جست‌وجوی استاد و پژوهشگر

Abhishta Abhishtaمشاهده پروفایل

استادیار

• Cybersecurity
• Security Economics
• Finance & Behavior
• +۹ مورد دیگر

Abhishta Abhishta is an Assistant Professor at the University of Twente's Industrial Engineering & Business Information Systems group. His research focuses on cybersecurity economics, particularly measuring financial impacts of cyberattacks and improving organizational security investments through data-driven methods. Key research areas: Cybersecurity Economics, Digital Sovereignty, Behavioral Data Science Active in security analytics, ransomware studies, and trust mechanisms in predictive systems Contributions to EU policy analysis, DDoS defense, and cloud security risk frameworks Recent publications explore ransomware economics, dark web communication patterns, and digital sovereignty through EU legal documents. He combines technical cybersecurity analysis with behavioral science and economic modeling. Media expert on botnet business models and cybercrime economics Collaborates with industry on security decision-making Contributor to neuroscience-enhanced marketing research

• Geotechnical Engineering
• Soil Mechanics
• Material Point Method (MPM)
• +۷ مورد دیگر

Michael Hicks is a Professor at Delft University of Technology (TU Delft) in the Civil Engineering & Geosciences school, specializing in Geo-engineering . His research focuses on geotechnical risk assessment, soil variability, and advanced numerical methods like the Material Point Method (MPM) to model slope failures, earthquake simulations, and soil-structure interactions. Editorial board member for Géotechnique , Georisk , and Computers and Geotechnics (2019) Keynote speaker at workshops on slope failure modeling (2018) Active in public engagement about flood risk management (2017–2018) His work addresses challenges in soil heterogeneity, dynamic boundary conditions, and reliability-based design for infrastructure. Notable contributions include developing probabilistic MPM frameworks and machine learning tools for CPT data interpretation, with applications in earthquake resilience and radioactive waste repository safety. Recent publications highlight innovations in 3D slope stability analysis, nonlocal soil deformation modeling, and thermomechanical interface behavior under cyclic loading. Collaborations span academia and industry, focusing on improving numerical accuracy and understanding failure mechanisms in geotechnical systems.

Albert Gattمشاهده پروفایل

استاد

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Albert Gatt is a Professor of Natural Language Processing at Utrecht University's Department of Information and Computing Sciences, where he also serves as Programme Director for AI & Data Science. He holds an Associate Professor position (on leave) at the University of Malta's Institute of Linguistics and Language Technology. His research focuses on Natural Language Generation (NLG), multimodal models, and under-resourced language support, particularly for Maltese. He leads projects like NL4XAI and MASRI, addressing challenges in explainable AI and speech recognition. Education: Advanced degrees in computational linguistics and AI (not explicitly detailed in text). Key Projects: Multilingual NLG, Vision-Language benchmarks, Maltese ASR, and NLP evaluation methodologies. Research interests span data-to-text generation, vision-language interfaces, and evaluation practices. His work bridges computational linguistics with cognitive science, emphasizing human-AI collaboration. Notable contributions include the TUNA corpus, SimpleNLG toolkit, and foundational studies on referring expression generation. Publications (2025-2024) explore robust fine-tuning, LLM evaluation, and visual-linguistic grounding. Collaborations span academia and industry, addressing ethical AI and language equity. Supervises a global team of researchers and PhD students across multiple institutions, fostering innovation in NLG, multimodal AI, and Maltese language tech.

