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Rob TimmermansView profile

Professor

• Theoretical Particle Physics
• Quantum Mechanics
• Quantum Field Theory
• +3 more

Prof. Rob Timmermans is a Professor of Theoretical Physics and Vice-Dean for Education at the University of Groningen (UG). He is affiliated with the Faculty of Science and Engineering and the Precision Frontier — Van Swinderen Institute for Particle Physics and Gravity. His research focuses on theoretical particle physics, quantum mechanics, and precision measurements, particularly in electric dipole moment (EDM) searches using molecules like BaF. His work includes developing methods for molecular beam manipulation, phase-space analysis, and symmetry violation studies. He has contributed to collaborations such as NL-eEDM, advancing techniques for EDM detection and precision physics. Prof. Timmermans has received nominations for teaching awards, reflecting his commitment to education. Research highlights include studies on nucleon decay, antinucleon-nucleon interactions, and chiral effective field theory. His lab activities involve collaborations on laser-cooled molecules and trapping techniques. Prof. Timmermans’ articles often address fundamental physics questions, such as Lorentz violation in beta decay and parity violation in molecular systems. Awards: Nominated for Faculty Teaching Award 2014, Teacher of the Year 2014-15. Grants/Advising: Leads projects on EDM searches and particle physics, with active roles in international collaborations. Labs/Teams: Van Swinderen Institute, Precision Frontier group.

• Digital Archaeology
• Computational Archaeology
• Machine Learning in Archaeology
• +13 more

Karsten Lambers is Professor of Digital and Computational Archaeology at the Faculty of Archaeology, Leiden University, where he leads research and teaching in the application of computational methods to archaeological data. His work integrates machine learning, remote sensing, text mining, and citizen science to advance archaeological prospection and heritage management. He is affiliated with the Department of Archaeological Sciences and plays key roles in research groups and university-wide initiatives such as SAILS and ARCHON. His research interests span Digital Archaeology , Machine Learning in Archaeology , Remote Sensing , Geoarchaeology , and Human-Environment Interaction . He investigates how computational tools can extract meaningful archaeological information from large datasets, including LiDAR imagery and excavation reports. His fieldwork spans Central Europe and Latin America, with a focus on prehistoric landscapes and cultural heritage. The analysis of his recent publications reveals a strong trend toward automated detection using deep learning (e.g., R-CNN, WODAN), named entity recognition in archaeological texts (e.g., ArcheoBERTje), and citizen science integration for data validation. His work bridges archaeology with computer science, geomatics, and environmental science, emphasizing interdisciplinary collaboration and methodological rigor. His scientific awards include: Best Thesis Award (University of Zurich, 2005) EUROPA NOSTRA Award (2020, 2022) Membership in the German Archaeological Institute (since 2022) Lambers actively supervises students and leads major research projects such as ABMA, EXALT, and Heritage Quest. He has secured substantial research funding and collaborates widely with computer scientists, geophysicists, and palaeoecologists. His teaching includes digital methods, modeling, and simulation, often linked to ongoing research. He has also contributed to open educational resources and digital textbooks in archaeology. He leads or participates in several research labs and teams, including the Digital Archaeology Research Group (which he chairs), the Heritage Quest citizen science project, and interdisciplinary teams focusing on alpine terraces and Iraqi prospection. His work emphasizes the integration of digital tools into practical archaeological workflows, advocating for complementary human-computer strategies.

Jakob SchoefferView profile

Assistant Professor

• Responsible AI
• Explainable AI
• Human-Centered AI
• +6 more

Jakob Schoeffer is a tenure-track Assistant Professor in the Artificial Intelligence department at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, Faculty of Science and Engineering, University of Groningen (Netherlands). His work focuses on the intersection of human decision-making and artificial intelligence, particularly in high-stakes contexts where fairness, transparency, and appropriate human-AI collaboration are critical. Dr. Schoeffer's research interests center on responsible and explainable AI, with specific focus areas including: Human-AI collaboration dynamics in decision-making processes Fairness perceptions and interventions in AI systems Appropriate reliance on AI recommendations Explainable AI techniques for high-stakes domains Transparency mechanisms that improve human-AI team performance Label indeterminacy issues in medical AI applications His recent publications (2023-2025) reveal a strong trend toward applying AI research in critical domains like healthcare (particularly neurological recovery prediction), while maintaining a rigorous focus on the human aspects of AI deployment. His work spans both theoretical foundations of human-AI interaction and practical implementations, often employing mixed-methods approaches that combine technical AI development with behavioral studies. Dr. Schoeffer actively collaborates with researchers across institutions including the University of Texas at Austin and has made significant contributions to top conferences in AI ethics, fairness, and human-computer interaction. His research has been featured in multiple news outlets and policy discussions, indicating real-world impact of his work on responsible AI development. Prior to his current appointment, Dr. Schoeffer was a Postdoctoral Research Fellow at the University of Texas at Austin. He received his PhD from the Karlsruhe Institute of Technology (KIT) in Germany with a dissertation titled "On the Interplay of Transparency and Fairness in AI-Informed Decision-Making." He also holds a master's degree in Operations Research from Georgia Tech and industry experience as a Senior Data Scientist at IBM.

