جست‌وجوی استاد و پژوهشگر

Josie Hughesمشاهده پروفایل

استادیار

• Soft Robotics
• Robot Design
• Fabrication
• +۴ مورد دیگر

Josie Hughes is a Tenure Track Assistant Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) within the School of Engineering's Institute of Mechanical Engineering. She leads the Computer Robot Design and Fabrication Laboratory (CREATE Lab) and serves on the doctoral program committee for Robotics, Control and Intelligent Systems. Her roles include teaching courses in product development, engineering design, and data-driven manufacturing methods while maintaining active research and student supervision. Her research centers on soft robotics with emphasis on adaptive design, fabrication techniques, and real-world applications. Key areas include agricultural robotics (exemplified by the GraspBerry raspberry harvester), biomimetic materials like self-healing e-skins, and developmental robotics (BabyBot project). She pioneers approaches integrating morphological computation, variable stiffness mechanisms, and machine learning for robotic control, while championing open-source principles and diversity in robotics through accessible educational initiatives like balloon robot kits. Analysis of her recent publications reveals dominant trends in soft robotics adaptability, particularly in variable-stiffness structures, sensor integration, and task-specific optimization. Her work bridges fundamental material science with practical applications in agriculture, food science, and human-robot interaction, frequently employing computational methods like Bayesian optimization and neural networks for design and control. Scientific awards: No specific awards were mentioned in the source materials. Dr. Hughes actively supervises 16 doctoral students across diverse projects including soft grippers for agriculture, biomimetic locomotion, and robotic manipulation systems. Her advising portfolio shows strong alignment with her research themes, with current students working on topics like modular soft arms, agricultural automation, and developmental robotics. While grant details weren't specified, her high publication volume indicates robust research funding. The CREATE Lab under her leadership focuses on holistic co-design of hardware and software for soft robotic systems, with notable projects including the GraspBerry agricultural harvester and BabyBot developmental platform. The lab emphasizes open-source development and educational outreach, maintaining strong industry and academic collaborations while pushing boundaries in reconfigurable robotics and human-centered applications.

Qingguo Liمشاهده پروفایل

استاد

• Biomechanical system design
• Energy harvesting
• Wearable sensors
• +۴ مورد دیگر

Qingguo Li is a Professor and Associate Head at the Department of Mechanical and Materials Engineering , Queen's University , and a member of the Ingenuity Labs Research Institute . He specializes in biomechanical system design, energy harvesting, wearable sensors, gait analysis, and load carriage systems. His research integrates robotics, biomedical engineering, and sensor technology to develop human-centric devices and mobility aids. Current Roles : Professor, Associate Head, Queen's University Research Institute : Ingenuity Labs Research Institute Lab : Bio-Mechatronics and Robotics Laboratory His work focuses on biomechanical energy harvesting , IMU-based motion analysis , and assistive device development . Key applications include stroke rehabilitation, gait monitoring, and wearable power generation systems. Articles span cable-driven robots , smart walkers , and 3D printing mechanisms , emphasizing human-robot interaction and dynamic modeling . The lab explores sensor calibration , adaptive control algorithms , and human movement optimization . Areas of impact include rehabilitation engineering , load carriage stability , wearable sensor accuracy , and assistive robotics . His team develops solutions for gait asymmetry detection , post-stroke mobility , and low-cost energy systems , leveraging machine learning and kinetic modeling .

Javad Dargahiمشاهده پروفایل

استاد

• Haptic Sensors
• Robotics
• Biomedical Engineering
• +۵ مورد دیگر

Javad Dargahi is a Professor of Mechanical, Industrial and Aerospace Engineering at Concordia University, Montreal. His research focuses on haptic sensors, robotic systems for minimally invasive surgery, and smart sensor fabrication using micromachining and piezoelectric polymers. He leads projects in teletaction, embedded force sensing for soft robots, and medical device innovation. Research interests include tactile sensor design for robots and endoscopes, nonlinear impedance matching in surgical robotics, and deep learning-driven force estimation for catheters. His work bridges mechanical engineering with biomedical applications, emphasizing safety and precision in interventional surgeries. Recent publications explore multitask neural architectures for intracardiac catheters, real-time force control algorithms, and biomimetic soft robotics. His lab develops miniature optical sensors and stiffness-adaptive systems for surgical tools, with applications in cardiac ablation and vascular navigation.

