جست‌وجوی استاد و پژوهشگر

Sadettin Kapucuمشاهده پروفایل

استاد

• Mechanical Engineering
• Robotics
• Mechatronics
• +۱۱ مورد دیگر

Sadettin Kapucu is a Professor at the Department of Mechanical Engineering , Faculty of Engineering , Gaziantep University , Turkey. With over 30 years of academic experience, he specializes in robotics, mechatronics, TRIZ-based inventive problem-solving, and vibration control systems. His career spans roles from Research Assistant (1987-1990) to Professor (2006-present) at Gaziantep University, and he has served as Head of the Mechanics and Dynamics Division since 2016. His educational background includes a PhD (1994) and MS (1990) in Mechanical Engineering from Gaziantep University and METU, respectively. PhD: Gaziantep University (1994) MS: Middle East Technical University (1990) BS: Middle East Technical University (1987) Kapucu’s research focuses on robot dynamics , TRIZ methodology , flexible systems control , and mechatronic design . He has pioneered techniques like hybrid input shaping for vibration suppression and variable stiffness actuators for rehabilitation robotics. His work bridges theoretical innovation and practical applications in industrial, medical, and agricultural robotics. Scientific achievements include the 2019 2nd Best Paper Award at ICICT 'xx19 and the 2009 Elginkan Foundation Technology Award . He has supervised over 18 graduate theses and secured 13 research grants, including TÜBİTAK-funded projects on olive oil processing and telehandler design.

Michael Ryooمشاهده پروفایل

دانشیار

• Deep Learning
• Computer Vision
• Robotics
• +۳ مورد دیگر

Michael Ryoo serves as a SUNY Empire Innovation Associate Professor in the Department of Computer Science at Stony Brook University while concurrently working as a Research Scientist with Google Brain's "Robotics at Google" team. Previously, he held positions as an Assistant Professor at Indiana University Bloomington and a Staff Researcher at NASA's Jet Propulsion Laboratory. His academic background includes a Ph.D. from the University of Texas at Austin (2008) and a B.S. from Korea Advanced Institute of Science and Technology (KAIST) in 2004. Ryoo's research centers on deep learning and computer vision with specific focus on convolutional neural network (CNN) models for video semantic understanding. His work bridges visual perception and robotic action through applications in robot perception, robot learning, and human-robot interaction. Key innovations involve developing efficient architectures for processing multimodal data and translating visual understanding into robotic control systems. Analysis of his 15 most recent publications reveals strong emphasis on multimodal AI integration, particularly vision-language models applied to robotics. His 2025 work shows significant advancement in token-efficient video representation, motion-controllable diffusion models, and zero-shot learning frameworks specifically designed for robotic control systems. The research trajectory demonstrates consistent focus on making video understanding more accessible and applicable to real-world robotic scenarios. Scientific awards: No awards were mentioned in the provided source material. Regarding academic advising, the source text does not list any students or mentoring activities. Similarly, no grant funding information is provided, though his dual academic-industry role suggests substantial research support. His Google Brain affiliation likely involves industry-sponsored research initiatives. Ryoo maintains active laboratory affiliations through Stony Brook's AI Innovation Institute and Google's Robotics team. His prior work at NASA JPL indicates experience with space robotics systems, while his current Google role focuses on large-scale robot learning infrastructure. The LAM SIMULATOR project represents his current focus on advancing data generation techniques for training large action models.

