جست‌وجوی استاد و پژوهشگر

Joshua Marshallمشاهده پروفایل

استاد

• Field Robotics
• Autonomous Vehicles
• Control Systems Engineering
• +۷ مورد دیگر

Joshua Marshall is a Professor of Electrical & Computer Engineering at Queen’s University, Canada, and Director of the Offroad Robotics research group. He holds a PhD from the University of Toronto and has cross-appointments in Mechanical & Materials Engineering and the Robert M. Buchan Department of Mining. His expertise spans field robotics, autonomous systems, control engineering, and harsh-environment applications in mining, space, and marine domains. He led the Ingenuity Labs Research Institute (2018–2024) and served as a Visiting Professor at Örebro University (2016–17). Dr. Marshall’s work focuses on autonomous vehicle navigation, robotic excavation, and spatiotemporal mapping. He has received the 2025 OPEA Engineering Medal and has commercialized technologies through partnerships with companies like Epiroc and RockMass Technologies. Education: PhD, Electrical & Computer Engineering, University of Toronto (2005) MSc(Eng), Mechanical Engineering, Queen’s University (2001) BSc (Hons), Engineering, (details not specified) Research Interests: Autonomous robotics in mining, space, and marine environments Data-driven control systems and model predictive control Proprioceptive sensing and terrain classification Multi-robot coordination and task planning Underground navigation and SLAM Professional Activities: Senior Member, IEEE Editorial roles: International Journal of Robotics Research , IEEE Transactions on Mechatronics Co-founded the NSERC Canadian Robotics Network (NCRN) Contributions to the IEEE Medal for Environmental & Safety Technologies Committee Labs/Teams: Offroad Robotics Group (Queen’s University) Ingenuity Labs Research Institute (founding Director) Advisor to Queen’s AutoDrive Challenge II Team and aQuatonomous ASV Design Club

Kyle B. Reedمشاهده پروفایل

دانشیار

• Rehabilitation engineering
• Haptics
• Human-robot interaction
• +۴ مورد دیگر

Kyle B. Reed serves as an Associate Professor in the Department of Mechanical Engineering at the University of South Florida's College of Engineering. His academic career at USF has progressed from Assistant Professor (2009-2016) to his current position as Associate Professor (2016-present), following postdoctoral research at Johns Hopkins University. He teaches specialized courses including Haptics (EML 4593/6594), Mechanical Controls, and Advanced Engineering Mathematics. Dr. Reed earned his Ph.D. (2007) and M.S. (2004) in Mechanical Engineering from Northwestern University, and his B.S. in Mechanical Engineering from the University of Tennessee-Knoxville (2001). Prior to his faculty position, he completed postdoctoral research at Johns Hopkins University's Laboratory for Computational Sensing and Robotics (2007-2009) and worked as a researcher at Los Alamos National Laboratory (1998-2001). His research focuses on rehabilitation engineering, haptics, human-robot interaction, and medical robotics, with applications in medical devices and rehabilitation technologies. The REED Lab (Rehabilitation Engineering and Electromechanical Design Lab), which he directs, develops innovative solutions for human motion analysis and assistive technologies. His work bridges fundamental engineering principles with clinical applications, particularly in stroke rehabilitation and assistive device development. Analysis of his publication record shows consistent contributions to haptics research, human-robot interaction, and rehabilitation engineering. His work spans theoretical investigations of human motor control to practical applications in medical devices, with publications appearing in venues like IEEE Transactions on Haptics, EMBC, and Haptics Symposium. Recent work emphasizes wearable haptic devices, rehabilitation robotics, and human factors in medical technology. Developed the Gait Enhancing Mobile Shoe (GEMS) prototype during postdoctoral work Created minimally invasive steerable needle system for biopsies at Johns Hopkins Established REED Lab focusing on rehabilitation engineering and haptic technologies Developed innovative haptic devices for communication, rehabilitation, and education Dr. Reed actively mentors students through the REED Lab, supervising both graduate and undergraduate researchers. His teaching philosophy emphasizes building intuition while providing frameworks for logical problem-solving. He incorporates substantial project components into his courses, with students regularly developing haptic devices and robotics applications that sometimes lead to publications. The lab maintains strong outreach connections, working with K-12 students to promote engineering education. The REED Lab, located in the Interdisciplinary Research Building Room 114 on USF's Tampa campus, serves as the hub for his research activities. Current projects include wearable haptic devices for communication, diagnostic tools for Parkinson's disease, and rehabilitation technologies for gait analysis. The lab maintains strong connections with both clinical partners and industry, facilitating translational research from concept to application.