Raquel FernándezView profile

Professor

• Computational Linguistics
• Dialogue Systems
• Cognitive Science
• +3 more

Raquel Fernández is Full Professor of Computational Linguistics and Dialogue Systems at the University of Amsterdam, where she leads the Dialogue Modelling Group at the Institute for Logic, Language & Computation (ILLC). As Vice-Director for Research at ILLC and a Fellow of the ELLIS Society, she bridges computational linguistics, cognitive science, and artificial intelligence through her research on language use in multimodal and conversational contexts. PhD in Computational Linguistics from King's College London Prior research positions at University of Potsdam and Stanford University's CSLI Her work explores how cognitive constraints, social interaction, and perception shape language use, with a focus on: Visually-grounded language processing Multimodal dialogue modeling Model uncertainty and calibration Language grounding in multimodal data Language learning and semantic change Dialogue reference resolution Recent publications analyze multimodal reasoning limitations, cross-lingual knowledge consistency, and uncertainty modeling in dialogue systems. She has received multiple accolades including an ERC Consolidator Grant , NWO VENI/VIDI/Aspasia fellowships , and EMNLP/GenBench awards . Outstanding Paper Award (EMNLP 2023) Best Data Award (GenBench Workshop 2023) ELLIS Society Fellow ERC Consolidator Grant #819455 recipient NWO VENI/VIDI/Aspasia awardee As a leader in academic service, she serves on the SIGDAT Executive Committee and chairs multiple conference committees. Her lab develops models for multimodal dialogue, visual storytelling, and grounded language understanding.

Steven HoekstraView profile

Associate Professor

• Atomic Physics
• Molecular Physics
• Stark Deceleration
• +5 more

Prof. dr. Steven Hoekstra is an Associate Professor of Atomic and Molecular Physics at the University of Groningen's Faculty of Science and Engineering, within the Van Swinderen Institute. His research focuses on precision measurements using cold molecules to explore fundamental physics, including Stark deceleration, laser cooling, and searches for physics beyond the Standard Model. He leads the NL-eEDM program at Nikhef, investigating the electron's electric dipole moment. Hoekstra is also involved in educational innovation, having received the Teacher of the Year award (2020) and a Senior Teacher Qualification (2023). He has supervised over 11 PhD theses and currently mentors 5 students. His work combines experimental techniques with theoretical insights, addressing questions like symmetry violations and quantum dynamics. Key projects include manipulating BaF molecules with electrostatic fields and exploring levitated nanoparticles as sensors. Hoekstra has secured major grants, including NWO VICI (2022) and VIDI (2013), and collaborates internationally on projects like the European Strategy for particle physics. Recent articles highlight advancements in molecular beam control, spin-precession methods for EDM searches, and opportunities in radioactive molecules. He actively participates in the Physics Olympiad Netherlands as chair, contributing to science outreach and education.

Massimo MischiView profile

Professor

• Biomedical Signal Processing
• Diagnostic Imaging
• Ultrasound Technology
• +4 more

Massimo Mischi is a Full Professor at the Faculty of Electrical Engineering of the Eindhoven University of Technology (TU/e) and chairs the Signal Processing Systems (SPS) Division , the largest division at TU/e with over 250 researchers. He founded the Biomedical Diagnostics (BM/d) Lab in 2012, which now includes 180 researchers and clinical/industrial advisors, focusing on biomedical signal processing for diagnostics and monitoring.

