جست‌وجوی استاد و پژوهشگر

Jiajun Xuمشاهده پروفایل

پژوهشگر

• Agricultural Engineering
• Robotics
• Machine Vision
• +۴ مورد دیگر

Jiajun Xu is a Research Associate in the Department of Biosystems and Agricultural Engineering (BAE) at Michigan State University's College of Engineering. His work focuses on advancing agricultural automation through machine vision systems, robotics, and path planning algorithms. Key areas of expertise include automated crop sorting, weed detection systems, and the development of cable-driven parallel robots for precision agriculture. His research integrates mechanical engineering principles with cutting-edge computer vision technologies, aiming to enhance efficiency in agricultural post-harvest processes and autonomous farming operations. Notable contributions include the OpenWeedGUI platform for weed imaging and the design of LiDAR-based systems for real-time crop quality assessment. Publications highlight trends in sensor integration, path optimization for mobile robots, and cross-season weed detection adaptations. Collaborative projects emphasize practical applications in agricultural automation, with a focus on open-source tools and industry-relevant solutions. Awards and grants are not explicitly mentioned in available texts, though his work indicates strong engagement with both academic and applied research in biosystems engineering.

Alexander Verlمشاهده پروفایل

استاد

• Industrial Robotics
• Control Engineering
• Mechatronics
• +۵ مورد دیگر

Prof. Dr.-Ing. Alexander Verl is a leading academic at the University of Stuttgart , serving as Principal Investigator at the Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) . His work bridges control engineering , industrial robotics , and digital twin technologies to enhance precision in manufacturing systems. Research Interests : Improving positioning accuracy of industrial robots through transmission error modeling and compliance compensation. Developing adaptive preload control mechanisms for cable-driven parallel robots and rack-and-pinion systems. Advancing IT/OT convergence via Time-Sensitive Networking (TSN) and cloud-edge integration. Creating digital twin platforms for real-time simulation and quality monitoring in CNC machining. Exploring deep learning applications for perception of deformable linear objects in automation. Recent Work Trends show expertise in: smart manufacturing , Industry 4.0 , and data-driven control systems . Publications emphasize practical validation through industrial testbeds (e.g., KUKA KR210–2 robotics, CNC machine simulations) and theoretical contributions to elastokinematic models and nonlinear dynamics . Advising & Grants : Collaborates extensively with researchers like Armin Lechler and Michael Neubauer. Projects funded through academic-industry partnerships in automotive production, precision engineering, and Gaia-X-based data ecosystems.

Michael Abbottمشاهده پروفایل

استادیار

• Mechatronics
• Haptics
• Biomechanics
• +۳ مورد دیگر

Michael Abbott is an Assistant Professor in the Department of Mechanical Engineering at Santa Clara University's School of Engineering. His work focuses on developing assistive technologies through interdisciplinary research spanning mechatronics, haptics, and biomechanics. Education: Ph.D. (2024), M.S. (2020) in Mechanical Engineering from UC Berkeley; B.S. (2016) in Mechanical Engineering from UC Santa Barbara Research interests center on creating innovative solutions for healthcare and robotics, including: Integration of continuously variable transmissions in body-powered prostheses Haptic characterization of cable-driven upper-limb assistance devices Biomechanical analysis for human-centered robotic design His recent publications demonstrate expertise in transmission systems (2023-2022), haptic feedback mechanisms (2021), and wearable assistive devices (2020). Prior industry experience includes automation engineering roles at Angstrom Designs and Northrop Grumman. Outside academia, he engages in music production, Brazilian jiu-jitsu, and Bay Area outdoor exploration.

Arunabha Majumderمشاهده پروفایل

پژوهشگر

• Mechatronics
• Robotics
• Soft Robotics
• +۶ مورد دیگر

Arunabha Majumder is a PhD Fellow at the Department of Materials and Production, under The Faculty of Engineering and Science at Aalborg University, Denmark. His research focuses on mechatronics, robotics, and smart materials, with a particular emphasis on soft robotics, exoskeletons, and neural network-based control systems. Education: M.Tech in Mechatronics (2022) from Academy of Scientific and Innovative Research, India; B.E in Mechanical Engineering (2019) from Siddaganga Institute of Technology, India. External Position: Researcher at CSIR - Central Mechanical Engineering Research Institute (2021-2022). His work spans wearable device technologies, soft robots, bio-inspired actuators, and computational mechanics. Key technical areas include: Pneumatic Artificial Muscles Position Control Algorithms Variable Stiffness Actuators Shape Memory Alloys Gain Scheduling in Control Systems Parallel Robot Design His publications between 2019-2024 demonstrate interdisciplinary research at the intersection of robotics, materials science, and neural networks. Collaborations include researchers in robotics and mechanics across India and Denmark.