Andrea Del Preteمشاهده پروفایل

دانشیار

• Robot Control
• Reinforcement Learning
• Trajectory Optimization
• +۷ مورد دیگر

Andrea Del Prete is an Associate Professor in the Industrial Engineering Department at the University of Trento (Italy) since 2022. His research focuses on robot control, reinforcement learning, trajectory optimization, and numerical algorithms for dynamic systems. He leads the Interdepartmental Robotics Lab (IDRA) and has previously held roles as a tenure-track assistant professor at the University of Trento (2019-2021), a research scientist at the Max-Planck Institute for Intelligent Systems (2018), and an associated researcher at LAAS-CNRS (2014-2017) working with the HRP-2 humanoid robot. Earlier, he conducted PhD and post-doc research at the Italian Institute of Technology (2010-2013) on iCub robot control. PhD in Robotics (2013) - Italian Institute of Technology MEng in Computer Engineering (2009) - University of Bologna BSc in Computer Engineering (2006) - University of Bologna Dr. Del Prete specializes in merging learning and model-based techniques for safe robot control, particularly in legged systems. His work bridges trajectory optimization (TO) with reinforcement learning (RL) to overcome local minima challenges (CACTO/CACTO-SL algorithms) and develops robust controllers for humanoid and quadrupedal robots in unstructured environments. He explores viability kernels in MPC, safety certificates, and bi-level optimization for co-designing hardware/control policies. Key application areas include mountain rescue robotics (ALPINE platform), aerial maneuver recovery, and energy-efficient legged locomotion. His recent publications (2023-2025) emphasize numerical optimization algorithms, multi-contact locomotion, and hybrid control frameworks. Topics span from analytical integral optimization (2025) to climbing robots for mountain operations (2025), demonstrating a trajectory from theoretical algorithm development to real-world robotic applications. Research keywords include robotics, numerical optimization, and machine learning, with sub-fields like MPC for dynamic systems, humanoid control, and terrain adaptation. As an educator, he teaches advanced courses on: Optimization and Learning for Robot Control (48-hour master's course) Optimization-based Control of Legged Robots (12-hour PhD course) Task-Space Inverse Dynamics (3-hour PhD course) Current PhD advisees include Mohammad Hasan Yeganegi (generalization bounds for imitation learning), Pietro Noah Crestaz (numerically-efficient RL), Veronica Campana (ergodic control for defect detection), Elisa Alboni (data-efficient model-based RL), and Gianni Lunardi (MPC for legged locomotion).

Michael L. Madiganمشاهده پروفایل

استاد

• Human Factors Engineering
• Ergonomics
• Occupational Biomechanics
• +۶ مورد دیگر

Michael L. Madigan is a Professor in the Grado Department of Industrial and Systems Engineering at Virginia Tech. His research focuses on human factors engineering, biomechanics, and ergonomics, particularly addressing issues related to slips, trips, falls, and musculoskeletal disorders. He leads the Madigan Biomechanics Group, which investigates the biomechanics of human motion and neuromuscular control to enhance occupational safety and elderly health. Education: Ph.D., Biomedical Engineering, Virginia Commonwealth University, 2001 M.S., Bioengineering, Texas A&M University, 1996 B.S., Bioengineering, Texas A&M University, 1994 Research Interests: Obesity’s impact on mobility, aging-related biomechanics, workplace ergonomics, and biomechanical interventions for fall prevention. His work combines experimental and computational methods to develop preventive measures like exercise interventions and ergonomic designs. Professional Roles: Editor-in-Chief, Journal of Applied Biomechanics (2017–present) Formerly Editor, Medicine and Science in Sports and Exercise (2013–2017) Secretary, American Society of Biomechanics (2009–2012) Awards: Kevin P. Granata Faculty Fellow (2013–2014) Virginia Tech College of Engineering Certificate of Teaching Excellence (2014) Finalist for International Society of Biomechanics Clinical Award (2005) Advising & Grants: Advised over 20 doctoral and undergraduate students since 2007. His grants support studies on obesity-related falls, exoskeleton design, and biomechanical modeling. Collaborates with the Virginia Tech-Wake Forest School of Biomedical Engineering and Sciences. Labs/Teams: Director of the Madigan Biomechanics Group and core member of the Occupational Ergonomics and Biomechanics Laboratories. Active in developing smart prosthetics and wearable technologies for injury prevention.

