeM multispectral dataset for mobile robotics.

Francois ChaumetteView profile

Research Professor

• Robotics
• Computer Vision
• Visual Servoing
• +17 more

François Chaumette is a Senior Research Scientist (Directeur de recherche) at Inria, affiliated with IRISA and the Centre Inria de l'Université de Rennes. He has been a key researcher in robotics and computer vision since 1990 and led the Lagadic research team from 2004 to 2017. His research interests are centered on robot vision, particularly visual servoing and active perception . He has made foundational contributions to image-based and position-based visual servoing, and his work integrates control theory, computer vision, and robotics. His research spans applications in mobile robotics, aerial systems, medical robotics, space robotics, and soft object manipulation. The recent publications highlight a consistent focus on visual servoing under complex constraints—such as motion blur, occlusions, and deformations—applied to drones, cable-driven robots, and space systems. There is a strong emphasis on robustness , stability analysis , and hybrid sensing (e.g., vision + proximity, vision + force). His work with the RemoveDebris mission demonstrates real-world impact in space robotics. AFCET/CNRS Prize for best Ph.D. in Automatic Control Best paper awards at RFIA 1996 & 2004 Best paper in IEEE T-RA (2002) Best paper in IEEE RA-L (2019) Best paper in IEEE RAM (2020) IEEE Fellow (2013) He has advised over 30 Ph.D. students, many of whom have become active researchers in robotics. He has served in editorial roles for top journals including IEEE Transactions on Robotics , IEEE Robotics and Automation Letters , and the International Journal of Robotics Research . He was elected to the IEEE RAS Administrative Committee (2016–2018) and served on ERC grant panels for robotics. Chaumette is the main developer of ViSP (Visual Servoing Platform), a widely used C++ library for visual tracking and servoing. His leadership in both theoretical advances and software tools has significantly shaped the visual servoing community.

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

Saurabh Gupta is an Associate Professor in the Electrical and Computer Engineering Department at the University of Illinois Urbana-Champaign (UIUC), where he is based at the Coordinated Science Lab (CSL 319). He previously served as a Research Scientist at Facebook AI Research in Pittsburgh working with Prof. Abhinav Gupta. His educational background includes a PhD in Computer Science from UC Berkeley advised by Prof. Jitendra Malik, and an undergraduate degree in Computer Science and Engineering from IIT Delhi, India. Gupta's research focuses on building intelligent agents that can interact with the physical world, with particular emphasis on computer vision, robotics, and machine learning. His work explores representations that enable physical interaction and learning from active engagement with environments. Key research directions include spatio-semantic and topological representations for visual navigation, skill discovery, learning from videos, and active visual learning. His recent publications reveal a strong trend toward practical robotics applications with an emphasis on real-world deployment. The research spans multiple domains including humanoid robotics, egocentric vision, physical reasoning, and wireless sensing. Significant attention is given to bridging the sim-to-real gap and developing systems that work in practical environments rather than controlled laboratory settings. As an educator, Gupta teaches advanced courses including Deep Learning for Computer Vision (CS 444/ECE 494), Computer Vision (ECE 549/CS 543), and Learning-Based Robotics (ECE 598 SG). Gupta advises multiple PhD students including Arjun Gupta, Shaowei Liu, Aditya Prakash, Xiaoyu Zhang, Runpei Dong, and Xialin He, with former student Matthew Chang completing his PhD in 2024 on Robot Learning from Videos. His research group operates within the Coordinated Science Laboratory at UIUC, collaborating with researchers across computer vision, robotics, and machine learning domains. The group maintains strong connections with industry research labs including Meta AI Research, where former students have pursued research scientist positions.

Roger D. EastmanView profile

Professor

• Computer Vision
• Robotics
• Immersive Media Design
• +3 more

Roger D. Eastman is a Professor of the Practice in the Department of Computer Science at the University of Maryland, College Park, and serves as Director of the Immersive Media Design Program. He holds a Ph.D. (1990) and B.A. (1979) in Mathematics and Computer Science from the University of Maryland and University of Missouri-Columbia, respectively. His research focuses on computer vision applications in robotics, remote sensing, and immersive media. Notable projects include work with NASA-Goddard on satellite imagery registration, NIST on robotics perception standards, and JHU on medical imaging for glaucoma diagnosis. Current efforts emphasize XR visualization for Earth science and algorithmic art. Teaching priorities include introductory computer science, non-major courses in computer art with Processing/Arduino, and graphics/HCI. He has supervised undergraduate research leading to advanced academic and industry careers in VFX/game design. Publications span image registration techniques, sensor ontology development, and XR-based scientific visualization. Collaborations include Google Scholar profiles and a Cambridge Press book on remote sensing registration.

