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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

Iris Walraven serves as Associate Professor of Cancer Epidemiology at Radboud University Medical Center, Radboud University, and holds a 2025-2026 L’Oréal-UNESCO For Women in Science Fellowship for her CLEAR-study project developing explainable AI to enhance shared decision-making for lung cancer patients with low health literacy. Her research integrates cancer epidemiology with human-centered AI design, focusing on translating complex medical information into accessible patient communication. She emphasizes co-creation with patients to develop relatable explanations for AI-driven treatment recommendations, ensuring patient perspectives shape decision-support tools while addressing health literacy barriers in oncology care. Publication analysis reveals consistent focus on patient-reported outcomes across cancer types, with methodological innovation in symptom monitoring tools (Delphi procedures, PRO-CTCAE adaptation) and clinical validation through trials like SYMPRO-Lung. Her work bridges macro-level healthcare systems, meso-level clinical implementation, and micro-level patient experiences in oncology. Scientific recognition includes: L’Oréal-UNESCO For Women in Science Fellowship The text specifies no student advisees or additional grants beyond the UNESCO fellowship. No laboratory or research team structures are described, though her collaborative publications indicate multi-institutional oncology research networks.

• Cancer Epidemiology
• Artificial Intelligence in Healthcare
• Patient Decision-Making
• +۲ مورد دیگر