• Evolutionary Computation
• Machine Learning
• Natural Computing
• +5 more

Thomas Bäck is a Professor at the Leiden Institute of Advanced Computer Science (LIACS) , Leiden University , Netherlands, and a member of the interdisciplinary programme Society, Artificial Intelligence and Life Sciences (SAILS) . His academic career spans roles at Leiden University (1996–present) and leadership positions at the Center for Applied Systems Analysis in Dortmund (1994–2000). Education : Diplom-Informatiker (Computer Science), Technische Universität Dortmund (1990) Dr. rer. nat. (Computer Science), Technische Universität Dortmund (1994) Research Interests : Dr. Bäck specializes in evolutionary computation , machine learning , and their applications in sustainable smart industry and healthcare . Recent work focuses on integrating large language models (LLMs) and quantum computing into optimization frameworks, with projects like CIMPLO (predictive maintenance), ECOLE (experience-based optimization), and SAPPAO (airline operations optimization). Scientific Contributions : His 526+ publications cover evolutionary algorithms, quantum optimization, and LLM-driven design, with recent trends including: Quantum computing (e.g., quantum approximate optimization, quantum advantage challenges) LLM integration (e.g., hyperparameter tuning, mutation control, code evolution graphs) Healthcare and industry (e.g., predictive maintenance, anomaly detection, melt quality prediction) Algorithm benchmarking (e.g., IOHprofiler, MA-BBOB, explainable benchmarking) Scientific Awards : IEEE Fellow (2022) Royal Netherlands Academy of Arts and Sciences (KNAW) member (2021) Academia Europaea member (2022) IEEE Computational Intelligence Society Evolutionary Computation Pioneer Award (2015) Fellow, International Society of Genetic and Evolutionary Computation (2003) Best Ph.D. thesis award, German Society of Computer Science (GI) (1995) Advising and Grants : He supervises Ph.D. candidates in evolutionary computation and machine learning and has secured 7 major grants from organizations like the Dutch Research Council , European Commission , and The Research Council of Norway . His editorial roles include Editor-in-Chief of the Evolutionary Computation Journal and associate editorships in leading AI journals.

Michael BurkeView profile

Professor

• Rhetoric
• Stylistics
• Cognitive Linguistics
• +5 more

Professor Michael Burke holds a full professorship in Rhetoric at Utrecht University (Faculty of Humanities) and teaches at University College Roosevelt (UCR) in Middelburg. Previously, he served as UU Honours Dean (2016–2021). His research focuses on rhetoric, stylistics, cognitive aspects of language, and education. He earned his Ph.D. in English Language and Literature from the University of Amsterdam, where he also completed his undergraduate studies. Research interests span written, oral, and digital rhetoric, emphasizing pedagogical, cognitive, stylistic, and neuroscientific dimensions. He has held visiting roles at institutions like the University of Cambridge and University of Bologna. Editorial roles include series editor for Routledge’s 'Research Monographs in Linguistics' and board memberships with journals like Language and Literature . Teaching includes undergraduate courses on classical rhetoric, argumentation, and public speaking at UCR, plus leadership and interdisciplinary research modules for Utrecht’s Honours College. He supervises PhD students in the UiL-OTS linguistics research school. Notable publications include The Routledge Handbook of Stylistics (2023) and studies on critical thinking, digital literacy, and cognitive literary science. Professional activities include keynote speaking at conferences like PCST and EARS, and contributions to projects such as ‘Undergraduate Research in the Netherlands’. His work bridges rhetoric, cognitive science, and education, emphasizing practical applications for students and educators.

Mathias FunkView profile

Associate Professor

• Design Theory
• Systems Design
• Data-Driven Design
• +5 more

Mathias Funk is an Associate Professor in the Industrial Design department at Eindhoven University of Technology (TU/e), leading the Things Ecology lab. His research focuses on designing with data and systems behavior, particularly in IoT and medical technology contexts. He co-founded UXsuite GmbH and developed the OOCSI communication framework. With a PhD in Electrical Engineering from TU/e (2011), Funk has held academic roles since 2013, including postdoctoral positions in Electrical Engineering and Industrial Design. He teaches courses like 'Data-enabled design' and supervises projects on AI, data foundry, and OOCSI applications. His work bridges engineering and design, addressing sustainability and human values through systemic design approaches. Education: PhD in Electrical Engineering, TU/e (2011) Computer Science background from RWTH Aachen Postdoc at TU/e's Electrical Engineering and Industrial Design departments Research Interests: Data-driven design methodologies, IoT systems, medical technology innovation, sustainable design practices, and interactive systems for musical expression. Recent work emphasizes telemonitoring efficacy in heart failure care and federated learning applications. Awards: Best Paper Award (2014) Honorable Mention (2021) Grants/Projects: Leading initiatives like MEDICAID (medtech solutions), ACACIA (interpretable AI), and Data-Driven Servitizing in Professional Printing. Active in clinical workflow prototyping and cardiovascular disease detection projects. Lab Activities: Manages the Things Ecology lab, focusing on systemic design challenges in smart ecosystems. Collaborates internationally through spin-offs and visiting lectureships.