Suman BistaView profile

Research Fellow

• Robotics
• Computer Vision
• SLAM Algorithms
• +3 more

Dr. Suman Bista is a Research Fellow at the QUT Centre for Robotics, Queensland University of Technology. He holds a PhD in Signal Processing and Telecommunications from Université de Rennes. His primary research focuses on robotics, computer vision, and SLAM algorithms, with notable contributions to indoor navigation systems, semantic segmentation, and medical imaging applications. He has published extensively in top-tier journals like the International Journal of Robotics Research and conferences such as IEEE/RSJ IROS. Key research interests include visual servoing, resource-constrained robotics, and simulation environments for active scene understanding. His work bridges theoretical advancements with practical applications in autonomous systems and healthcare diagnostics. Dr. Bista’s publications highlight innovative solutions in robotics navigation, including the development of BenchBot environments for simulating real-world robotics challenges. His research emphasizes cross-disciplinary approaches, integrating computer vision techniques with robotics hardware design.

Andrew RazjigaevView profile

Researcher

• Medical Robotics
• Surgical Robotics
• Robot Kinematics
• +3 more

Dr Andrew Razjigaev is a PhD Researcher at the Queensland University of Technology (QUT), affiliated with the Medical Robotics Group within the QUT Centre for Robotics. He holds a Mechatronics Engineering degree from QUT (2017) and has been involved in the Medical Robotics Group since 2016, contributing to projects like teleoperating snake robots via hand gestures and visual servoing systems. His research focuses on surgical robotics, particularly developing continuum robots for vision-based teleoperated minimally invasive surgeries. Education: Bachelor of Mechatronics Engineering, Queensland University of Technology (2017) Research interests include robot arm kinematics, robotic vision, and teleoperation systems. His work integrates computational design algorithms with patient-specific surgical needs, advancing the field of minimally invasive surgery through snake-like manipulators and robotic collaboration (e.g., RAVEN II integration). He has also contributed to projects like CARTMAN, a low-cost Cartesian manipulator that won the Amazon Robotics Challenge, and semantic segmentation techniques for limited training data. He served as President of the QUT Robotics Club in 2018, developing robot arm workshops focused on control systems and computer vision for students. His contributions span surgical robotics, competition robotics, and medical automation, with a strong emphasis on practical applications and interdisciplinary collaboration.

• Guidance Navigation and Control (GNC)
• Space Robotics
• Autonomous Systems
• +7 more

Pedro Arroz Correia Bonifácio Serra is a researcher in the Department of Electrical and Computer Engineering at Universidade Lusófona, specializing in Guidance, Navigation, and Control (GNC) systems for aerospace and robotic applications. His work is closely aligned with European Space Agency (ESA) missions such as e.Deorbit, COMRADE, GUIBEAR, and HERACLES, focusing on active debris removal, on-orbit servicing, and autonomous spacecraft operations. Research Interests: His primary research areas include Guidance, Navigation and Control (GNC), space robotics, autonomous systems, image-based visual servo control, fault-tolerant control, and nonlinear control systems. He has made significant contributions to the development and validation of control architectures for capturing tumbling satellites and enabling autonomous landing of UAVs and spacecraft. The most recent publications reflect a strong emphasis on space safety, debris removal technologies, and computational GNC for complex space missions. His work bridges theoretical control design with practical ground validation, particularly in the context of ESA-led projects. The recurring themes across his publications include autonomous rendezvous, manipulator control for space robots, and robust GNC under uncertain conditions. Scientific Contributions: Key contributor to ESA's e.Deorbit mission studies, focusing on capture and deorbiting of defunct satellites like Envisat. Developed and tested GNC systems for the HERACLES lunar ascent element. Involved in the COMRADE project for combined control of robotic spacecraft and manipulators. Worked on GUIBEAR project for bearings-only rendezvous navigation. Advising and Grants: While no formal students are listed, his research is supported by major European space initiatives, likely involving collaborative grants from ESA and industrial partners such as Airbus. His work involves experimental validation and prototype development, indicating access to advanced research funding and facilities. Labs and Teams: Although specific lab affiliations are not mentioned, his involvement in projects like WMS LEMUR and e.Deorbit suggests collaboration with ESA’s GNC teams and space robotics laboratories focused on on-orbit servicing and debris removal technologies.

