جست‌وجوی استاد و پژوهشگر

• Cognitive Aging
• Visual Attention
• Visual Short-term Memory
• +۴ مورد دیگر

Dr. Iris M. Wiegand serves as Assistant Professor in Neuropsychology and Rehabilitation Psychology at Radboud University and holds dual Associate Principal Investigator roles at the Donders Centre for Cognition and Donders Institute for Brain, Cognition and Behaviour. Her research examines cognitive aging through the lens of visual attention and memory systems, utilizing advanced neuroimaging techniques to investigate lifelong cognitive plasticity. Her work centers on how visual short- and long-term memory processes evolve across the lifespan, with particular focus on preserved cognitive functions in older adults. Key investigations include hybrid visual-memory search resilience, electrophysiological correlates of memory systems, and neural network plasticity in aging populations. This research bridges fundamental cognitive neuroscience with clinical rehabilitation applications. Publication trends (2017-2025) reveal consistent methodological rigor using EEG and neuroimaging to dissect visual memory mechanisms in aging. Recent work demonstrates remarkable preservation of hybrid search capabilities in older adults while identifying nuanced neural correlates that vary with cognitive development history, challenging simplistic decline models of aging cognition. Major recognitions include: Open Competition XS Grant, NWO (2023 & 2025) Startersbeurs (NWO Starting Grant for Assistant Professors) (2023) EU Horizon 2020 Marie Skłodowska-Curie Individual Global Fellowship (2017) MOBILEX Mobility Postdoc Grant (Danish Research Council/FP7 EU) (2014) Her grant portfolio demonstrates exceptional success in securing competitive funding from Dutch and European sources, enabling sophisticated investigations into cognitive aging mechanisms. While specific advisees aren't listed, her teaching responsibilities for Brain & Cognition courses indicate active graduate student supervision within clinical neuropsychology programs. Dr. Wiegand operates within the Cognitive Aging research group at the Donders Centre for Cognition, collaborating across disciplines to advance understanding of brain-behavior relationships throughout the human lifespan through integrated experimental and clinical approaches.

• Urban Analytics
• Smart Charging Systems
• Electric Vehicle Infrastructure
• +۵ مورد دیگر

Dr. Pieter Bons serves as a Senior Lecturer at the Faculty of Technology, Hogeschool van Amsterdam, where he teaches Applied Mathematics and Data Science. His academic work spans urban analytics, smart charging systems, and geospatial modeling, with significant contributions to electric vehicle infrastructure and climate adaptation research. His research focuses on applying data science to urban challenges, particularly in smart charging for electric vehicles and neighborhood typology classification . Bons specializes in extracting actionable insights from complex urban datasets while addressing critical issues like data bias, quality, and privacy. His work bridges theoretical data science with practical urban applications, notably through projects like the Rijkswaterstaat charging infrastructure study and nationwide neighborhood typology mapping. Recent publications reveal a clear trajectory from fundamental physics (2010-2017) to applied urban analytics (2020-present), with current work emphasizing energy grid optimization through smart charging AI-driven climate adaptation tools geospatial analysis for urban planning His fingerprint analysis highlights strong connections to Smart Charging (95%), Public Charging Stations (36%), and Electric Vehicles (54%). Award highlights: HvA onderzoeksprijs 2021 for collaborative urban research Nominatie KennisDC Parel 2023 for innovation in zero-emission infrastructure Bons actively enhances data literacy across the faculty through educational initiatives like Data Studio, integrating students into real-world research cases. His activities include stakeholder presentations for Rijkswaterstaat, knowledge clips on neighborhood typologies, and academic talks on walkability and zero-emission corridors. He contributes to datasets like the Wijktypologie Buurtniveau 2023, supporting national climate adaptation efforts. His work occurs at the intersection of urban planning, energy systems, and AI, with current projects focusing on balancing urban energy grids through flexible EV charging and developing nationwide neighborhood classification systems for climate resilience.

• Pervasive Computing
• Sensor Systems
• Machine Learning
• +۷ مورد دیگر

Berend Jan van der Zwaag is an Assistant Professor at the University of Twente, affiliated with the Digital Society Institute and the Pervasive Systems group within the Faculty of Electrical Engineering, Mathematics and Computer Science. His interdisciplinary work bridges sensor technology, machine learning, and animal biomechanics. His research interests focus on pervasive computing, sensor systems, and machine learning applications, particularly in equine health. He investigates how inertial measurement units (IMUs) and AI models can be used for lameness detection, gait analysis, terrain classification, and kinetic parameter prediction in horses. His work emphasizes real-world deployment of smart, data-driven systems in veterinary and agricultural contexts. The recent publications reveal a strong trend in applying deep learning and recurrent neural networks to time-series sensor data from horses. His research integrates wearable technology with AI to enable precision monitoring of animal locomotion, contributing to both veterinary science and pervasive computing. The interdisciplinary nature of his work spans engineering, computer science, and life sciences. Berend Jan van der Zwaag actively contributes to scientific discourse through expert media commentary, such as on the role of sensors in data-driven maintenance. His research has garnered citations and downloads, indicating growing academic and practical relevance. He supervises students, including J. I. M. Parmentier, whose work on equine IMU data forms a significant part of recent publications. While no formal grants are listed, his output suggests involvement in collaborative, applied research projects. His work is supported by open-access dissemination and digital research metrics platforms like Pure and PlumX. Berend Jan van der Zwaag is part of a dynamic research network at the University of Twente, contributing to the Pervasive Systems lab, which focuses on intelligent, context-aware sensor systems for societal challenges. His work exemplifies the convergence of digital technology with real-world applications in health and sustainability.