Özkan Bebekمشاهده پروفایل

دانشیار

• Medical Robotics
• Mechatronics
• Biomedical Measurement
• +۴ مورد دیگر

Özkan Bebek is an Associate Professor in the Faculty of Engineering at Ozyegin University, specializing in Medical Robotics and Mechatronics. He holds a Ph.D. in Systems and Control Engineering from Case Western Reserve University (2008), an M.S. in Mechatronics from Sabanci University (2003), and a B.S. in Mechanical Engineering from Middle East Technical University (2001). Ph.D.: Systems and Control Engineering, Case Western Reserve University (2008) M.S.: Mechatronics, Sabanci University (2003) B.S.: Mechanical Engineering, Middle East Technical University (2001) His research focuses on medical robotics , mechatronics , biomedical measurement , and haptic systems . Recent publications highlight advancements in exoskeleton design, 3D printing optimization, and soft-landing actuation systems. He has directed the Ozyegin University Robotics Laboratory , contributing to innovations in robotic-assisted surgery and wearable technologies. Notable scientific achievements include the Outstanding Graduate Student Research Poster at Research ShowCASE 2005. He has mentored students in projects spanning robotic biopsies, exoskeleton locomotion control, and intelligent actuator systems.

• Robotics
• Aerospace Engineering
• Mechanics and Mechatronics
• +۳ مورد دیگر

Professor Tomoyuki Miyashita is a distinguished faculty member at Waseda University's Faculty of Science and Engineering, specializing in Mechanical Engineering. With a career spanning over three decades, he has established himself as a leading researcher in robotics, aerospace engineering, and mechanics and mechatronics. His academic journey began at Waseda University where he earned both his undergraduate and graduate degrees in Mechanical Engineering before embarking on his professional career. Dr. Miyashita's research interests span a remarkably diverse range of topics including robotics, medical systems, aerospace engineering, and design engineering. His work bridges theoretical foundations with practical applications, particularly evident in his numerous publications on surgical robotics, space structures, and intelligent mechanical systems. His research group has produced significant contributions in areas such as lunar rover mobility, medical robotics for laparoscopic surgery, and deployable space structures. His publication record demonstrates consistent high-impact research across multiple disciplines. Analyzing his recent works reveals a strong focus on robotic systems with applications spanning medical procedures, space exploration, and industrial automation. His research shows particular strength in optimization techniques applied to mechanical systems, haptic interfaces, and deployable structures. The interdisciplinary nature of his work is evident in collaborations across engineering, medical, and aerospace domains. IEEE ISATP2003 Best Paper Award (2003.07) JSCES Encouragement (2003.05) Professor Miyashita has mentored numerous students who have become co-authors on his publications, indicating an active research group with strong student involvement. His work has attracted significant research funding, particularly in the areas of space structures and medical robotics, though specific grant details are not provided in the current documentation. His laboratory appears to maintain strong connections with industry partners and international research institutions, facilitating collaborative projects across multiple domains of engineering.