Matei T. Ciocarlieمشاهده پروفایل

دانشیار

• Robotic Manipulation
• Robotics Control Systems
• Human-Robot Interaction
• +۳ مورد دیگر

Matei T. Ciocarlie is an Associate Professor of Mechanical Engineering at Columbia Engineering, Columbia University. He holds affiliations with the Sense, Collect and Move Data Committee. His research focuses on reliable robotic performance in unstructured environments, emphasizing robotic hand designs, control systems, autonomous and Human-in-the-Loop mobile manipulation, shared autonomy, teleoperation, and assistive robotics. He also explores novel sensor integration (tactile, proprioceptive, range) in robotic systems. Education: Ph.D. in Mechanical Engineering from Columbia University (New York), with a dissertation on reducing computational complexity in dexterous robotic grasping. Professional Experience: Research Scientist and Group Manager at Willow Garage, Inc. Senior Research Scientist at Google, Inc. Awards: 2010 Robotdalen Scientific Award 2013 IEEE Robotics and Automation Society Early Career Award His work bridges mechanical and computational intelligence in robotics, prioritizing practical applications in human-centric environments.

• Gait Analysis
• Functional Task Analysis
• Neurological Rehabilitation
• +۷ مورد دیگر

Sylvie Nadeau is a Full Professor in the School of Rehabilitation at the University of Montreal's Faculty of Medicine. Her research focuses on locomotor activity assessment, rehabilitation interventions for neurological conditions, and biomechanical analysis of movement. She leads interdisciplinary projects addressing spinal cord injuries, stroke recovery, and mobility challenges in aging populations. Key affiliations include the INTER strategic research group and the REPAR provincial rehabilitation research network. She collaborates with institutions like the Institut de Réadaptation Gingras-Lindsay-de-Montréal (IRGLM) and has secured funding from agencies such as FRQNT, MITACS, and the Rick Hansen Institute. Her work integrates technologies like smart stationary bikes and real-time avatars to enhance rehabilitation outcomes. Research interests span gait analysis, dynamic balance, and sensorimotor rehabilitation. She has supervised over 30 graduate students, contributing to advancements in post-stroke mobility, incontinence management, and telerehabilitation. Recent projects include developing intelligent exercise systems and evaluating environmental impacts on mobility in museum settings. Directed the 2019 SOFPEL international congress Co-led the TRIVEL intelligent cycle prototype development Pioneered studies on bilateral upper limb coordination post-stroke Her teaching includes courses in physiotherapy and evidence-based practice, shaping future generations of rehabilitation professionals. She prioritizes translating research into clinical practice through innovative interventions and technology integration.

Stephen Brownمشاهده پروفایل

دانشیار

• Lumbar Spine Mechanics
• Muscle Physiology
• Biomechanics
• +۳ مورد دیگر

Dr. Stephen Brown is an Associate Professor in the Department of Human Kinetics at the University of Guelph. His research focuses on lumbar spine mechanics, muscle physiology, and injury rehabilitation. He holds a BHK and MHK from the University of Windsor, a PhD from the University of Waterloo, and completed postdoctoral training at the University of California San Diego. Education: BHK, MHK - University of Windsor PhD - University of Waterloo Post-doctoral Fellowship - University of California San Diego His research integrates anatomical studies, mechanical testing, and human participant analysis to address four core themes: lumbar spine function, injury mechanisms, adaptation responses, and rehabilitation strategies. Current work combines novel techniques like laser diffraction with biomechanical modeling to explore muscle-tissue interactions. His lab employs three main methodologies: cadaveric tissue analysis, mechanical testing of muscles/spine tissues, and human movement studies using EMG and kinematic modeling. Recent publications (2016–2018) highlight investigations into spine kinematics, kinesio taping effects, muscle fatigue impacts, and postural control in athletic populations. Advising & Grants: Advises 5 graduate students (3 PhD, 2 MSc) Teaching: HK*4600 Applied Human Kinetics II, HK*4240 Occupational Biomechanics Labs are located in ANNU 358/362. Research aims to reduce low-back pain incidence through mechanistic insights into spine-muscle interactions.