Leila Notashمشاهده پروفایل

استاد

• Robotics
• Mechatronics
• Kinematics
• +۳ مورد دیگر

Dr. Leila Notash is a Professor in the Department of Mechanical and Materials Engineering at Queen's University, where she has been a faculty member since 1997. She is a Fellow of Engineers Canada (FEC) and a licensed Professional Engineer with Professional Engineers Ontario (PEO), with significant contributions to engineering education and professional service. Her educational background includes: Bachelor of Science in Mechanical Engineering, Middle East Technical University (Ankara, Turkey) - High Honor Student (2nd out of 166) Master of Applied Science in Mechanical Engineering, University of Toronto PhD in Mechanical Engineering, University of Victoria Dr. Notash's research centers on robotics and mechatronics, with specialized expertise in cable-driven parallel manipulators. Her work integrates kinematics, fault-tolerant design, and neural network applications to address challenges in robot calibration, workspace analysis, and motion control under real-world constraints like cable mass and elasticity. She investigates both theoretical frameworks and practical implementations for industrial and specialized robotic systems. Analysis of her recent publications (2020-2024) reveals a clear trajectory toward intelligent control systems, where machine learning techniques—particularly neural networks and reinforcement learning—are increasingly applied to solve complex problems in cable-driven robotics. This includes motion control optimization, path generation, and kineto-static analysis while accounting for physical limitations such as cable elasticity and mass effects, demonstrating a shift from traditional mechanical analysis to data-driven adaptive control methodologies. Her scientific recognition includes: Fellow of Engineers Canada (FEC) University of Toronto Open Fellowship University of Toronto International Differential Fee Waiver Charles S. Humphrey Graduate Student Award NSERC Doctoral Prize Nominee (1996) Dr. Notash has mentored 161 undergraduate students as Faculty Advisor for the Mechanical '06 cohort and pioneered international educational initiatives like the International Undergraduate Student Design project (IVDS), connecting Queen's University with Middle East Technical University and Union College. Her service extends to editorial leadership for Mechanism and Machine Theory and ASME journals, and governance roles including Faculty Senator at Queen's University (2009-2025) and PEO Council Councillor-at-Large (2019-2025). She has established collaborative research networks through initiatives like the Reading Week shop course 'Design Basics 1.0' and sustained leadership in the Canadian Committee for the Promotion of Mechanism and Machine Science (CCToMM) and the International Federation for the Promotion of Mechanism and Machine Science (IFToMM), where she chaired the Permanent Commission on Communications (2006-2011).

• Rehabilitation Robotics
• Dynamic Systems and Control
• Optimization
• +۶ مورد دیگر