Willemijn van DolenView profile

Professor

• Consumer Behavior
• Marketing Strategy
• Social Media Analysis
• +5 more

Prof. Willemijn van Dolen is a Professor in the Section of Marketing at the Faculty of Economics and Business, University of Amsterdam. Her research focuses on consumer behavior, marketing strategies in digital environments, and the psychological impacts of communication in service encounters. She has extensively studied topics such as visual influence in consumer decisions, corporate greenwashing detection, and the role of humor in service interactions. Her academic career includes notable contributions to understanding online consumer behavior through multimodal datasets and AI frameworks. She has published widely on social media analytics, CSR communication, and child helpline effectiveness, bridging psychological insights with practical marketing applications. Prof. van Dolen’s work emphasizes empirical investigations into customer engagement, ethical consumption, and the interplay between digital platforms and human decision-making. Her research demonstrates a consistent focus on real-world applications, from optimizing brand posts on Instagram to analyzing CEO communication during global crises. Her studies often employ interdisciplinary methods, combining marketing theory with data science and behavioral economics. Despite her prolific output (over 50+ publications), no specific scientific awards are highlighted in the provided texts.

Ming CaoView profile

Professor

• Multi-agent systems
• Autonomous Robots
• Complex Systems and Networks
• +4 more

Ming Cao is a Full Professor at the University of Groningen (Netherlands), holding positions in the Department of Discrete Technology and Production Automation, the Engineering and Technology Institute Groningen, and serving as Chair of the Jantina Tammes School of Digital Society, Technology and AI. His academic roles include Director of the Jantina Tammes School and membership in prestigious organizations such as the International Federation of Automatic Control (IFAC) and the European Commission’s DG CNECT. Cao’s research focuses on multi-agent systems, autonomous robotics, complex networks, and cooperative control, with applications in robotics, epidemic modeling, and biomimetic sensors. Education: PostDoc in Mechanical Engineering from Princeton University (2008), PhD in Electrical Engineering from Yale University (2007). Research Interests: Multi-agent systems, distributed decision-making, cooperative control, robotic teams, seal whisker-inspired flow sensing, and privacy-preserving control systems. Recent Trends in Articles: Recent work emphasizes co-evolutionary dynamics in social-technical systems, privacy in control systems, and biomimetic robotics. Key topics include feedback mechanisms in cooperation, hypergraph-based epidemic models, and seal whisker mechanics for underwater sensing. Awards: European Control Award (2016), Manfred Thoma Medal (2017), ERC Grant (2012). Grants: Vidi Grant from NWO (2015) for agent coordination research. Labs/Teams: Jan C. Willems Center for Systems and Control, Research Center for Data Science and Systems Complexity (DSSC). Active in editorial roles for journals like Artificial Life and Robotics and the SIAM Journal on Control and Optimization .

Hyosang LeeView profile

Assistant Professor

• Tactile Sensing
• Robotics
• Soft Robotics
• +4 more

Hyosang Lee is an Assistant Professor in the Robotics Section of the Mechanical Engineering Department at Eindhoven University of Technology (TU/e). He holds a PhD from KAIST and has held research positions at the Max Planck Institute and University of Stuttgart. His work focuses on tactile sensing technologies, including artificial skin development, soft robotics, and integration of sensory systems with AI. Bachelor's: Mechanical Engineering, Korea University Master's: Robotics and Mechanical Engineering (double major) PhD: Mechanical Engineering, KAIST (2017) Research interests span tactile sensor design, electrical impedance tomography (EIT), and human-robot interaction. His group emphasizes creating scalable, flexible tactile systems for robots. Recent work includes air pressure sensing for force estimation and biomimetic skin materials. Publications highlight innovations in multi-directional force sensing, soft component technologies, and haptic interfaces for autism therapy. He teaches 'Dynamics and Control of Robotic Systems' and serves on the editorial board of npj Robotics . No formal student advisees are listed, though his lab, the Tactile Sensing and Robotic Skin Group , likely involves graduate researchers. His research contributes to UN Sustainable Development Goals related to health and technology.