Tobias Blankeمشاهده پروفایل

استاد

• Artificial Intelligence
• Digital Humanities
• Big Data Ethics
• +۷ مورد دیگر

Professor Tobias Blanke is a leading scholar at the University of Amsterdam and the Institute for Logic, Language, and Computation , with additional affiliation as Visiting Professor of Social and Cultural Informatics at King’s College London. His work bridges artificial intelligence and humanities disciplines. PhD in Computer Science and Political Philosophy Director of DARIAH (2012–2016) Head of Digital Humanities Department at KCL (2016–2019) Blanke’s research focuses on artificial intelligence and big data applications within the human sciences, emphasizing ethical implications such as: Predictive policing systems Algorithmic othering Platform monopolization Computational genealogy XML retrieval frameworks His recent publications demonstrate increasing interdisciplinary collaboration in digital humanities , with key partnerships at the Open Data Institute , TacticalTech , and British Library . While no formal awards are listed in available materials, his leadership in infrastructural projects like the European Holocaust Research Infrastructure highlights significant contributions to the field. Blanke maintains active teaching and research roles, leading initiatives like the International Artificial Intelligence PhD Academy courses for social sciences. His technical expertise spans: XML retrieval systems NoSQL database applications Algorithmic governmentality Digital publishing frameworks

Antske Fokkensمشاهده پروفایل

استاد

• Computational Linguistics
• Language Technology
• Interpretable AI
• +۳ مورد دیگر

Prof. Antske Fokkens is a Full Professor in Computational Linguistic Methods at Vrije Universiteit Amsterdam, with joint appointments in the Faculty of Humanities and the Network Institute. She directs the Text Mining/Language and AI track in the Linguistics Master's program and serves as Vice Dean of Research. Her research investigates methodological aspects of computational linguistics, focusing on language models, interpretable AI, and digital humanities. She develops tools to extract patterns from large text corpora for applications in social science and history, emphasizing transparency and interdisciplinary collaboration. Current projects include analyzing perspective expression in media and semantic modeling for biographical data. Recent publications examine shortcut learning in text classification, persona-driven content generation, hate speech model alignment, and cross-disciplinary approaches to stance detection. Her work integrates NLP with social science theories to analyze discourse on sustainability, polarization, and media framing.

• Biomedical Engineering
• Obstetrics
• Signal Processing
• +۳ مورد دیگر

Guid Oei is a Part-time Professor at Eindhoven University of Technology in the Signal Processing Systems group, focusing on Biomedical Diagnostics . He also works as a Gynecologist at the Máxima Medical Center since 1996. Chair of Fundamental Perinatology Leader of the Fundamental Perinatal Care Research Group Co-founder of Woman Mother Child Center, Obstetrics High Care Unit, and NICU at Máxima Medical Center President of Stichting Gynaecongres (2011–present) Collaborator with institutions in Uganda and China His research integrates biomedical engineering with obstetrics to enhance maternal-fetal safety through signal processing and simulation. Key projects include the Technological Research Group Perinatology (TOP) and Impuls initiative with Philips Healthcare. His 15 most recent articles (2018–2025) focus on fetal monitoring , electrohysterography , AI-assisted diagnostics , and simulation-based training in low-resource settings. Common sub-fields include uterine contraction analysis , fetal heart rate variability , umbilical cord physiology , and global maternal health . He has supervised over 20 PhD students and contributed to 288 research outputs . His work aligns with UN SDGs for healthcare innovation and maternal safety. Key collaborations include: MEDICAID ENGINE : MedTech solutions for cardiovascular disease TKI-HTSM/20.0295/PPS2006 MEDUSA : Data utilization in obstetrics National Obstetrics Consortium

• Sea Level Change
• Climate Change
• Antarctica
• +۶ مورد دیگر

Prof. Roderik van de Wal is a Professor of Sea Level Change and Coastal Impacts at Utrecht University, affiliated with the Faculty of Science and collaborating with the Faculty of Geosciences. His research focuses on climate dynamics, polar ice sheets, and sea level changes, integrating observational and modeling approaches at the intersection of natural and earth sciences. Research Interests: Paleoclimate modeling and ice core interpretation Climate sensitivity and dynamics Sea level variations and ice dynamics of Greenland and Antarctica Glacier modeling and numerical ice sheet simulations Collaborative efforts bridge oceanography, meteorology, glaciology, hydrology, and physical geography. His work emphasizes understanding future sea-level rise drivers, including thermal expansion, ice melt, and storm surge impacts. Key Contributions: Developed models like ZEMBA and UFEMISM for Quaternary climate and ice sheet dynamics Explored Antarctic bedrock uplift effects and basal meltwater dynamics Assessed regional sea level risks for coastal adaptation strategies He supervises graduate students on topics ranging from glacial inception to compound flooding projections. His research supports policy-relevant sea-level assessments through initiatives like the EU Knowledge Hub.