Sunil K. Agrawal is a Professor of Mechanical Engineering and Professor of Rehabilitation and Regenerative Medicine at Columbia University, where he directs a highly interdisciplinary rehabilitation robotics program bridging the School of Engineering and Applied Sciences and the College of Physicians and Surgeons. His research focuses on developing robotic systems to restore and enhance human mobility for individuals with neurological disorders, pediatric conditions, and age-related decline. Education: PhD in Mechanical Engineering, Stanford University, 1990 MS in Mechanical Engineering, Ohio State University, 1986 BS in Mechanical Engineering, Indian Institute of Technology (IIT) Kanpur, 1984 Research Focus: Dr. Agrawal’s work centers on rehabilitation robotics , where he integrates dynamic systems, control theory, and optimization to create robotic devices that assist in gait training, balance improvement, and functional movement restoration. His studies span stroke, Parkinson’s disease, cerebral palsy, vestibular disorders, and spinal cord injury, using devices like the Tethered Pelvic Assist Device (TPAD) and robotic exoskeletons. Scientific Honors: Machine Design Award, ASME (2016) Robotics and Mechanisms Award, ASME (2016) Fellow, American Institute of Medical and Biological Engineering (AIMBE) (2016) Fellow, American Society of Mechanical Engineers (ASME) (2004) Alexander von Humboldt Foundation U.S. Senior Scientist Award (2007) Friedrich Wilhelm Bessel Research Award (2002) Presidential Faculty Fellow Award, The White House (1994) Research Collaborations & Funding: Dr. Agrawal collaborates with faculty across Neurology, Rehabilitation Medicine, Pediatric Orthopedics, Otolaryngology, Geriatrics, and Psychiatry. His work is supported by the National Science Foundation, National Institutes of Health, and the Spinal Cord Injury Research Board. Laboratory & Outreach: He leads an active research group focused on translational robotic systems, with ongoing clinical trials for stroke, Parkinson’s, cerebral palsy, and elderly fall prevention. His lab develops novel robotic braces, exoskeletons, and VR-integrated training platforms.

Ryan Caverlyمشاهده پروفایل

دانشیار

• Control Theory
• Dynamic Modeling
• Aerospace Systems
• +۸ مورد دیگر

Ryan Caverly serves as an Associate Professor in the Department of Aerospace Engineering and Mechanics at the University of Minnesota, Twin Cities, holding the prestigious McKnight Land-Grant Professorship. His research bridges theoretical control frameworks with practical aerospace and robotics applications, focusing on dynamic modeling and system control. Education: BS in Honours Mechanical Engineering from McGill University MS in Aerospace Engineering from the University of Michigan PhD in Aerospace Engineering from the University of Michigan Professor Caverly's research centers on input-output stability, robust control of nonlinear systems, and computationally efficient modeling of flexible structures. His work spans aerospace vehicles, spacecraft, and robotic manipulators, emphasizing theoretical rigor alongside real-world implementation challenges in structural flexibility and control precision. Recent publications reveal strong emphasis on predictive control for orbital mechanics, hypersonic vehicle dynamics, and cable-driven systems. His work consistently integrates convex optimization, state estimation, and structural dynamics to solve complex problems in solar sail technology, UAV navigation, and hypersonic flow measurement. Scientific Awards: McKnight Land-Grant Professor Caverly leads multiple externally funded projects including NASA-sponsored research on solar sail momentum management, UAV state estimation with Honeywell, hypersonic bow shock measurements with the Air Force, and deployable space structure control. His grants portfolio demonstrates significant industry and government collaboration in aerospace innovation. He directs the Aerospace, Robotics, Dynamics, and Control (ARDC) Lab, which specializes in the intersection of dynamic modeling and control theory for flexible multi-body systems, with particular focus on cable-driven mechanisms and lightweight aerospace structures.

Changyang Liمشاهده پروفایل

مدرس

• Robotics
• Fusion Reactor Engineering
• Remote Maintenance Systems
• +۲ مورد دیگر

Changyang Li serves as a University teacher in the Department of Mechanical Engineering at LUT University's School of Energy Systems in Lappeenranta, Finland. His institutional contact includes email Li.Changyang@lut.fi and phone +358 50 301 7482. Dr. Li's research specializes in robotics for nuclear fusion infrastructure, with emphasis on remote maintenance systems for tokamak reactors. His work addresses critical engineering challenges in vacuum vessel assembly, port-based maintenance, and heavy-duty manipulator design for next-generation reactors like DEMO and CFETR. Key methodologies include multi-objective optimization, kinematic mechanism analysis, and data-driven modeling of robotic systems operating in high-radiation environments. Analysis of his 15 publications (2019-2025) reveals concentrated expertise in DEMO reactor maintenance robotics, particularly mobile parallel mechanisms and cable-driven systems. His research demonstrates consistent focus on enhancing remote maintainability through innovations in elephant trunk robots, port closure tools, and in-situ machining solutions, directly supporting international fusion energy initiatives. No scientific awards are documented in available sources. No information is available regarding student supervision or research grant acquisitions. Specific laboratory affiliations or research team structures are not disclosed in the source materials.

