جست‌وجوی استاد و پژوهشگر

• Social Cognition
• Facial Emotion Recognition
• Mental Health Interventions
• +۲ مورد دیگر

Dr. Barbara Montagne is a Lecturer in the Faculty of Social and Behavioural Sciences at Utrecht University , affiliated with the Experimental Psychology department. Her work bridges psychology and computer science, focusing on facial emotion recognition, social cognition, and digital mental health interventions. Her research spans clinical populations (stroke survivors, OCD, psychosis, Korsakoff syndrome) and tech-driven applications (LLMs in mHealth, gamified systems). Recent studies examine LLM-generated treatment goals, social touch deficits, and crisis dynamics modeling. She collaborates with institutions like the Helmholtz Institute and ACM conferences. Doctoral thesis on facial expressions in psychiatric/neurological disorders (2005) Key areas: emotion perception, mental health technology, social cognition Her 2024-2025 work highlights mHealth gamification, personalized psychiatry, and trauma impacts on borderline disorder. Despite no listed awards, her 29+ peer-reviewed outputs and Mendeley readers indicate significant academic impact.

Merel Scholmanمشاهده پروفایل

استادیار

• Discourse Analysis
• Psycholinguistics
• Computational Linguistics
• +۳ مورد دیگر

Dr. Merel Scholman is an Assistant Professor at Utrecht University within the Department of Languages, Literature and Communication and affiliated with the Institute for Language Sciences . Her research focuses on how people use language to create meaning through discourse relations , investigating cognitive processing of coherence markers in written, spoken, and visual communication. PhD in Language Science and Technology from Saarland University (summa cum laude, 2019) Research Master in Linguistics from Utrecht University (cum laude, 2015) Visiting researcher at Lancaster University and University of Edinburgh Her work combines theoretical psycholinguistics with computational modeling , using quantitative empirical methods like corpus analysis and crowdsourcing experiments. Recent research examines cross-modal discourse signals across Nigerian Pidgin , English , and European languages , while methodological contributions explore annotation reliability and experimental design. Publications demonstrate expertise in discourse markers , coherence relations , and low-resource NLP , with applications to gesture synthesis , spoken language analysis, and educational tools . She received the Veni grant for her project on natural discourse structure signals across modalities. As an educator, she contributes to the Communication and Information Sciences (BA) and Linguistics (RMA) programs, teaching courses like Writing Style as a Choice . Her methodological innovations in crowdsourcing and annotation frameworks have shaped discourse analysis practices in computational linguistics.

• Model-Based Design Methods
• Design Automation
• Optimization
• +۵ مورد دیگر

Marc Geilen is an Associate Professor at the Electronic Systems group of Eindhoven University of Technology (TU/e) . He leads the Model-Based Design Lab within the CompSOC Lab and High Tech Systems Center .

Andrew Nelsonمشاهده پروفایل

استادیار

• Embedded Systems
• Real-Time Control
• Multi-Sensor Fusion
• +۴ مورد دیگر

Andrew Nelson is a part-time Assistant Professor at the Electronic Systems department, College of Engineering , Eindhoven University of Technology . He also serves as a founder and R&D lead at Verintec Solutions B.V. . Research Focus : Predictable and composable embedded systems, real-time robotics, multi-sensor fusion for industrial positioning, multi-core processor optimization. Key Contributions : Development of the CompSOC platform, CompROS architecture for ROS2, and novel multi-rate control strategies. Recent Article Trends : His work emphasizes predictable execution on multi-core platforms, sensor fusion techniques (linear encoders + vision systems), and real-time robotics. Articles span 2015–2025, highlighting collaborations with institutions like TU/e and ECSEL JU grant projects IMOCO4.E (2021–2023) and COMP4DRONES (2021).