Abolfazl Mohebbiمشاهده پروفایل

دانشیار

• Robotics
• Control systems
• Applied Artificial Intelligence
• +۱۰ مورد دیگر

Abolfazl Mohebbi is an Associate Professor in the Department of Mechanical Engineering at Polytechnique Montréal. He directs the Polytechnique Laboratory for Assistive and Rehabilitation Technologies (POLAR) and holds the TransMedTech Research Chair in Assistive and Rehabilitation Technologies. His academic appointments also include Adjunct Professor at McGill University's Department of Biomedical Engineering and membership in numerous research networks including REPAR, FRQNT INTER cluster, Pediatric Rehabilitation Technology Park, and several biomedical engineering institutes. Professor Mohebbi's research focuses on robotics, control systems, and applied artificial intelligence with applications in biomedical engineering. His laboratory develops innovative robotic and biomechatronic technologies to help humans relearn, restore, or enhance their neuromotor performance. Specific research areas include human balance control modeling, joint neuromechanics, deep learning for medical diagnosis, sensory restoration in prosthetic users, custom exoskeleton design, and robotic rehabilitation systems. His recent publications (2022-2025) show a strong focus on rehabilitation robotics, with significant contributions to exoskeleton control, prosthetic feedback systems, neuromuscular modeling, and AI applications in medical diagnostics. The research demonstrates interdisciplinary collaboration across engineering, neuroscience, and clinical rehabilitation. Professor Mohebbi has received research funding from various organizations including NSERC, as evidenced by multiple grants awarded to Polytechnique Montréal researchers. His work demonstrates strong connections between academic research and clinical applications in rehabilitation engineering. He teaches courses in dynamic systems analysis, mechatronics, and dynamic measurement at Polytechnique Montréal and has supervised five graduate students to completion (one PhD and four Master's students) with research topics directly aligned with his laboratory's focus areas.

• Robotics
• Control Systems
• Machine Learning
• +۷ مورد دیگر

Matteo Saveriano is an Associate Professor at the University of Trento , affiliated with both the Department of Industrial Engineering and the Department of Information Engineering and Computer Science . His work focuses on Robotics , Control Systems , and Machine Learning , with applications in robotic manipulation, locomotion, and human-robot interaction. Email: matteo.saveriano@unitn.it Research interests include antifragile control systems, dynamic movement primitives, reinforcement learning, biomechanical characterisation, and motion planning on discrete manifolds. His teaching covers Automatic Control and Robotics , with a hybrid theoretical-practical approach using Python simulations. Recent publications explore topics such as neuro-symbolic robotics, radiation effects on embedded GPUs, surface defect identification with Bayesian filtering, and reactive navigation using control barrier functions. These works highlight interdisciplinary trends at the intersection of robotics , machine learning , and control theory .

Quoc Chi Nguyenمشاهده پروفایل

استاد

• Robotics
• Crane Control
• Vibration Control
• +۶ مورد دیگر

Professor Quoc Chi Nguyen serves as Vice Dean of the Faculty of Mechanical Engineering at Ho Chi Minh City University of Technology, Vietnam. He also holds the position of Head of the Department of Mechatronics since 2018. With a strong academic background including a Ph.D. from Pusan National University, Korea, and a Marie Curie FP7 postdoctoral fellowship at Tel Aviv University, Professor Nguyen has established himself as a leading researcher in control engineering and robotics. Professor Nguyen's educational journey began with a B.S. in Mechanical Engineering from Ho Chi Minh City University of Technology in 2002, followed by an M.S. in Cybernetics from the same institution in 2006. He completed his Ph.D. in Mechanical Engineering at Pusan National University, Korea, in 2012, and then pursued postdoctoral research at Tel Aviv University from 2013-2014. His research expertise spans Robotics , Crane Control , Vibration Control , Nonlinear Analysis , Dynamic Analysis , and Advanced Control Theory . Professor Nguyen's work focuses on developing innovative control algorithms for flexible structures, industrial automation systems, and mechatronic applications. His recent publications demonstrate a strong emphasis on practical industrial applications of control theory, including robotics integration, computer vision systems, and energy-efficient pneumatic systems. With 58 publications that have accumulated 32,041 reads and 782 citations, Professor Nguyen has established a significant research impact. His publication trend shows consistent productivity with recent work extending to projected 2025 publications, indicating an active and ongoing research program. The breadth of his work spans from fundamental control theory to practical industrial applications across multiple sectors including manufacturing, agriculture, and logistics. Marie Curie FP7 Postdoctoral Fellowship Professor Nguyen currently leads research activities through his lab at Ho Chi Minh City University of Technology. His leadership roles as Vice Dean and Department Head provide substantial resources and opportunities for research collaboration. With numerous co-authors and international connections, particularly stemming from his time at Tel Aviv University, he maintains an active global research network that benefits his students and colleagues.