Keyvan Hashtrudi-Zaadمشاهده پروفایل

استاد

• Haptics
• Telerobotics
• Tele-rehabilitation
• +۵ مورد دیگر

Keyvan Hashtrudi-Zaad is a Professor in the Department of Electrical and Computer Engineering at Queen's University, affiliated with the Smith School of Engineering and the Ingenuity Labs Research Institute. His expertise spans robotics and control systems, with a focus on haptics, telerobotics, tele-rehabilitation, autonomous vehicles, and medical robotics. He holds the email addresses keyvan.hashtrudi-zaad@queensu.ca and khz@queensu.ca, and his office is located in Walter Light Hall, Room 427. Research Interests: His research emphasizes human-robot interaction, haptic interfaces, autonomous systems, and mechatronics. Key areas include kinesthetic haptics, collaborative teleoperation systems, energy storage systems for electric vehicles, and medical robotics applications such as needle deflection estimation and rehabilitation robotics. His work bridges theoretical control systems with practical applications in healthcare and autonomous technologies. Publications: His recent work addresses challenges in haptic system stability, energy-efficient inverters for electric vehicles, and teleoperation networks. Notable projects include a cable-driven parallel robot for stroke rehabilitation and a study comparing DC/BLDC actuators for haptic feedback. His research often integrates sensor fusion, nonlinear control, and dynamic modeling to solve real-world problems. Awards and Recognition: While specific awards are not listed, his extensive publication record and leadership in interdisciplinary robotics initiatives highlight his contributions to the field. He is part of the Interactive Robotics and Intelligent Systems (IRIS) Laboratory, advancing innovations in medical robotics and autonomous systems. Grants and Collaborations: His work likely involves collaborations across engineering and medical disciplines, supported by grants focused on robotics, control systems, and healthcare technologies. The IRIS Lab serves as a hub for developing cutting-edge solutions in haptic training systems and assistive robotics.

• Compliant Mechanisms
• Robotics
• Precision Manufacturing
• +۵ مورد دیگر

Dr. Guangbo Hao is a Professor of Mechanical Engineering at University College Cork (UCC), where he leads the UCC CoMAR research group and directs the Mechatronics/Robotics Lab. He holds dual PhDs from Northeastern University (China, 2008) and Heriot-Watt University (UK, 2011). His research focuses on compliant mechanisms, robotics, and their applications in precision manufacturing, energy harvesting, and medical devices. He has secured over €1.3M in research funding, including grants from SFI, EU Horizon 2020, and Enterprise Ireland. He is an ASME Fellow and has received multiple accolades, including the ASME Compliant Mechanisms Award (2017, 2018, 2022) and the UCC President’s Excellence in Teaching Award (2023). Education: BSc (2004), MSc (2007), PhD (2008) from Northeastern University; second PhD (2011) from Heriot-Watt University Research interests include compliant mechanisms, mechatronics, and robotics with emphasis on deployable structures, medical devices, and energy harvesting systems. His work has resulted in over 200 peer-reviewed publications and 30 invited talks. He supervises students in PhD, research-master, and taught-master programs, with notable student achievements in international competitions and awards. Professional roles include Associate Editorships at Advanced Equipment , ASME Journal of Mechanisms and Robotics , and IEEE Robotics and Automation Letters . He chairs major conferences like ASME IDETC/CIE 2025 and co-chairs the 2026 IEEE/ASME AIM conference. His labs, including the UCC Engineering Maker Lab, focus on innovation in robotics and mechatronics.

