جست‌وجوی استاد و پژوهشگر

• Systems Engineering
• Nuclear Fusion
• Complexity Management
• +۴ مورد دیگر

Torben Beernaert is a researcher at DIFFER (Dutch Institute for Fundamental Energy Research) and completed his PhD at Eindhoven University of Technology (TU/e). His work focuses on applying model-based systems engineering techniques, particularly Dependency Structure Matrix (DSM) methods, to address complexity in nuclear fusion projects. His research bridges nuclear fusion technology, plasma physics, and control systems engineering, emphasizing multi-domain integration and technical risk management. He has contributed to advancements in fusion diagnostics, plasma control architecture, and designer productivity optimization. Scientific awards include the Best Paper on Ecological Vehicles (2015) . He defended his PhD thesis 'Discovering the potential of dependency structure modelling for fusion systems engineering' on August 7, 2024, at TU/e, with promoters Prof. Marco R. de Baar and Prof. L.F.P. Etman.

Jacques M.B. Terkenمشاهده پروفایل

دانشیار

• Automotive Human Factors
• Autonomous Vehicles
• Human-Technology Interaction
• +۳ مورد دیگر

Jacques M.B. Terken is an Associate Professor in the Department of Industrial Design at Eindhoven University of Technology, specializing in automotive human factors and human-technology interaction. He leads the iCave project, investigating communication between autonomous vehicles and road users. His research spans speech technology, user experience in autonomous vehicles, and design methodologies. Academic Background: Earned his PhD in Psycholinguistics from Leiden University (1985) after graduating from Utrecht University (1979). Held roles at the Max Planck Institute for Psycholinguistics (1985-1986) and the Institute for Perception Research (IPO, 1986-2002). Co-founded the User-Centered Engineering group, now part of TU Eindhoven's Industrial Design department. Research Interests: Focuses on enhancing safety and usability in autonomous vehicle systems through interdisciplinary approaches. Key areas include driver-vehicle interaction, pedestrian communication, and design processes for emerging transportation technologies. Awards: AHFE 2016 Best Paper Award AutomotiveUI '20 Honorable Mention Award CHI '20 Best Paper Award Best Demo Award (2017) Best Poster Award (2015) Advocacy & Grants: Supervises over 100 PhD projects in automotive human factors. Actively contributes to advancing automotive interaction design through collaborative research initiatives. Labs/Teams: Leads the iCave project, collaborating with multidisciplinary teams to address autonomous vehicle integration challenges.

Gert Pasmanمشاهده پروفایل

پژوهشگر

• Human-Centered Design
• Healthcare Design
• Human-Technology Interaction
• +۳ مورد دیگر

Dr. Gert Pasman is affiliated with the Faculty of Industrial Design Engineering at Delft University of Technology. He specializes in Human-Centered Design and Human Technology Relations, focusing on healthcare interventions, assistive technologies, and inclusive design. His research bridges design methodologies with healthcare challenges, particularly for neurological conditions like Parkinson's disease and dementia. Key research interests include co-design approaches for patient-centered solutions, smart object interaction, and innovation strategies for small businesses. He teaches courses such as Interactive Formgiving , emphasizing hands-on design processes. Recent publications highlight creative therapies for Parkinson's patients, assistive tools for dementia care, and automotive innovation in SMEs. His work integrates user-centric principles with technological advancements to address societal challenges. No scientific awards are explicitly listed, but his contributions span academic and applied design domains. He collaborates with interdisciplinary teams and is based in room 32.C-3-300 at TU Delft.

• Composite Materials
• Additive Manufacturing
• Finite Element Analysis
• +۳ مورد دیگر