• Sports Analytics
• Predictive Analytics
• Complex Networks
• +3 more

Dr. Otto Koppius is an Assistant Professor at the Rotterdam School of Management , Department of Technology and Operations Management. His research focuses on sports analytics , predictive analytics , and complex networks , emphasizing data-driven decision-making in organizations. He explores applications ranging from talent identification in sports using sensor data to sustainability in supply chains. Key research interests include: Methodological advances in predictive analytics, including feature engineering and algorithmic bias detection. Integration of predictive analytics into organizational practices. Smart cargo sensor data for optimizing supply chain networks. Past work includes studies on social influence in networks, closed-loop supply chains, and knowledge transfer within firms. His articles analyze topics like network interventions, innovation dynamics, and digital ecosystem orchestration. No scientific awards were explicitly mentioned in the provided text. He has supervised 6 academic works, though specific student names are not listed. Research extends to themes like sustainability, business strategy, and organizational behavior, with a focus on translating technical methods to real-world business challenges.

• Latent Variable Modeling
• Machine Learning
• Measurement Equivalence
• +3 more

Dr. David Goretzko is an Assistant Professor in the Department of Methodology and Statistics at Utrecht University's Faculty of Social and Behavioural Sciences. He leads the Measurement and Machine Learning Lab and specializes in the integration of data science techniques with psychometric theory. His academic journey includes: Ph.D. in Psychological Methods from LMU Munich (2020) M.Sc. in Statistics from LMU Munich (2018) M.Sc. in Psychology from LMU Munich (2016) B.Sc. in Physics from LMU Munich (2015) B.Sc. in Psychology from LMU Munich (2014) Dr. Goretzko's research primarily focuses on the intersection of machine learning and psychometrics. His work addresses critical challenges in factor analysis, measurement invariance, and model fit assessment. He develops innovative methods that combine traditional psychometric approaches with modern data science techniques, particularly in the areas of exploratory factor analysis trees, regularized factor analysis, and cost-sensitive machine learning applications in psychological assessment. His research has significant implications for improving the validity and reliability of psychological measurements across diverse populations. His recent publications reveal a strong trend toward integrating machine learning methodologies with traditional psychometric approaches. A significant portion of his work focuses on factor analysis techniques, particularly addressing the challenge of determining the appropriate number of factors. His research also extensively covers measurement invariance testing across multiple covariates using tree-based approaches, and he has made notable contributions to evaluating model fit in confirmatory factor analysis. The interdisciplinary nature of his work spans psychology, statistics, and computer science. Dr. Goretzko serves as an Associate Editor for the European Journal of Psychological Assessment and is an active reviewer for numerous prestigious journals including Psychological Methods, Behavior Research Methods, and Structural Equation Modeling. He also reviews grant proposals for major funding agencies such as the German Research Foundation (DFG), National Science Foundation (NSF), and Dutch Research Council (NWO). He currently holds a Project Grant from the German Research Foundation (DFG GO 3499/1-1) since 2021. His research program focuses on developing and validating new methodologies for psychological assessment that incorporate machine learning techniques while maintaining psychometric rigor. His work has practical applications in educational measurement, clinical psychology, and organizational assessment. Dr. Goretzko leads the Measurement and Machine Learning Lab at Utrecht University, which focuses on developing innovative methodologies that bridge the gap between traditional psychometrics and modern data science. The lab's research has particular relevance for improving measurement practices in cross-cultural research, educational assessment, and clinical psychology settings where measurement invariance and factor structure validation are critical concerns.

• Environmental Science
• Climate Change Mitigation and Adaptation
• Geographic Information Systems (GIS)
• +3 more

Dr. Jennifer Koch is an Associate Professor at the Laboratory of Geo-information Science and Remote Sensing, part of Wageningen University & Research. Previously, she served as an Associate Professor and Associate Research Director at the University of Oklahoma's Data Institute for Societal Challenges. Her research integrates data-driven methods like simulation modeling to address socio-economic and climate change challenges, focusing on sustainable urbanization and environmental management. Education: She holds a Diplom (Univ.) in Geoecology from the University of Bayreuth and a Dr.-Ing. in Electrical Engineering/Computer Science from the University of Kassel. She teaches courses on geo-information management and data analytics. Research emphasizes multi-scale modeling, stakeholder engagement, and participatory approaches to socio-ecological systems. Recent work explores urban growth in Africa, methane emission monitoring, and renewable energy siting. Articles highlight interdisciplinary methods in GIS, climate policy, and community geography. Professional service includes roles with iEMSs, IALE, and the AAG. No ancillary activities reported. Her work bridges technical geospatial tools with societal challenges, emphasizing practical policy applications.