Yun Seong Songمشاهده پروفایل

دانشیار

• Physical Human-Robot Interaction
• Rehabilitation Robotics
• Wearable Devices
• +۳ مورد دیگر

Dr. Yun Seong Song is an Associate Professor in the Department of Mechanical and Aerospace Engineering at Missouri University of Science and Technology (Missouri S&T), directing the Physical Human-Robot Interaction Laboratory. He holds a Ph.D. from MIT (2012), M.S. from Carnegie Mellon University (2006), and dual B.S. degrees from Seoul National University (2004). Prior to joining Missouri S&T, he conducted postdoctoral research at EPFL (2012-13) and served as a postdoc/lecturer at Georgia Tech (2014-16). Recognized for both research and teaching excellence, he has received the NSF CAREER Award (2021) and Faculty Teaching Award (2019). His research focuses on the intersection of robotics and biomechanics, emphasizing physical human-robot interaction (pHRI), rehabilitation robotics, wearable devices, energy harvesting from human motion, and medical device design. Key projects include developing robots for overground interaction experiments and assistive technologies for mobility support. His lab explores human motor communication through stiffness modulation, haptic feedback systems, and energy-efficient human-assistance mechanisms. Notable achievements include pioneering interactive stairs for energy-efficient mobility and a light-touch based virtual cane for walking assistance. His work integrates mechanical engineering, control systems, and biomedical applications to advance assistive technologies and human-robot collaboration. Education: Ph.D. Mechanical Engineering, MIT (2012) M.S. Mechanical Engineering, CMU (2006) B.S. Mechanical Engineering & B.S.E. Computer Science, Seoul National University (2004) Awards: NSF CAREER Award (2021) Missouri S&T Faculty Teaching Award (2019) Lab Focus: Physical Human-Robot Interaction, Wearable Robotics, Biomechanical Energy Harvesting

David J Reinkensmeyerمشاهده پروفایل

استاد

• Neuroengineering
• Rehabilitation Robotics
• Motor Control
• +۳ مورد دیگر

David J. Reinkensmeyer is a Professor at the University of California, Irvine (UCI), holding appointments in the Department of Mechanical & Aerospace Engineering (The Henry Samueli School of Engineering), Anatomy & Neurobiology (School of Medicine), and Biomedical Engineering. His research focuses on neurorehabilitation engineering, developing robotic and sensor-based technologies to enhance motor recovery after neurological injuries such as stroke and spinal cord injury. He leads interdisciplinary efforts in robotic therapy, sensor design for movement assessment, and computational models of motor learning. Key areas include: Design of robotic devices for upper/lower extremity rehabilitation Development of wearable sensors to monitor home exercise programs Studying motor adaptation and proprioception in clinical populations Optimizing neurorehabilitation interventions through computational modeling His work integrates biomechanics, machine learning, and clinical neuroscience to create practical solutions for disabling movement disorders. Recent projects explore scalable mRehab systems, data-driven diagnostics, and real-time feedback technologies. Funding sources include NIH grants (e.g., R01 HD062744) and industry collaborations. Over 200 peer-reviewed publications and numerous patents reflect his impact in translating engineering innovations into clinical practice.

• Physical Therapy
• Rheumatology Rehabilitation
• Biopsychosocial Model in Rehabilitation
• +۳ مورد دیگر