Hamid D. Taghiradمشاهده پروفایل

استاد

• Robust Control
• Nonlinear Control
• Medical Robotics
• +۵ مورد دیگر

Hamid D. Taghirad is Professor and Director of the Advanced Robotics and Automated Systems (ARAS) laboratory in the Department of Systems and Control, Faculty of Electrical Engineering at K. N. Toosi University of Technology, Tehran, Iran. He concurrently serves as Visiting Professor at the University of Alberta. A senior IEEE member, he holds editorial roles in four robotics journals and has published 6 books and over 300 papers. Education: Ph.D. Electrical Engineering (McGill University, 1997) M.Sc. Mechanical Engineering - Mechatronics (McGill University, 1993) B.Sc. Mechanical Engineering (Sharif University of Technology, 1989) Research interests span: Robust/Nonlinear Control Systems Medical Robotics & Surgical Training Cable-Driven & Parallel Manipulators AI/VR for Medical Applications Industrial Automation & Inspection Robotics His ARAS lab developed the Kamalolmol® cable robot for artistic applications and commercial inspection tools. He received numerous awards including: Best Teaching Professor (2010, 2013, 2016) Research Award for Published Books (2014) PBEEE Quebec Visiting Scientist Award (2005) Prestigious McGill fellowships (Top 5% university-wide) He secured 15+ industrial grants (~$2M total) for projects like: Haptic eye surgery trainer ($255K) Pipeline inspection robots ($310K) Driverless car perception ($175K) Automatic casting systems ($320K) and has supervised ~200 graduate theses. He directs the ARAS lab focusing on cable robots, medical robotics, and industrial automation, with projects ranging from driverless vehicles to surgical training systems.

• Medical Robotics
• Surgical Robotics
• Continuum Robots
• +۴ مورد دیگر

Dr. Leo Wu is a Research Fellow at Queensland University of Technology (QUT), affiliated with the Faculty of Engineering, School of Mechanical, Medical and Process Engineering. His research focuses on medical robotics, particularly in the development of surgical robotic systems for minimally invasive procedures. Dr. Wu's research interests span Medical Robotics , Surgical Robotics , Continuum Robots , Image-Guided Surgery , and Robot Kinematics . His work bridges engineering principles with clinical applications, developing innovative robotic solutions for complex surgical procedures. He has made significant contributions to the field of flexible and continuum robotics, with applications in nasopharyngeal biopsy, knee arthroscopy, and other minimally invasive procedures. Analysis of Dr. Wu's publications reveals a strong focus on practical robotic solutions for surgical applications. His work consistently addresses challenges in medical robotics including dexterity, precision, and integration with imaging technologies. The research spans fundamental robotics theory (kinematics, calibration) to applied medical devices, demonstrating both theoretical depth and clinical relevance. Dr. Wu has collaborated extensively with researchers at QUT and internationally, particularly with Professor Hongliang Ren, Professor Jonathan Roberts, and Professor Ross Crawford. His collaborative approach has resulted in numerous high-impact publications in IEEE transactions and other leading robotics and medical engineering journals. His laboratory work focuses on developing novel robotic mechanisms, particularly continuum and concentric tube robots, for surgical applications. These systems are designed to navigate complex anatomical pathways while providing surgeons with enhanced precision and control during minimally invasive procedures.

Guillaume Mercereمشاهده پروفایل

استاد

• System Identification
• Model Learning
• Automatic Control
• +۶ مورد دیگر

Guillaume Mercere is a Full Professor in Automatic Control and Systems at ENSIP (Ecole Nationale Supérieure d'Ingénieurs de Poitiers), University of Poitiers. He maintains dual affiliations with Laboratory LIAS at both ENSIP in Poitiers and ISAE-ENSMA in Chasseneuil, conducting research in system identification and control theory. Professor Mercere teaches automatic control and signal processing at the Master's level, with additional expertise in numerical optimization, machine learning, and time series analysis. His teaching materials are available upon request, reflecting his commitment to educational transparency. Research Focus: Model learning, system identification, estimation theory, state space modeling, gray box modeling, linear parameter varying (LPV) systems, linear fractional representation (LFR), and subspace-based methods Application Areas: Electrical engineering, aeronautics, heat transfer, flexible/cable-driven manipulators, vehicle tire/road interactions, and image processing Analysis of his recent publications reveals a strong emphasis on recursive estimation methods (particularly total least squares), theoretical developments in LPV system representations, predictive control methodologies, and noise covariance estimation for Kalman filtering. His work bridges theoretical advances in identification methodologies with practical applications across multiple engineering domains, demonstrating both depth and breadth in his research program. Professor Mercere leads the Automatic Control Team at Laboratory LIAS, where he collaborates with researchers on theoretical and applied projects. His research group focuses on developing identification methodologies with practical implementation in real-world engineering systems, maintaining an active publication record through 2025 that demonstrates ongoing contributions to the field of system identification and control engineering.