Mohsen Kaboliمشاهده پروفایل

استادیار

• Embodied Robotics
• Tactile Intelligence
• Machine Learning
• +۳ مورد دیگر

Mohsen Kaboli is an Assistant Professor (Part-time) at Eindhoven University of Technology (TU/e) in the Netherlands, affiliated with the Department of Electrical Engineering and the Electronic Systems group. Since 2018, he has served as head of the AI, Robotics & Cognitive Vehicle research lab at BMW Group’s Center of Invention in Munich, Germany. Previously, he held positions at Radboud University’s Institute for Brain and Cognition (2019-2022) and Technical University of Munich (TUM) as a postdoctoral research fellow. His research focuses on Embodied Robotics, Visuo-Tactile Interactive Perception, and Machine Learning, with applications in Robotic Grasping, Human-Robot Collaboration, and Neuromorphic Computing. He leads European-funded projects like PHASTRAC (Oscillatory Neural Networks for AI Edge Computing) and INTUITIVE (Tactile User Interfaces). Keywords: Tactile Intelligence, AI, Robotics Application Domains: Mobile Robotics, Medical Instrumentation, Neuroprosthetics His recent publications (e.g., ViTract, Shared Visuo-Tactile Perception) emphasize robust object pose estimation and shape reconstruction using Bayesian filtering and Graph Neural Networks. He has authored ~40 academic works and contributed to 20 patents. Scientific Awards : IEEE Senior Member (2018) Georges Giralt Ph.D. Award (Finalist) IEEE ICRA Outstanding Paper Award (Finalist, 2023) IEEE FLEPS Outstanding Student Award (Winner, 2022) IEEE ROSE Outstanding Paper Award (Winner, 2024) Mohsen Kaboli serves as Editor/Associate Editor for IEEE ICRA, IROS, R-AL, T-RO, and IJRR. His work bridges tactile perception, AI, and robotics, with impacts in wearables, medical devices, and autonomous systems.

• Embedded Systems
• Cyber-Physical Systems
• Performance Engineering
• +۳ مورد دیگر

Jeroen Voeten is a Full Professor in the Electronic Systems group of the Department of Electrical Engineering at Eindhoven University of Technology (TU/e). He also holds a position as a Research Fellow at the Embedded Systems Institute in Eindhoven and is a Senior Scientist and Scientific Advisor to TNO-ESI since 2017. Academic Background: MSc in Mathematics and Computing Science (1991, TU/e) PhD in Electrical Engineering (1997, TU/e) Voeten's research focuses on formal methodologies for hardware/software system specification, design, and implementation. His work spans computer architectures, embedded systems, performance modeling, and cyber-physical systems. He is currently leading the Carm 2G project with ASML to enhance model-based engineering environments for wafer scanner control systems. His recent publications emphasize advancements in global scheduling, fault-tolerant real-time systems, and hybrid performance modeling. These studies address critical areas like latency reduction, schedulability improvements, and data age analysis in multi-rate task chains. Scientific Awards: Best Paper Award, Forum on Specification and Design Languages (FDL 2005) Best Paper Award, Property-Preserving Synthesis for Unified Control and Data-Oriented Models (2005) Voeten has contributed to 87 conference reports, 13 academic reports, 11 book chapters, and 11 journal articles, reflecting his extensive involvement in both academic and industrial research. Labs and Collaborations: He is affiliated with the Model-Based Design Lab and the High Tech Systems Center at TU/e, collaborating with institutions like TNO-ESI and industry leaders such ASML. His work aligns with the UN Sustainable Development Goals (SDGs) through applications in embedded systems and high-tech manufacturing.

Esther van Kleefمشاهده پروفایل

استادیار

• Antimicrobial Resistance (AMR)
• Emerging Infectious Diseases
• Infection Prevention and Control
• +۳ مورد دیگر

Esther van Kleef is an Assistant Professor at the University Medical Centre Utrecht and a technical consultant for the World Health Organisation (WHO) on global surveillance of antimicrobial resistance (AMR). She is affiliated with the Oxford Nuffield Department of Medicine and focuses on interdisciplinary research to enhance public health responses to emerging infectious diseases through data science. Her research integrates mathematical modeling and surveillance data to analyze AMR transmission dynamics and evaluate infection prevention strategies . She works across high-income and low- to middle-income countries, with projects spanning Europe, Africa, and global health contexts. Recent publications highlight her expertise in AMR surveillance , outbreak analytics (including LLM applications), and behavioral interventions for antibiotic use reduction. She specializes in merging conventional and innovative data sources for policy-driven public health solutions.