Assoc. Prof. Dr. Sevim Öksüz serves as a faculty member in the Department of Physiotherapy and Rehabilitation at Eastern Mediterranean University's School of Health Services. Her academic foundation stems from Hacettepe University, where she completed her BS, MS, and PhD in Physiotherapy and Rehabilitation. Her educational journey includes: PhD in Physiotherapy and Rehabilitation (2013-2017), Hacettepe University MS in Physiotherapy and Rehabilitation (2009-2012), Hacettepe University BS in Physiotherapy and Rehabilitation (2005-2009), Hacettepe University Dr. Öksüz specializes in biopsychosocial rehabilitation approaches for rheumatic and musculoskeletal disorders, with particular expertise in Pilates-based interventions, osteoporosis management, and development of disease-specific assessment tools. Her research bridges clinical practice with psychosocial dimensions of chronic conditions including ankylosing spondylitis, fibromyalgia, and systemic lupus erythematosus. Analysis of her 2021-2024 publications reveals a dominant focus on validating biopsychosocial questionnaires for rheumatic diseases while rigorously comparing exercise modalities. A significant portion examines Pilates efficacy across diverse populations, from osteoporosis patients to those with spinal disorders, emphasizing functional outcomes and patient-centered metrics. Dr. Öksüz actively mentors graduate researchers through EMU's Physiotherapy and Rehabilitation programs: PhD supervision: Süleyman Güzelşemme (ongoing) Master's supervision: Ebru Kadioğlu (2024), Süleyman Güzelşemme (2023), Ayşe Nur Gancel (2022), Gizem Vaiz Haklıgil (2022), Merve Betül Öztarsu (2022), Özge Şahin (2020), Hande Karin Özgür (ongoing, co-supervised) She contributes to clinical research within EMU's specialized laboratories including the Cardiopulmonary Laboratory, Therapeutic Movements Laboratory, and Neurological Rehabilitation Unit, integrating evidence-based practice with academic instruction.

François Gouletteمشاهده پروفایل

استاد

• 3D Point Cloud Processing
• LiDAR Perception
• Autonomous Systems
• +۷ مورد دیگر

François Goulette is a Professor and Deputy Director of the Computer Science and Systems Engineering Unit (U2IS) at ENSTA Paris, part of Institut Polytechnique de Paris. His research focuses on 3D point cloud processing, LiDAR perception, and autonomous systems within the Robotics Center (CAOR). His primary research interests lie in 3D point cloud processing , LiDAR perception , and autonomous systems . His work spans fundamental algorithm development to practical applications in autonomous driving, cultural heritage digitization, and robotics. He has made significant contributions to domain generalization of LiDAR perception, semantic segmentation of 3D point clouds, and point cloud registration techniques. The analysis of his recent publications reveals a strong focus on domain generalization for LiDAR perception systems, with multiple papers addressing challenges in 3D semantic segmentation across different environments. His work combines multi-scale architectures , unsupervised learning , and dataset creation to advance the state-of-the-art in autonomous systems perception. The research spans both theoretical algorithm development and practical applications in urban environments. François Goulette leads research activities within the Robotics Center (CAOR) at ENSTA Paris. His team develops advanced techniques for 3D environment understanding, with applications in autonomous vehicles, cultural heritage preservation, and industrial robotics. The research combines computer vision, machine learning, and robotics to solve challenging problems in 3D perception and scene understanding.

Emily Bayerمشاهده پروفایل

استادیار

• Visceral Sensation
• Sexual Dimorphism
• Behavioral Genetics
• +۴ مورد دیگر

Emily Bayer is appointed as Assistant Professor of Neural Science and Biology at New York University, commencing January 2026. Her research program investigates neural mechanisms of visceral sensation and behavioral outputs, with emphasis on fertility status and sex differences using C. elegans and D. cerebrum (zebrafish) models. Her educational background includes: Ph.D. in Biological Sciences, Columbia University (2019) B.S. in Biology/German, Muhlenberg College (2014) Dr. Bayer's research explores how internal bodily sensations (visceral sensation) modulate behavior and environmental interaction, focusing on molecular and anatomical sex differences in neural circuits. Her lab examines how fertility status influences behavior through genetic and neural mechanisms, revealing conserved principles of neural circuit organization. Key approaches include C. elegans genetics, zebrafish neuroimaging, and behavioral analysis to dissect how reproductive state and sex converge in brain function. Analysis of her recent publications (2025-2016) demonstrates a cohesive focus on sexual dimorphism in neural development and behavior, with increasing integration of genomic and connectomic methodologies. Her work spans molecular genetics, neural circuit mapping, and behavioral phenotyping, consistently highlighting sex-specific differences in neural wiring and function across model organisms. Her scientific recognition includes: Research Fund for Excellent Junior Researchers (University of Basel, 2025) Jane Coffin Childs Memorial Fund for Medical Research Fellowship (2021-2023) Dr. Bayer has secured competitive fellowships supporting her independent research program. Her lab establishes innovative frameworks for studying visceral sensation-behavior relationships, with current work emphasizing monoaminergic signaling in experience-dependent neural plasticity and the role of conserved transcription factors in sexually dimorphic development. Future directions include expanding to vertebrate models to investigate evolutionary conservation of these mechanisms. She leads a research team utilizing C. elegans and zebrafish to dissect neural circuits underlying internal sensation, with particular focus on how fertility signals modulate social and mating behaviors through sex-specific neural pathways.