• Robotics
• Humanoid Robotics
• Bio-inspired Locomotion
• +7 more

Vincent Hugel is a Professor at the University of Toulon, affiliated with the Mechanical and Robotic Systems Design Laboratory. He previously served as a lecturer at the University of Versailles-Saint-Quentin-en-Yvelines from 2000 to 2014. His research is centered on robotics, particularly humanoid and bio-inspired systems, compliant mechanisms, and advanced robotic manufacturing. Research Interests: Dr. Hugel's work spans humanoid robotics , bio-inspired locomotion (especially avian and bipedal movement), compliant spine design , tactile sensing , underwater robotics , and multi-axis additive manufacturing . His studies often integrate biomechanical analysis with robotic implementation, as seen in projects like ROBOCOQ for bird leg modeling. Publication Trends: His recent work (2021–2023) focuses on additive manufacturing (WAAM, medical orthotics) and underwater gesture recognition using deep learning. Earlier publications (2005–2017) emphasize kinematic modeling , visual servoing , and humanoid design (e.g., NAO robot). The interdisciplinary nature of his research bridges mechanical engineering, control theory, and artificial intelligence. Scientific Awards: No specific awards or fellowships were mentioned in the provided text. Advising and Grants: Dr. Hugel has supervised doctoral research, including Mouna Souissi’s thesis on humanoid spine design (2012) and served as jury president for Gamal Elghazaly’s thesis (2017). He has collaborated on multiple projects involving robotic manufacturing and underwater systems. While specific grants are not listed, his sustained publication record suggests active research funding. Labs and Teams: He is a key member of the Mechanical and Robotic Systems Design Laboratory at the University of Toulon. He has contributed to the L3M-SIM and L3M SPL RoboCup teams, focusing on humanoid robotics and simulation. His collaborations extend to researchers in biomechanics, control systems, and additive manufacturing, indicating a strong interdisciplinary network.

Shahab Heshmati-AlamdariView profile

Associate Professor

• Robotics
• Autonomous Systems
• Control Systems
• +5 more

Shahab Heshmati-Alamdari is an Associate Professor in Robotics at Aalborg University's Department of Electronic Systems. His work focuses on robust control, autonomous systems, and underwater robotics. He holds a PhD from NTUA (2018) and held postdoctoral positions at TU Munich (2020) and KTH Royal Institute of Technology (2019–2020). His research emphasizes constrained planning, cooperative control, and human-robot interaction. Education: MEng (Mechanical Engineering), MSc (Automatic Control Systems & Robotics), PhD (Mechanical Engineering), all from NTUA. Research Interests: Constrained navigation, robust control in uncertain environments, cooperative robotics, and underwater vehicle systems. Awards: Marie Sklodowska-Curie Fellowship, ERCIM Postdoctoral Fellowship, Thomaidion Awards. His lab, the Safe Autonomous Systems Lab, develops advanced planning and control systems for single/multi-robot systems. Key platforms include the MuR250 mobile manipulator, Boston Dynamics Spot, and custom ballbots like Kugle. He teaches courses in motion planning and robot navigation at Aalborg University. Recent work includes control barrier functions for UAV navigation, robust predictive control for underwater vehicles, and cooperative manipulation systems. His projects address marine debris cleanup (SeaClear EU project) and safe human-robot interaction.