Joris J.C. Remmers is an Associate Professor of Composite Materials at the Department of Mechanical Engineering, Eindhoven University of Technology (TU/e). He is also affiliated with the EAISI High Tech Systems and leads the Mechanics of Materials research group. His academic journey includes a MSc in Aerospace Engineering (TU Delft, 1998) and a PhD in Computational Mechanics (TU Delft, 2006). Remmers' research focuses on composite materials and additive manufacturing, particularly the relationship between manufacturing processes, microstructure, and mechanical properties. He employs advanced numerical techniques to study multi-physics phenomena across scales. Research Themes: Composite materials and fiber-reinforced systems 3D printing and additive manufacturing processes Numerical methods (e.g., finite element analysis, model order reduction) Micromechanical modeling of material behavior Grants and Projects: Project Manager for Innovation test bed for development and production of nanomaterials for lightweight embedded electronics (2019–2023) Awards: Emerging DMD Based Systems and Applications Best Paper Award (2025) Teaching: Leads courses on advanced manufacturing, computational mechanics, and data-driven approaches in engineering, including Advanced and Additive Manufacturing and AI-assisted innovation in portable plasma technology . Labs/Teams: Active in the Mechanics of Materials group, collaborating on multi-scale mechanics, damage modeling, and material failure analysis.

Daniel Strüberمشاهده پروفایل

دانشیار

• Model-Driven Engineering
• AI Engineering
• Software Quality Assurance
• +۱۲ مورد دیگر

Daniel Strüber is an Associate Professor in Software Engineering at the joint Interaction Design and Software Engineering Division of Chalmers University of Technology and the University of Gothenburg, Sweden. He is also affiliated with the Department of Software Science at Radboud University Nijmegen, Netherlands. His research focuses on model-driven engineering, AI engineering, and variability management to enhance software quality, security, and collaborative development across domains like robotics and web systems. Education : Diplom (M.Sc. equivalent) in Computer Science from Philipps University Marburg (2011, with distinction), Ph.D. (summa cum laude) from Philipps University Marburg (2016). His research bridges empirical, formal, and engineering approaches to address developer challenges in ML-enabled systems. Key trends in his work include model-driven methods for ML deployment, variability management in robotics, and empirical studies of tool usability. He has co-edited a Journal of Systems and Software special issue on software product lines. Scientific Awards : Best Reviewer Awards (SoSyM 2025, GPCE 2024), Transformation Tool Contest Awards (2017, 2020), Best Paper Awards (VAMOS 2019, ICMT 2016), and multiple conference nominations. As a supervisor, he guides current Ph.D. students like Vladislav Indykov and Weixing Zhang, while his former advisees include Shayan Ahmadian and Samuel Idowu. Grants include a VR Open Call Grant (2022-2024) for SEMLA and a DFG Individual Fellowship (2019) for EUphORia. His teaching spans courses on Software Engineering for AI Systems and Software Product Lines , often integrated with real-world projects via GiPHouse.

Mónica Isela Acuautla Menesesمشاهده پروفایل

دانشیار

• Piezoelectric materials
• Micro/Nano Electro Mechanical Systems (MEMS/NEMS)
• Flexible electronics
• +۵ مورد دیگر

Prof. Mónica Isela Acuautla Meneses is an Associate Professor at the University of Groningen's Faculty of Science and Engineering, affiliated with the Discrete Technology and Production Automation department. Her research focuses on piezoelectric materials, MEMS/NEMS, flexible electronics, and sensors. She holds a PhD in Micro and Nanoelectronics from Aix Marseille University, an MSc in Electrical Engineering from CINVESTAV, Mexico, and a BSc in Mechatronic Engineering from IPN, Mexico. She has received the TKI Top sector HTSM grant (2022) and has authored over 50 peer-reviewed publications. Research Interests Her multidisciplinary work integrates material science and engineering to develop sensors, actuators, and energy harvesters using piezoelectric materials such as ceramics, thin films, and polymers. Key areas include ferroelectric hafnium-based materials, flexible piezoelectric composites, and piezoelectric energy harvesting systems. Recent advancements include low-toxicity chemical deposition methods for ferroelectric thin films and deformable mirror concepts leveraging piezoelectric hysteresis. Awards & Grants - TKI Top sector HTSM grant (2022) - Recognized for innovations in piezoelectric energy harvesting and sensor technologies. Key Projects - Development of high-performance piezoelectric sensors for biomedical and aerospace applications. - Exploration of novel ferroelectric materials for next-generation electronic devices. - Collaboration with the Engineering and Technology Institute Groningen for advanced materials prototyping. Labs & Teams Affiliated with the Discrete Technology and Production Automation research group, focusing on micro/nano fabrication, MEMS, and smart materials systems.