Andrew Sabelhausمشاهده پروفایل

استادیار

• Soft Robotics
• Control Systems
• Mechanical Design
• +۳ مورد دیگر

Andrew Sabelhaus is an Assistant Professor of Mechanical Engineering at Boston University, focusing on control-oriented approaches to soft and flexible robot locomotion. His work integrates modeling, feedback control, and mechanical design to balance autonomous decision-making with embodied intelligence, enabling safe operation in unstructured environments. His research spans soft robotics , actuator design , and feedback systems , with applications in medical devices, underwater locomotion, and autonomous systems. Recent work emphasizes real-time trajectory generation , control barrier functions , and self-sensing actuators . 2025: Soft Robotics for Cardiac Interventions 2025: Thermoelectric Actuators 2025: Differential Flatness in Motion Planning 2024: CAREER Award in Safe Autonomy Key contributions include Dismech , a discrete geometry-based simulator, and advancements in shape memory alloy artificial muscles . He received his Ph.D. from the University of California, Berkeley.

Ross Armstrongمشاهده پروفایل

دانشیار

• Musculoskeletal screening
• Hypermobility
• Systematic reviews
• +۴ مورد دیگر

Ross Armstrong is an Associate Professor in Musculoskeletal and Population Health at the University of Cumbria's Pears Cumbria School of Medicine, serving as Programme Lead for the Master of Research programme. He previously held roles at Edge Hill University and has extensive clinical experience in NHS, private practice, professional sports (including Liverpool FC and Gillingham FC academies), military, and international events like the Olympics and Commonwealth Games. His research focuses on musculoskeletal screening, hypermobility, systematic reviews, and dance medicine. He leads the Healthy Ageing Research Team and co-leads the Rehabilitation and Healthy Lives Group and Systematic Review Group. Education: BSc (Hons) Sports Science and Physiology (University of Leeds, 1998); MSc Physiotherapy (Teesside University, 2002); MSc Sports and Exercise Medicine (Queen Mary University, 2013); PhD (Musculoskeletal Screening: Implications for Injury and Performance, Edge Hill University). Research interests include injury prevention, clinical prediction rules, and dance medicine. He has contributed to over 50 peer-reviewed publications, Cochrane reviews, and book chapters. Current roles include editorial board memberships for journals like Telethusa and Frontiers in Sport and Active Living , plus external advisory roles for physiotherapy programs. Grants: £50,000 co-applicant for the EPSRC NortHFutures 2025 project on digital health technologies for frailty monitoring. Active in supervising PhD candidates with a focus on musculoskeletal health and rehabilitation. Labs/Teams: Leads the Healthy Ageing Research Team and collaborates with the Brazil/UK Dance Medicine and Science Network and Somatic Practice and Chronic Pain networks.

Babar Jamilمشاهده پروفایل

مدرس

• Robotics
• Control Engineering
• Sensors
• +۵ مورد دیگر

Dr. Babar Jamil is a Lecturer in Electrical Engineering at the University of York's School of Physics, Engineering and Technology. His expertise spans robotics, sensors, control engineering, and mechanism design. He holds a Ph.D. from Hanyang University (South Korea) and conducted postdoctoral research at Sungkyunkwan University, where he also served as a Research Professor. His current research focuses on safe human-robot collaboration systems, novel control algorithms for robotic systems, and smart structures through sensor integration. Education: Ph.D. in Electrical and Electronic Engineering, Hanyang University, South Korea Postdoctoral Researcher, Sungkyunkwan University, South Korea Research Interests: Developing hybrid robotic manipulators combining soft and rigid actuation Designing proprioceptive sensors for extreme environments Advances in pneumatic artificial muscles and soft actuators Integration of machine learning in robotics control systems Publications: Recent work emphasizes soft robotics actuators, sensor design, and human-robot interface innovations. Key themes include energy-efficient actuation, sensorized robotic fingers, and pumpless pneumatic systems. Labs/Teams: Leads robotics research at York, focusing on collaborative robotics and sensor-actuator integration. Maintains an active research group through his UoY Robotics website .