• Pig Welfare
• Animal Welfare
• Feeding Behavior
• +۳ مورد دیگر

Iris Boumans is an Assistant Professor at Wageningen University's Wageningen Institute for Animal Science, specializing in Animal Production Systems . Her work bridges animal behavior modeling , precision livestock farming , and welfare assessment through innovative technologies like computer vision and machine learning . Active in applied ethology and agent-based modeling since 2013 Co-developer of 3D camera systems for pig posture/location tracking Recipient of three scientific awards for presentation and thesis excellence Key research themes include: Feeding behavior analysis and its links to health/stress Light spectrum/intensity impacts on circadian rhythms and growth Novel frameworks connecting circular economy principles to animal welfare Self-organizing maps for identifying behavioral types in sows Recent collaborations focus on ammonia exposure effects and sensor data aggregation for real-time welfare monitoring. Awards highlight her contributions to tail-biting modeling and feeding behavior analysis at international conferences. She supervises PhD candidates in projects like Enlighted Pigs and Drawing Pig Feeding Patterns , emphasizing individual variation and non-invasive assessment tools for improving pig welfare in modern farming systems.

Hans van Dijkمشاهده پروفایل

پژوهشگر

• Biomedical Engineering
• Clinical Neurophysiology
• Electrophysiology
• +۷ مورد دیگر

Hans van Dijk serves as a Senior Researcher in the Signal Processing Systems group within the Department of Electrical Engineering at Eindhoven University of Technology. He simultaneously holds leadership and research positions at multiple institutions, heading the Clinical Physics department at Kempenhaeghe (an institute specializing in Epileptology and Sleep medicine) and working as a Senior Researcher at the University Hospital in Ulm, Germany. His multidisciplinary career bridges engineering, clinical neurophysiology, and sleep medicine. Dr. van Dijk's research focuses on biomedical engineering applications in Clinical Neurophysiology, with particular expertise in electrophysiological techniques including EEG, EMG, and ECG. His work centers on developing and applying signal processing methods to diagnose neurological disorders, with specific emphasis on seizure detection using EEG , High-Density EMG for facial and masticatory muscles , and alternative diagnostic methods for sleep disorders . His recent publications demonstrate a strong focus on applying machine learning techniques to sleep medicine and epilepsy monitoring. Analysis of Dr. van Dijk's recent publications (2021-2025) reveals a consistent research trajectory in developing advanced signal processing methods for clinical neurophysiology. His work spans three main domains: epilepsy monitoring and seizure detection (particularly in children), sleep disorder diagnostics (using multimodal approaches beyond traditional polysomnography), and advanced EMG techniques for motor unit analysis. His research increasingly incorporates deep learning and multi-modal sensor fusion approaches to improve diagnostic accuracy while reducing the invasiveness of monitoring procedures. 2699 citations according to Scopus metrics 101 research outputs documented in institutional repository Active research collaboration with Philips Research and Kempenhaeghe Contributions to UN Sustainable Development Goals through medical diagnostics research Dr. van Dijk supervises research activities with 8 documented supervised works, collaborating extensively with clinical and engineering researchers across multiple institutions. His research program integrates signal processing expertise with clinical needs in neurology and sleep medicine, developing practical solutions for monitoring and diagnosing neurological disorders. His work at Kempenhaeghe focuses on translating engineering innovations into clinical practice for epilepsy and sleep disorder patients.