Janet Huangمشاهده پروفایل

استادیار

• Human-AI Interaction
• Creative AI
• Design of AI Systems
• +۳ مورد دیگر

Janet Huang serves as Assistant Professor in the Industrial Design department at Eindhoven University of Technology (TU/e), where she contributes to the Future Everyday group. Her research pioneers human-AI co-learning frameworks that empower designers to harness AI as a creative material for solving complex real-world problems across diverse contexts. Academic Background: PhD in Computer Science, National Taiwan University (2018) MSc in Computer Science, National Taiwan University (2008) Research Focus: Dr. Huang designs novel toolkits bridging data sensemaking and decision-making support, with emphasis on creative AI applications and ethical human-AI collaboration . Her work spans healthcare data visualization, urban play systems, and memory augmentation tools, consistently exploring how AI can enhance human creativity while addressing societal implications. She employs participatory design methods to develop systems that balance technical innovation with user-centered values. Publication Trends: Recent articles (2023-2025) reveal three dominant trajectories: (1) generative AI for domain-specific problem-solving in nursing and biodesign, (2) playful urban exploration systems examining citizen-AI tensions, and (3) memory and decision-making support tools analyzing anthropomorphism effects. These works demonstrate her signature approach of embedding technical AI research within rich human contexts. Awards & Recognition: Ph.D. Thesis Honorable Mention, TAAI 2018 MOST Postdoctoral Scholarship (Taiwan) Mingler Scholarship 2023 Best Poster Honorable Mention, CSCW 2023 Academic Contributions: Dr. Huang teaches specialized courses including Creativity and Aesthetics of Data & AI and Digital Craftsmanship , while supervising 19 student projects. Her research receives support from competitive grants including the MOST scholarship, with applications spanning healthcare innovation and sustainable community development. She actively contributes to UN Sustainable Development Goals through human-centered AI solutions. Research Environment: As core member of TU/e's Future Everyday group, she collaborates with interdisciplinary teams spanning computer science, design, and domain experts. Her lab environment emphasizes iterative prototyping and real-world deployment, particularly in healthcare settings and urban contexts where AI systems interface with complex human practices.

Siria Xiyueyao Luoمشاهده پروفایل

استادیار

• Consumer Behavior
• Behavioral Decision Making
• Emotion-Cognition Interaction
• +۳ مورد دیگر

Siria Xiyueyao Luo is an Assistant Professor at the Faculty of Economics and Business, University of Groningen. Her research focuses on how hope and uncertainty influence consumer judgment and decision-making, particularly in financial contexts. She has published in top journals such as the Journal of Behavioral Decision Making and Emotion , exploring topics like investor behavior and hope prototypes. Luo teaches courses on marketing, international business, and consumer behavior at both undergraduate and graduate levels. Her academic contributions include analyzing the 'disposition effect' in investors and the psychological underpinnings of hope. She serves as an ad hoc reviewer for journals like Emotion and Journal of Behavioral Decision Making .

Robby van Deldenمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Gamification
• Interactive Play Design
• +۷ مورد دیگر

Robby van Delden is an Assistant Professor at the Human Media Interaction (HMI) group of the University of Twente , specializing in interactive play and gamification for health and sports contexts. His educational background includes MSc degrees in Human Media Interaction and Industrial Design Engineering (Emerging Technology Design track) , followed by a PhD on "(Steering) Interactive Play Behavior". His research integrates exergaming technology persuasive systems movement-based design social VR applications with a focus on measurable outcomes in rehabilitation, sports, and education. Recent publications examine sport data's impact on athlete motivation, movement design toolkits, and ethical considerations in gamification. Scientific awards include the Best poster award CVOI 2022 for collaborative research on patient mobilization. He actively participates in academic events like CHI ’24 MOCO 2024 and organizes national XR and Human-Computer Interaction workshops.