Justus PiaterView profile

Professor

• Robotics
• Robot Learning
• Robot Perception
• +3 more

Justus Piater is a Professor of Computer Science at the University of Innsbruck, serving as the Head of the Digital Science Center and an ELLIS Fellow. His primary affiliation is the Department of Computer Science within the Faculty of Mathematics, Computer Science and Physics. He has held academic roles since 2002, including Assistant and Associate Professorships at Université de Liège before joining the University of Innsbruck in 2010. His research focuses on robot learning, perception, and manipulation, emphasizing how robots can learn to perceive and act with understanding. Notable projects include the EU-H2020 IMAGINE project and the Euregio International Project Network OLIVER. Education includes a Ph.D. in Computer Science from the University of Massachusetts Amherst (2001), complemented by earlier studies in Germany and Belgium. His service roles include Dean of the Faculty of Mathematics, Computer Science and Physics (2014–2017) and Vice Chair of the Department of Computer Science (2014–present). His research outputs span robotics, AI, and interdisciplinary education, with a strong emphasis on autonomous systems and cognitive development.

Haoxiang LangView profile

Associate Professor

• Mechatronics
• Autonomous Robotics
• Visual Servoing
• +3 more

Haoxiang Lang serves as Department Chair and Associate Professor in the Department of Automotive and Mechatronics Engineering at Ontario Tech University's Faculty of Engineering and Applied Science. His laboratory, GRASP Lab, focuses on advanced robotics and intelligent systems research. Education: PhD in Mechanical Engineering, University of British Columbia (2013) MASc in Mechanical Engineering, University of British Columbia (2008) BSc in Marine Engineering, Ningbo University (2003) Dr. Lang's research spans mechatronics, autonomous robotics, visual servoing, and machine learning. His work focuses on developing advanced control systems for robotic manipulation, autonomous vehicle navigation, and sensor fusion techniques. Recent projects include vision-based combat vehicle control, deep learning for aerial image processing, and thermal management for robotic systems. His publications demonstrate strong emphasis on robotic perception-control integration, with recurring themes in visual servoing, sensor fusion, autonomous navigation, and machine learning applications in robotics. Recent works increasingly incorporate deep neural networks for complex tasks like object manipulation and environment mapping. Dr. Lang leads the GRASP Lab, which develops experimental platforms including autonomous combat vehicles and robotic manipulators. The lab focuses on practical implementations of control theories and collaborates on industrial applications.

Timothy WileyView profile

Lecturer

• Autonomous Robotics
• Artificial Intelligence
• Online Learning
• +6 more

Dr. Timothy Wiley is a Lecturer in Computer Science at RMIT University's School of Computing Technologies within the STEM College. He specializes in Artificial Intelligence and Robotics, focusing on autonomous systems, online learning, and human-robot interaction. His roles include leading the RedbackBots RoboCup team and designing core courses in AI and robotics. He holds a PhD from UNSW Sydney and has extensive industry and academic collaborations, including with Rheinmetall Defence Australia and Nova Systems. Affiliations: RMIT AI Innovation Lab, CIAIRI, RUASRT Education: PhD (Computer Science, UNSW), BSc (Computer Science, UNSW) Research: Autonomous robotics, Explainable AI, UAV systems, fatigue crack modeling Research interests center on data-efficient machine learning for robotics, explainable AI, and applications in agriculture, aviation, and defense. Recent projects include UAV delivery systems and AR visualization for RoboCup. He teaches courses like Programming Autonomous Robots and leads the first-year Programming Studios. Notable achievements include the 2025 Best Paper Award at HRI and finalist status in RMIT's 2023 Research Leadership Awards. His work bridges academic research with industry applications, such as food waste reduction in macadamia harvesting and urban wind environment modeling for AAM.

