جستجوی استاد راهنمای دانشگاهی

Pengcheng Liu is an Associate Professor in the Department of Computer Science at the University of York, holding this position since January 2020. He maintains active memberships in IEEE, IEEE Robotics and Automation Society (RAS), IEEE Control Systems Society (CSS), and the International Federation of Automatic Control (IFAC), while serving on the IEEE Technical Committee for Bio Robotics, Soft Robotics, Robot Learning, and Safety, Security and Rescue Robotics. His research spans robotics, machine learning, automatic control, and optimization, with specialization in humanoid robotics, rehabilitation systems, agricultural applications, and human-computer interaction. Key focus areas include developing lightweight neural networks for embedded agricultural systems, bionic-companionship frameworks for service robots, EMG-controlled rehabilitation devices, and precise control of robotic manipulators using ROS/Gazebo. His work consistently bridges theoretical control systems with practical implementations in healthcare and precision agriculture. Analysis of his publication trends reveals strong emphasis on applying machine learning to real-world robotics challenges, particularly in resource-constrained environments (e.g., agricultural robotics with efficient neural networks) and human-centered applications (e.g., rehabilitation gloves and brain-computer interfaces). Recent work demonstrates increasing integration of computer vision with control systems for autonomous operation. His notable scientific awards include: Global Peer Review Awards from Web of Science (2019) Outstanding Contribution Awards from Elsevier (2017) Dr. Liu has secured and managed research funding through major programs including EPSRC, Newton Fund, Innovate UK, Horizon 2020, Erasmus Mundus, FP7-PEOPLE, and NSFC. He serves as a regular reviewer for EPSRC, NIHR, and NSFC grant panels while reviewing for over 30 flagship journals and conferences in robotics, AI, and control systems. His editorial roles include Associate Editor for IEEE Access and PeerJ Computer Science, where he has edited 17 publications. Though specific lab affiliations aren't detailed, his research in agricultural robotics, rehabilitation systems, and humanoid platforms suggests active collaboration with York's robotics and AI research groups, particularly in developing practical implementations of control algorithms and machine learning models for real-world deployment.

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

Thomas Wilschut, MSc is an active researcher specializing in cognitive psychology with a focus on memory retrieval, speech recognition, and adaptive learning systems. His work bridges theoretical cognitive science with practical educational applications, particularly for learners with dyslexia. His research interests center around Retrieval Practice , Adaptive Learning , and Speech-Based Educational Technology . Wilschut investigates how cognitive principles can be applied to develop more effective learning systems, with particular attention to how speech recognition technology can support vocabulary acquisition and memory consolidation. His publications demonstrate a strong trend toward developing model-based adaptive learning systems that personalize educational experiences based on individual cognitive profiles. Much of his recent work focuses on the intersection of speech motor control and memory processes, exploring how speech production affects learning outcomes. Wilschut frequently collaborates with researchers including van Rijn, Sense, and others on projects related to cognitive modeling of learning processes. His work contributes to Sustainable Development Goals related to quality education through innovative learning technologies.

• Cognitive Psychology
• Memory Retrieval
• Speech Recognition
• +۵ مورد دیگر