Kars Alfrinkمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Contestable AI
• Design Research
• +۳ مورد دیگر

Dr. Kars Alfrink is a postdoctoral researcher at Delft University of Technology's Faculty of Industrial Design Engineering, specializing in Human-Centred Artificial Intelligence. His research focuses on contestable AI systems, investigating how to design public artificial intelligence that remains subject to societal control and democratic oversight. With over 15 years of professional experience as an interaction design consultant, entrepreneur, and community organizer prior to entering academia, Alfrink brings practical expertise to his critical examination of AI systems. Alfrink's research interests center on creating more democratic public AI systems through the lens of contestability. His work combines extensive practical knowledge in digital product design with critical socio-political theory, examining how AI systems can be designed to allow citizens to challenge and influence both AI decisions and development processes. His research explores the intersection of AI infrastructure, design methodology, and democratic governance, with particular focus on creating systems where power dynamics are transparent and contestable. Best Paper Award at the 2023 CHI Conference on Human Factors in Computing Systems As an advisor and consultant at SORCEREE (2023-2028), Alfrink bridges academic research with practical implementation. His industry experience informs his academic work, creating a feedback loop between theoretical frameworks and real-world applications of contestable AI principles. He actively participates in research projects examining how AI systems can maintain societal accountability while delivering technological benefits. Alfrink leads the 'Contestable AI' research project at TU Delft, which investigates how to design AI systems that allow humans to challenge and influence decisions and development. This project brings together interdisciplinary researchers from design, computer science, and social sciences to develop frameworks for creating public AI systems that incorporate democratic oversight mechanisms directly into their technical architecture.

• Analytical Chemistry
• Food Chemistry
• Chemical Engineering
• +۵ مورد دیگر

Hans-Gerd Janssen is a Professor in Organic Chemistry at an institution (likely University of Wageningen) active in analytical and food chemistry. His work bridges gas chromatography , mass spectrometry , and chemical engineering to solve interdisciplinary problems in food systems and environmental analysis. Current research focuses on protein-flavor interactions , cannabinoid profiling , and microplastics detection . He supervises multiple PhD candidates in projects related to CBRN detection , sustainable food , and chromatography innovations . Recent publications highlight advancements in two-dimensional gas chromatography, QSAR modeling for flavor binding, and microplastics analysis. Collaborations span medical entomology (mosquito attraction studies) and materials science (Prussian Blue analogs). Media contributions emphasize food science applications (plant-based meat alternatives, sound science in culinary contexts).

• Machine Learning
• Critical Care Medicine
• Medical Informatics
• +۳ مورد دیگر

Ashley de Bie serves as a University Researcher at Eindhoven University of Technology within the Department of Electrical Engineering's Signal Processing Systems group. She is deeply embedded in the Eindhoven MedTech Innovation Center, a strategic partnership between TU/e and Catharina Hospital that drives medical technology translation into clinical practice. Her work directly addresses UN Sustainable Development Goals for health and well-being through engineering-clinical collaborations. Her research centers on machine learning applications for critical care, with three core thrusts: (1) developing and validating early warning systems like the Advanced Alert Monitor for patient deterioration detection; (2) creating computational tools for mechanical ventilation optimization, particularly in identifying patient-ventilator asynchrony; and (3) designing clinical decision support systems such as the TraceBook tool for individualized patient management. This work consistently bridges algorithm development with real-world hospital implementation. Analysis of her 2022-2025 publications reveals a strong trend toward context-specific validation of medical algorithms in Dutch healthcare settings. Key patterns include local optimization of international models, integration of clinician feedback in design cycles, and rigorous multicenter trials like the PRECISe study on critical care nutrition. Her publications demonstrate exceptional translational impact, with several tools already deployed in hospital workflows. With 349 Scopus citations and significant media attention (8 press mentions, 121 X posts, 101 Mendeley readers), her work resonates across academic and clinical communities. The PlumX metrics show particularly strong clinical uptake, with news coverage and social media engagement indicating real-world relevance. Dr. de Bie has supervised 5 students and maintains a robust collaborative network spanning TU/e's engineering departments and Catharina Hospital's clinical units. Her projects consistently involve multidisciplinary teams of data scientists, biomedical engineers, intensivists, and nurses, reflecting the complex nature of healthcare innovation. As a core contributor to the Signal Processing Systems group and Eindhoven MedTech Innovation Center, she operates within a dynamic ecosystem focused on rapid prototyping and clinical validation of medical technologies. Her current work with the Advanced Alert Monitor team exemplifies this environment, where algorithms move from simulation to hospital wards within months.