Stasha LauriaView profile

Lecturer

• Intelligent Robotics
• Neural Networks
• Pattern Recognition
• +6 more

Dr. Stasha Lauria is a Lecturer in the Department of Computer Science within the College of Engineering, Design and Physical Sciences at Brunel University London. With over 15 years of experience in intelligent robotics, she specializes in human-machine interactions, neural networks, and pattern recognition, leading the Brunel Robotics Laboratory for cognitive mobile robot experiments. Education: Laurea, University of Studies “Federico II” of Napoli, Italy Ph.D. in Cybernetics, University of Reading, UK Research Focus: Her work centers on modeling mobile robots through natural language interactions, converting human speech into robot actions, and AI-driven signal processing. Current projects investigate social media's impact on human-robot dialogue management and robotics as educational tools, with strong emphasis on neural networks and big data applications in vision systems. Publication Trends: Recent publications (2022-2009) reveal consistent innovation in computer vision (object detection, segmentation) and human-robot interaction, increasingly integrating deep learning for manufacturing and vision tasks. Educational robotics remains a parallel thread, with quantitative evaluations of programming pedagogy. Research Grants: A human-centred internet of things platform for the sustainable mine of the future (European Commission, May 2020 - April 2024) Intelligent data-driven pipeline for certified metal parts manufacturing (European Commission, October 2018 - March 2023) Big Data Learning-based QoS Analysis for Cloud-services (Royal Society, March 2016 - February 2018) Laboratory & Collaboration: Founder of the Brunel Robotics Laboratory, she collaborates extensively with Dr. Theodora Koulouri, Prof. Xiaohui Liu, and Dr. Stephen Swift on human-robot interaction, as evidenced by co-author networks spanning neural networks, dialogue systems, and multi-agent architectures.

• Environmental Robotics
• Robotic Vision
• Deep Learning
• +3 more

Dr. Dorian Tsai is a Research Fellow and Associate Investigator at the Queensland University of Technology (QUT) Centre for Robotics, affiliated with the School of Electrical Engineering & Robotics. His research focuses on environmental robotics, robotic vision, and deep learning applications for large-scale environmental challenges. He currently leads the Technology Development stream in the Reef Restoration and Adaptation Project (RRAP), developing robotic technologies for coral monitoring and endangered species tracking. Education: Bachelors in Engineering Science (University of Toronto), Masters in Space Science & Technology (Lulea Technical University), Robotics & Automation (Aalto University), and a PhD in Robotics from QUT. His doctoral work involved light field features for camera motion control, completed under supervisors Prof. Peter Corke, Dr. Donald Dansereau, and Dr. Thierry Peynot. Research emphasizes robotic solutions for marine conservation (e.g., Great Barrier Reef preservation), precision agriculture, and autonomous systems. His work combines machine learning, computer vision, and robotics engineering to address real-world environmental and industrial challenges. Prior to QUT, he worked at the Canadian Space Agency and completed thesis research at NASA's Jet Propulsion Lab on rover docking systems.

Luis Mejias AlvarezView profile

Associate Professor

• Unmanned Aerial Systems (UAS)
• Computer Vision
• Collision Avoidance
• +5 more

Luis Mejias Alvarez is an Associate Professor and Researcher in the School of Electrical Engineering & Robotics at Queensland University of Technology (QUT). He specializes in Unmanned Aerial Systems (UAS), focusing on vision-based guidance, collision avoidance, and autonomous navigation technologies. His work integrates computer vision, sensor fusion, and control systems to advance UAV applications in aerospace and robotics. Education: Electronic Engineer (UNEXPO, Venezuela, 1999) MSc in Networks and Telecommunication Systems (Universidad Politécnica de Madrid, 2001) PhD in Robotics and Automation (Universidad Politécnica de Madrid) Research Interests: His research spans Unmanned Aerial Systems (UAS), including autonomous helicopters, vision-based navigation, collision avoidance, and forced landing technologies. He develops algorithms for computer vision, sensor fusion, and control systems, with applications in aerospace engineering and artificial intelligence. His work aims to enhance UAV safety and autonomy in complex environments. Awards & Fellowships: 2017 Endeavour Executive Fellowship Visiting Professorships at Université de Bretagne Occidentale (2017) and UTIS (2017) Editor of Springer Tracts in Advanced Robotics (2016) Keynote Speaker at CIIMA 2014 Program Chair for UAS Conferences (2013) DECRA Fellowship (2012–2015) IRSES Grant (2009) Advising & Grants: Supervised PhD/Masters students in areas like vision-based collision avoidance and UAV navigation. Key grants include ARC DECRA and international IRSES collaboration with European institutions. Labs & Collaborations: Active in QUT’s Centre for Robotics and the Australian Research Centre for Aerospace Automation. Collaborates globally on projects like drone ship landing under adverse conditions and beyond-line-of-sight navigation.