• Artificial Intelligence
• Robotics
• Materials Science
• +۳ مورد دیگر

Dengpeng Huang is an Assistant Professor specializing in Artificial Intelligence and Robotics within the field of Elastomer Technology and Engineering . His work bridges computational modeling with advanced materials, focusing on applications in smart materials and mechanical systems. Research Interests: Development of AI-driven models for predicting elastomer properties Multiscale analysis of rubber composites Electromechanical coupling in dielectric elastomer actuators Meshfree methods for metal cutting and chip formation Ultra-precision polishing of optical surfaces Recent Trends: His 2024–2025 publications emphasize data-driven modeling of rubber's viscoelastic behavior, multiscale analysis of composites, and CNN-based approaches for material characterization. Earlier work (2014–2022) explores tool path optimization, beam modeling, and computational machining. Scientific Recognition: Holds an h-index of 5 according to Scopus citations, with recognition as an AI and robotics expert in the service industry. Advising & Collaboration: Collaborates with researchers like Anna Blume, Evgeny Karaseva, and Tim Bor on elastomer composites. Supervised at least one academic work, though specific students are not named in the provided data. Labs & Teams: Affiliated with simulation and robotics teams in the smart materials sector, likely within an advanced materials or mechanical engineering research group.

Yanqiu Huangمشاهده پروفایل

استادیار

• Internet of Things (IoT)
• Cyber-Physical Systems
• Embedded Systems
• +۶ مورد دیگر

Yanqiu Huang is an Assistant Professor in Pervasive Systems, focusing on interdisciplinary research in Internet of Things (IoT), cyber-physical systems, embedded systems, wireless communication, and optimization. Their work addresses resource-constrained networks, emphasizing energy efficiency and collaborative algorithms for IoT devices. Research Interests Design of energy-efficient algorithms for IoT networks Integration of wireless communication and control systems Edge AI and sensor technologies for intelligent transport Recent Publications Key contributions include advancements in Bluetooth Low Energy (BLE) discovery, DNN task allocation for edge computing, and cyclist behavior prediction via IMU data. Research spans environmental monitoring, industrial ventilation, and smart mobility solutions like connected bicycles. Scientific Awards Best Poster Award: DNN Task Allocation for Edge-Aided IoT (2023) Best Poster Award: Smart Connected Bikes (2023) Best Presentation Award (2025) Activities Active in organizing and participating in international conferences (PerVehicle 2024/2025), hosting academic visitors (Koojana Kuladinithi, Konrad Fuger), and delivering invited talks on privacy-preserving crowdsensing.

• Artificial Intelligence
• Systems Engineering
• Cyber-Physical Production Systems
• +۵ مورد دیگر

Dr. Saber Darmoul is an Associate Professor specializing in Systems Engineering and Multidisciplinary Design. His research bridges artificial intelligence with industrial applications, focusing on cyber-physical production systems, operational resilience, and smart transportation. He actively explores knowledge representation, reinforcement learning, and agent-based modeling to address complex system challenges. Key Research Interests: Operational resilience, AI in manufacturing, multi-agent systems, smart mobility Technical Expertise: Ontology modeling, simulation platforms, immune-inspired control architectures His recent publications (2025-2019) demonstrate a consistent focus on integrating artificial immune systems into control architectures for transportation and manufacturing. Notable trends include: Development of knowledge-based systems for dynamic reconfiguration Application of multi-criteria decision frameworks in production environments Advancing predictive maintenance strategies through distributed systems Exploring 6G system-of-systems engineering While no explicit awards or student advisement information appears in available records, his 15 most recent publications reflect sustained academic productivity and evolving focus from foundational control systems (2017-2019) to advanced applications in Industry 4.0 (2020-2025).