Melika Ayoughiمشاهده پروفایل

پژوهشگر

• Computer Vision
• Multimodal Representation Learning
• Hyperbolic Geometry in Machine Learning
• +۳ مورد دیگر

Melika Ayoughi is a PhD student at the University of Amsterdam , affiliated with the Faculty of Science and the Institute for Logic, Language and Computation (ILLC) . Her research focuses on computer vision and multimodal representation learning , particularly hierarchical knowledge modeling using hyperbolic geometry and self-supervised pretraining for transformers. Supervised by Prof. Dr. Paul Groth (INDE Lab) and Dr. Pascal Mettes (VIS Lab) Completed 4-month internship at Apple Machine Learning Research (2023) Research Themes: Hyperbolic embeddings for hierarchical data Continual learning of instance-class relationships Self-supervised pretraining through relative transformations Self-contained entity discovery in videos Key Article Trends : Recent work spans hyperbolic geometry applications in semantic hierarchies, continual learning frameworks for dual granularity recognition, and self-supervised vision transformers using relative patch relationships. Her methods show improvements over MAE/DropPos baselines in object detection and competitive performance on ImageNet-1k. Scientific Recognition : Nominated for Best Research Paper Award at ESWC 2025 Active in academic dissemination through conference presentations at ESWC, ECCV workshops, and Netherlands Conference on Computer Vision Teaching & Mentorship : Supervised multiple Master's and Bachelor's AI theses (2022-2024) Teaching Assistant for Applied Machine Learning (2020-2022) and Machine Learning 1 (2019) Mentor/Organization Team, Inclusive AI Program (2020-2023)

Debargha Deyمشاهده پروفایل

استادیار

• Human Factors in Transportation
• Intelligent Transportation Systems
• Ubiquitous Computing
• +۴ مورد دیگر

Debargha (Dave) Dey is an Assistant Professor in the Department of Industrial Design at Eindhoven University of Technology. He holds dual roles as an EAISI Foundational Assistant Professor and EAISI High Tech Systems researcher. His work focuses on human factors in Intelligent Transportation Systems and Future Mobility, with expertise in ubiquitous computing, multimodal interaction, and automotive user interfaces. He earned a PhD cum laude from TU Eindhoven in 2020, followed by postdoctoral research at TU Eindhoven and Cornell Tech. Education background includes a Master's in Computer Science from Vanderbilt University (2012), PDEng in User-System Interaction from TU Eindhoven (2017), and a PhD in Human-Machine Interaction (2020). Research interests emphasize traffic safety, autonomous vehicle-pedestrian interaction, and cross-cultural behavior modeling for AV development. His work addresses UN Sustainable Development Goals related to safe cities and communities (SDG 11). Recent research explores external human-machine interfaces (eHMIs) for autonomous vehicles, using VR simulators and participatory design methods. He investigates multimodal communication (light/sound) effectiveness and collaborative in-car activities' fairness. Awards: AutomotiveUI '22 Best Paper Award (2022) CHI '20 Best Paper Award (2020) AutomotiveUI '20 Honorable Mention (2020) Best Demo Award (2017) Active in ACM SIGCHI and AutomotiveUI communities, he serves on steering committees and organizes conferences like AutomotiveUI 2023. His work bridges academia and industry through collaborative projects on smart mobility solutions.

Chiara Gabellieriمشاهده پروفایل

استادیار

• Robotics
• Aerial Robotics
• Motion Control
• +۵ مورد دیگر

Chiara Gabellieri is an Assistant Professor specializing in Robotics and Mechatronics, focusing on advanced control systems, aerial robotics, and multi-rotor systems. Her work contributes to UN Sustainable Development Goals related to innovation and infrastructure. She collaborates internationally, with research emphasizing experimental validation, dynamic control, and morphing UAV designs. Her research interests include motion control of unmanned aerial vehicles (UAVs), collaborative robots (cobots), and optimal control strategies for flexible systems. Recent studies explore omnidirectional MAVs, impact-aware collision dynamics, and propeller force modeling in multi-rotor systems. Key contributions include experimental validation of propeller models, impact-aware UAV safety protocols, and the development of the OmniMorph morphing UAV. Her work is published in journals like Journal of Intelligent and Robotic Systems and at conferences such as ICUAS. Notable datasets include studies on cable-suspended load manipulation and collision dynamics, available via Zenodo and 4TU.Centre for Research Data. Collaborations span institutions globally, with a focus on interdisciplinary projects combining robotics, control theory, and aerospace engineering.