Rianne M. Schoutenمشاهده پروفایل

پژوهشگر

• Computer Science
• Data Mining
• Exceptional Model Mining
• +۶ مورد دیگر

Rianne M. Schouten is a postdoctoral researcher at Eindhoven University of Technology (TU/e), affiliated with the School of Mathematics and Computer Science and specializing in Data Mining . Her work focuses on Exceptional Model Mining and Pattern Discovery in complex datasets, including hierarchical and sequential data. She has held external positions at Utrecht University (2017–2019), Columbia University (2016), and SRON Netherlands Institute for Space Research (2015). Research Trends : Her publications (2017–2025) emphasize quality measures for data mining, subgroup discovery , and sequence analysis , with applications in Markov chains and high-dimensional data . Collaborations span France, the Netherlands, and the U.S. External Roles : External researcher, Utrecht University (2017–2019) Staff associate, Columbia University (2016) Intern, SRON Netherlands Institute for Space Research (2015)

• Explainable AI
• Privacy-Preserving Machine Learning
• Medical Image Analysis
• +۶ مورد دیگر

Dr. W.J. (Wilson) dos Santos Silva is an Assistant Professor at the Faculty of Science , University of Utrecht, specializing in AI & Data Science and Biology . His research focuses on creating explainable and robust AI models for multimodal multi-centre medical data , with emphasis on privacy-preserving machine learning and out-of-distribution generalization . PhD in Electrical and Computer Engineering (2022), University of Porto Master's and Bachelor's in Electrical and Computer Engineering (2016), University of Porto Research Interests include: Explainable AI for medical decision-making transparency Privacy-Preserving Machine Learning in healthcare Multi-Centre Data Analysis across institutions Medical Imaging applications in oncology and neurology Recent Publications demonstrate expertise in: Medical image segmentation techniques Cross-modal learning approaches Federated learning for privacy Biomedical data interpretation Generalization in heterogeneous datasets Scientific Contributions include organizing the iMIMIC workshop at MICCAI 2024 and mentoring students receiving competitive awards. Students & Collaborators : PhD Candidates: Valentina Corbetta, Daan Boeke, Miriam Cobo, Aniek Eijpe, Jan van Eck Postdoctoral Researchers: Soufyan Lakbir Former Students: Tingyang Jiao, Laura Latorre, Filipe Campos, etc. Laboratory develops AI solutions for medical imaging , multi-centre collaboration , and ethical AI in healthcare contexts.

• Artificial Intelligence
• Remote Sensing
• Earth Observation
• +۵ مورد دیگر

Annisa Puspa Kirana is a Ph.D. candidate and researcher at the Department of Geo-information Processing (ITC-GIP), Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente. She is a Lecturer in the Department of Information Technology at State Polytechnic of Malang, currently on study leave to focus on her Ph.D. research. Her work integrates Artificial Intelligence , Computer Vision , and Geospatial Analytics to analyze satellite/aerial imagery for Climate Change Mitigation , Disaster Monitoring , and Resource Management . PhD in Geo-Information Science @ University of Twente (Netherlands) Master of Computer Science @ IPB University (Indonesia) Her research emphasizes Deep Learning applications in Earth Observation, including Vision-Language Models and Agentic AI for multimodal data analysis. She collaborates with interdisciplinary teams , government agencies , and industry partners . Selected Publications Trends: Focus on AI agents , LLMs , VLMs , and Vision Transformers for geospatial and environmental applications Technical tutorials on Streamlit , TalkToEBM , and LangChain integration Conceptual breakdowns of agentic vs. agent-based systems , interpretability in AI , and prompt engineering Scientific Awards: LPDP Awardee (Indonesian Endowment Fund for Education) Microsoft Certified Educator She actively mentors students in AI/geospatial fields and advocates for open-source science and ethical AI practices in environmental decision-making. Her work bridges academic research and practical policy tools .