Dongming Ganمشاهده پروفایل

دانشیار

• Robotics
• Human-Robot Interaction
• Mechanism Design
• +۵ مورد دیگر

Dr. Dongming Gan is an Associate Professor in the School of Engineering Technology at Purdue University, part of the Purdue Polytechnic Institute. His research focuses on robotics, mechanism design, and human-robot interaction, with an emphasis on compliant systems and wearable devices. He holds PhDs in Robotics and Mechatronics from King’s College London and Beijing University of Posts and Telecommunications. Prior roles include postdoctoral work at the Italian Institute of Technology and faculty positions at Khalifa University. He has authored over 130 journal/conference papers and six patents. His work includes advancements in variable stiffness actuators, soft robotics, and sensor integration for safe human-robot collaboration. Notable awards include the 2023 Freudenstein Young Investigator Award (ASME) and ASME Fellow status. Current leadership roles include serving as an Associate Editor for Mechanism and Machine Theory, ASME Journal of Mechanisms and Robotics, and Robotica. He also chairs major conferences like ASME IDETC-CIE 2025 and IEEE/IFToMM ReMAR 2024. Recent grants total over $900K, including NSF funding for variable stiffness actuators and safe human-robot interaction. Research interests span robotics design, industrial automation, and bio-inspired systems. His lab (C3RL) develops innovative robotic solutions for healthcare, manufacturing, and human-robot coexistence scenarios.

Ali Tavallaeiمشاهده پروفایل

استادیار

• Image Guided Therapy
• Cardiovascular Interventions
• Medical Imaging Instrumentation
• +۳ مورد دیگر

Ali Tavallaei serves as an Assistant Professor at Toronto Metropolitan University since 2019 and concurrently holds a Visiting Scientist position at Sunnybrook Research Institute. He is also the President and Co-founder of Magellan Biomedical Inc. (2018-present) and Vital Biomedical Technologies Inc. (2012-present), demonstrating strong industry engagement in medical device commercialization. His academic foundation includes: Ph.D. in Biomedical Engineering from Western University (2010-2015) Medical Innovation Fellowship at University of Minnesota/Western University (2015-2016) Postdoctoral Fellowship at Sunnybrook Research Institute, University of Toronto (2016-2019) Dr. Tavallaei's research centers on image guided therapy with emphasis on solving unmet clinical needs in minimally invasive interventions. His core focus areas include: Cardiovascular device innovation and evaluation Medical imaging instrumentation for real-time guidance Robotic systems for catheter navigation Mechatronic solutions for therapeutic delivery His work bridges engineering design with clinical translation through preclinical and clinical validation. Recent publications (2023-2026) reveal a concentrated effort in developing next-generation catheter technologies, including steering mechanisms (CathPilot), imaging tools (CathEye, CathCam), and specialized devices for vascular interventions. The research consistently emphasizes performance validation, mechanical characterization, and clinical feasibility across peripheral artery disease, aneurysm repair, and cardiac ablation applications. As director of the Medical Devices and Systems Lab, Dr. Tavallaei leads a translational research program focused on fundamental advances in cardiovascular disease management. The lab's workflow integrates solution design, system verification, preclinical testing, and technology transfer to address global healthcare challenges posed by cardiovascular diseases—the leading cause of death worldwide.