Sebastian Thiedeمشاهده پروفایل

استاد

• Sustainable Manufacturing
• Smart Industry
• Human-Centered Manufacturing
• +۸ مورد دیگر

Sebastian Thiede is a Full Professor specializing in Manufacturing Systems , with extensive research contributions to Smart Industry , Sustainable Manufacturing , and Human-Centered Production . His work bridges advanced technologies like Machine Learning , Simulation , and Artificial Intelligence with industrial applications, addressing critical challenges in Circular Economy , Energy Efficiency , and Factory Decarbonization . Research focuses on Battery Manufacturing , Edge Computing , and Real-Time Locating Systems (RTLS) . Key methodologies include Digital Twinning , Surrogate Modeling , and Data-Driven Process Optimization . Recent publications highlight trends in Autonomous Sensor Data Analysis (2025), Cyber-Physical Architectures for reconfigurable systems, and Circular Transition Methodologies for manufacturing. His work often integrates Human Factors with Smart Automation , emphasizing environmental and economic impacts.

Christoph Bruneمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Computer Vision
• +۷ مورد دیگر

Christoph Brune is a Full Professor at the University of Twente , affiliated with the Digital Society Institute and TechMed Centre . His research bridges Artificial Intelligence , Deep Learning , and Medical Imaging with applications in Robotics and Computational Fluid Dynamics . Keywords: Machine Learning , Network Analysis , Optimal Transport , Medical Image Segmentation Research Trends : Recent publications focus on physics-informed neural networks , equivariant learning for vascular modeling, and operator learning for PDE-constrained problems. His work emphasizes geometric deep learning , implicit neural representations , and robust AI for clinical settings. Scientific Awards : CMI-NEN seed-money award (2022) for medical imaging innovation Collaborative Networks : Active in graph neural networks , optimal transport , and Barron space theory . Key collaborations include Zenodo dataset contributions and ArXiv preprints with multidisciplinary teams in AI, medicine, and engineering.

Bojana Rosicمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Robotics
• +۱۲ مورد دیگر

Bojana Rosic is a Full Professor specializing in Applied Mechanics & Data Analysis. Her research spans Artificial Intelligence, Machine Learning, Robotics, and Uncertainty Quantification, with a focus on integrating computational methods into mechanical systems and materials science. Key Research Areas: Machine Learning, Uncertainty Quantification, Robotics, Soft and Compliant Mechanisms, Materials Simulation. Recent Work: Contributions to neural network-based constitutive modeling for anisotropic materials, real-time control systems for robotic manipulators, and uncertainty quantification techniques using Polynomial Chaos Expansion. Collaborations: Active in interdisciplinary research with applications in energy, sustainability, and biomedical engineering. Her work emphasizes practical implementations of AI in mechanical engineering, including autonomous systems and collaborative robots (cobots). While no specific awards or educational background are detailed here, her extensive research output (68 publications) highlights her leadership in computational methods and machine learning integration.

• Biomechatronics
• Biorobotics
• Exoskeletons
• +۵ مورد دیگر

A.Q.L. Keemink serves as an Assistant Professor in Biomechatronics and Biorobotics at the University of Twente, within the Faculty of Engineering Technology's Department of Biomechanical Engineering. He is a member of the Biomechatronics and Rehabilitation Technology (ET-BE-BRT) research group and the TechMed Centre. His academic credentials include an MSc (cum laude) in Mechatronics and a PhD in human power augmentation systems and interaction control. Research interests encompass optimization-based control for human-robot interaction, specifically exoskeletons for upper and lower limb support. His work integrates machine learning, optimal motion planning, model-predictive control, and neuromechanics imitation to address rehabilitation challenges for individuals with movement deficits. Key domains include biomechatronics, biorobotics, and rehabilitation engineering. Keemink collaborates within the Biomechatronics and Rehabilitation Technology group, contributing to the University of Twente's TechMed Centre for medical technology innovation.

Mahdi Nabipourمشاهده پروفایل

پژوهشگر

• Human locomotion
• Wearable robotics
• Exoskeleton design
• +۴ مورد دیگر

Mahdi Nabipour is a postdoctoral researcher at the Department of Biomechanical Engineering, University of Twente, Netherlands. He is affiliated with the Neuromuscular Robotics group (ET-BE-NR) under the Faculty of Engineering Technology and the TechMed Centre. B.S. and M.S. in Mechanical Engineering (2011 & 2014) from Shahid Chamran University of Ahvaz and Amirkabir University of Technology, Iran His research focuses on: Design of wearable robotic devices Predictive control strategies using real-time neuromuscular feedback and biomechanical models Development of human-in-the-loop control systems for lower-limb ankle exoskeletons