Ihor Smalمشاهده پروفایل

استادیار

• Image Analysis
• Smart Microscopy
• Artificial Intelligence
• +۷ مورد دیگر

Ihor Smal is an Assistant Professor at the Department of Biology, Faculty of Science, Utrecht University. He has held previous positions at Erasmus MC (2009-2018) and TU Delft (2019-2020). His research bridges statistical image processing, smart microscopy, and explainable AI for biological motion analysis, with applications in automated real-time imaging systems. Education: M.Sc. in Physics and Electrical Engineering, Ivan Franko National University of Lviv (1999, cum laude) Professional Doctorate in Engineering (PDEng), Eindhoven University of Technology (2005) PhD in Biomedical Imaging, Erasmus University/MC (2009) His work focuses on developing AI-driven solutions for motion registration, particle tracking, and image understanding in biological systems. He leads the NWO IMAGINE! program's Tech Work Package 2, aiming to automate imaging experiments using explainable AI. The 15 most recent publications highlight his contributions to deep learning for CT segmentation, particle tracking, diffusive state modeling, and real-time imaging optimization. Key subfields include neural networks, biomedical signal processing, and automated microscopy. Scientific Awards: VENI grant Erasmus MC Fellowship NWO BBoL grant Students: Vincent Hellebrekers Daan te Rietmole His lab at Utrecht University, accessible via www.smal.ws, collaborates with institutions like Erasmus MC and TU Delft, leveraging facilities such as the Utrecht Biology Imaging Center.

Yoeri R.J. Poelsمشاهده پروفایل

پژوهشگر

• Fusion Energy
• Tokamak Engineering
• Deep Learning Applications
• +۴ مورد دیگر

Yoeri R.J. Poels is a researcher at Eindhoven University of Technology specializing in fusion energy and artificial intelligence applications. His work focuses on enhancing tokamak operations through data-driven modeling and AI techniques, with significant contributions to the Eurofusion Tokamak Exploitation Team and MAST Upgrade collaboration. His research interests bridge fusion energy engineering and artificial intelligence , particularly in developing surrogate models and deep learning algorithms for tokamak control systems. Key areas include power exhaust management, divertor technology, and real-time plasma control solutions for next-generation fusion reactors. His work integrates physics-based modeling with advanced machine learning techniques to address critical challenges in fusion energy development. Analysis of his publication record reveals a strong trajectory in applying AI methods to fusion challenges , with increasing focus on practical implementation in experimental tokamak devices. His recent work demonstrates how data-driven approaches can enhance control systems for managing transient heat loads and improving reactor stability. As part of major international collaborations including the MAST Upgrade team and TCV tokamak research, Poels contributes to cutting-edge fusion research across multiple institutions. His work appears in high-impact journals including Nature Energy , Communications Physics , and Nuclear Fusion , reflecting the interdisciplinary nature of his research at the intersection of physics, engineering, and computer science.

• human-centered ai
• psychology of technology
• machine learning
• +۵ مورد دیگر

Chao Zhang is an Assistant Professor in Human-Centered AI at the Human-Technology Interaction group, Eindhoven University of Technology. His research bridges psychology and technology through data-driven methods and psychological theories, focusing on behavior change, AI-human dynamics, and trustworthy systems. MSc in Human-Technology Interaction (TU/e) PhD in Intelligent Systems (TU/e, 2019) Postdoc at Utrecht University Research interests span Human-Centered AI , Explainable AI , and Behavioral Data Science . Key contributions include: Integrating psychological principles with machine learning Modeling longitudinal behavioral data Developing interpretable AI systems for lifestyle interventions Investigating social characteristics in AI-driven environments Current work includes the ENFIELD project on Trustworthy Green AI. Scientific contributions appear in CHI Conference , arXiv , and International Journal of Social Robotics . Recognized with a TU/e PhD Thesis Award nomination in 2021.