• Industrial Automation
• Robotics
• Control Systems
• +۷ مورد دیگر

Julio Garrido Campos is a full-time researcher at the University of Vigo , affiliated with the School of Industrial Engineering and the Department of Systems and Automation Engineering . He is a member of the research group EN.EDI Efficient and Digital Engineering , focusing on advanced robotics, industrial automation, and digital manufacturing standards. Education: Doctor from the University of Vigo (1999) with a thesis on technical information exchange in concurrent engineering environments, supervised by Dr. Ricardo Marín Martín. His research spans mechatronics , cable-driven parallel robots (CDPR) , motion control systems , and STEP-NC standards for manufacturing. Recent work includes marine robotics applications for underwater load handling, 3D printing for maritime plastic circular economy initiatives, and digital twin development for industrial automation. Publications highlight trends in robotics for rehabilitation , custom non-conventional robotics , and energy-efficient manufacturing . He has contributed to frameworks for integrating simulation, control, and management tools in industrial digital twins. No specific scientific awards are mentioned in the provided text. Labs & Teams: Garrido Campos works within the Laboratorio de manutención e informática industrial Ricardo Marín , a group dedicated to industrial automation and mechatronics research for 25+ years.

• Autonomous Driving
• V2X Communication
• Robotics
• +۳ مورد دیگر

Dr. Gamal ELGHAZALY is a Research scientist at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), affiliated with the Ubiquitous and Intelligent Systems department. His work focuses on autonomous driving technologies, V2X communication systems, robotics, and control systems. Key research areas include 5G-enabled teleoperated driving, high-definition map construction, and 3D perception for autonomous vehicles. He has developed platforms like RoboCar and contributed to frameworks like FastCycle for modular automated systems. Research interests span robotics kinematics (planar parallel manipulators), adaptive control methodologies (sliding mode control, fuzzy logic), and hybrid systems (cable-driven robots). His publications emphasize real-time motion planning, sensor fusion, and safety-critical systems. Recent works (2023-2025) highlight advancements in 4D perception, cloud-assisted 3D reconstruction, and V2X-enabled collaborative systems. Publications from 2017-2018 reflect early contributions on parallel manipulator modeling and control, while recent efforts focus on integrating cutting-edge technologies like 5G and edge computing into autonomous systems. His work bridges theoretical robotics with practical implementations, addressing challenges in both dynamic environments and industrial applications.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۹ مورد دیگر

Carlo Masone is a Fixed-term Researcher at the Department of Control and Computer Science (DAUIN), Politecnico di Torino, affiliated with the College of Electronic, Telecommunications, and Physics Engineering. He is also an invited member of the College of Management and Production Engineering and the College of Mathematical Engineering, reflecting his interdisciplinary contributions. His research focuses on artificial intelligence, machine learning, computer vision, and robotics, with significant work in visual place recognition, federated learning, and geospatial AI. His research interests span Artificial Intelligence , Machine Learning , Computer Vision , Robotics , Visual Place Recognition , Federated Learning , Open-Set Segmentation , and Geospatial AI . He has developed methods for uncertainty quantification in ML models for autonomous vehicles and contributed to digital heritage through the MAPP project. The recent publications highlight a strong trend in visual place recognition (e.g., EigenPlaces, MeshVPR), geolocalization of astronaut photography (Earthloc, EarthMatch), and robust segmentation (Mask2Anomaly). There is a clear emphasis on leveraging pre-trained features, federated learning for privacy-preserving recognition, and topological methods in vision. His work bridges robotics, AI, and real-world applications in autonomous systems and cultural heritage. Scientific Awards: Outstanding Reviewer at CVPR (2022, 2023, 2024) IROS JTCF Novel Technology Paper Award (2016) Best Paper Award Finalist at IEEE ICIA (2016) ELLIS Fellow (2024–) He advises PhD students in Artificial Intelligence and Computer and Systems Engineering and leads commercial research projects such as Quantifying Uncertainties in ML Models for Driver-Assisted and Autonomous Vehicles and MAPP - Phygital and Participatory Alpine Museums . He has previously collaborated with the Max Planck Institute for Biological Cybernetics (2014–2017). He teaches courses including Machine Learning for Mathematical Engineering , Robot Learning , and GeoAI , and contributes to programming and data science curricula. He is also a co-inventor on a patent for automated neural network design.

Francois Chaumetteمشاهده پروفایل

استاد پژوهشی

• Robotics
• Computer Vision
• Visual Servoing
• +۱۷ مورد دیگر

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.