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Ron H.J. Peerlings is Associate Professor in the Department of Mechanical Engineering at Eindhoven University of Technology (TU/e) , where he leads the Mechanics of Materials research group. Promoted to Associate Professor in 2007 after joining as Assistant Professor in 2000, he has built an extensive portfolio in theoretical and computational mechanics of materials. Education: PhD (1999) – Eindhoven University of Technology, thesis: Enhanced damage modelling for fracture and fatigue Post-doctoral research (1999–2000) – University of Cambridge, Engineering Department Research interests revolve around micromechanics , micro-plasticity , multiscale modelling , homogenisation , damage and fracture , and enriched continuum theories . His work spans advanced high-strength steels, composites, paper and fibrous networks, with strong emphasis on coupling rigorous theoretical developments to industrially motivated problems. His recent publications (2023-2025) demonstrate a clear trajectory towards integrating advanced experimental techniques (e.g., digital image correlation, micro-mechanical testing) with high-fidelity computational frameworks such as crystal-plasticity finite-element modelling, FFT-based solvers and micromorphic homogenisation. Dominant themes include: Deformation and fracture in lath martensite and dual-phase steels Hygro-mechanics of paper and fibrous networks Pattern-transforming mechanical metamaterials Discrete-to-continuum scale bridging methods Scientific awards are not explicitly listed in the provided material; however, his prolific output (294 research items, >6500 citations) attests to significant peer recognition. Teaching & supervision: He delivers courses on Computational Mechanics – Numerical Methods for Fluids and Solids and Fracture Mechanics – Theory and Application , and has supervised >80 student works and numerous PhD candidates whose names appear on joint publications. Laboratory & teams: He heads the Group Peerlings within the Mechanics of Materials cluster, maintaining close collaboration with the Mechanics of Materials Group Geers and extensive national/international experimental and computational networks.

• Micromechanics
• Micro-plasticity
• Multiscale modelling
• +7 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.

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

Professor Jasper van Wezel is a distinguished academic in the field of Condensed Matter Theory at the University of Amsterdam's Faculty of Science, where he serves as Professor in the Institute for Theoretical Physics (ITFA) within the Institute of Physics. With a career spanning over two decades, he has progressed from Assistant Professor (2014-2016) to Associate Professor (2016-2024) and currently holds the position of Professor since 2024. His academic journey began with a PhD in theoretical condensed matter physics from Leiden University in 2007, followed by prestigious fellowships at Argonne National Laboratory and Homerton College, Cambridge. PhD in theoretical condensed matter physics (cum laude), Leiden University, 2007 Master's diploma in theoretical condensed matter physics (cum laude), Leiden University, 2003 Dutch VWO Diploma (cum laude), Dalton Scholengemeenschap, Den Haag, 1997 US High School Diploma (cum laude), Sanford High School, Maine, USA, 1998 Professor van Wezel's research focuses on several interconnected areas within Condensed Matter Theory. His work explores competing instabilities in Charge Density Wave materials, including Superconductivity and Charge Order, Combined Charge and Orbital Order, and Transition-metal dichalcogenides. He has made significant contributions to Topology in Condensed Matter, particularly examining the Role of crystal symmetries and Topology in non-Hermitian systems. A major theme in his research involves investigating the Connections between Quantum and Classical behaviour, with special emphasis on Spontaneous Symmetry Breaking both in equilibrium (The role of the Thin Spectrum) and dynamically (Spontaneous loss of Unitarity). Analysis of Professor van Wezel's recent publications reveals a strong focus on quantum phenomena in condensed matter systems, with particular attention to topological aspects, symmetry breaking, and connections to fundamental physics concepts like black hole thermodynamics. His work often bridges theoretical concepts with potential experimental realizations, as evidenced by studies on electron patterns in materials like TaS2 and theoretical frameworks for understanding quantum phase transitions. Bristol Physics Teaching Award (2014) Students' Award for Outstanding Teaching (2014) Fellow of the Higher Education Academy (2014) Aneesur Rahman Fellowship at Argonne National Laboratory (2010-2012) Junior Research Fellowship at Homerton College, Cambridge (2007-2010) Physics 'Discovery of the year' by Leiden University Physics department (2005) 'Onderwijsprijs Natuurkunde' teaching award (2004/2005) Professor van Wezel has secured numerous research grants including an ENW-M grant (2023), an ENW-Groot project with Leiden University (2021), and a prestigious VIDI personal grant from NWO (2014). He has supervised over 50 students at various levels, including PhD candidates, MSc students, and BSc students, fostering the next generation of physicists. His leadership extends to organizing conferences, serving on PhD committees, and holding administrative roles such as chair of the educational committee for the Dutch Research School in Theoretical Physics. His research group at the University of Amsterdam's Institute for Theoretical Physics maintains active collaborations with institutions worldwide, including Leiden University, University of Cambridge, University of Bristol, and research centers in France, Germany, and Poland. The group's work combines analytical theoretical approaches with computational methods to tackle fundamental questions in quantum condensed matter physics.

• Condensed Matter Theory
• Quantum Phase Transitions
• Topological Materials
• +7 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.

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

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

Prof. Marc Koper is a Professor of Catalysis and Surface Chemistry at Leiden University, affiliated with the Leiden Institute of Chemistry (LIC) . His research focuses on sustainable energy and chemistry, particularly electrocatalytic redox reactions of carbon, nitrogen, and oxygen compounds. He leads a dynamic research group with 17 current PhD candidates, including Ariba Adnan, Karen van den Akker, and others. Koper’s work bridges experimental, theoretical, and catalyst design principles to advance energy transition technologies. His research interests span catalysis , electrochemistry , and surface chemistry , with a focus on CO 2 reduction , nitrate reduction , and electrochemical water oxidation . Recent studies emphasize solvent effects, cation roles in catalysis, and nanostructured electrode design to enhance reaction selectivity and efficiency. Notable achievements include the Antwerp Honorary Doctorate (2024) for contributions to sustainable energy research. His publications explore topics like platinum hydride formation, double-layer capacitance measurement challenges, and the mechanisms of electrochemical CO 2 reduction on metal surfaces. Koper’s work also addresses industrial-scale applications, such as optimizing gas bubble detachment during hydrogen evolution and designing bipolar membranes for CO 2 electrolysis. Advisor to over 38 former PhD students, Koper’s teaching spans Electrochemistry (MSc) and Chemical Energy Transition (Minor). He collaborates widely, with projects funded by initiatives like the ANION Gravitation Program and the ELCOREL EU Horizon 2020 Project .

• Catalysis
• Electrochemistry
• Surface Chemistry
• +3 more

Prof. Khalil Sima'an serves as Professor of Computational Linguistics and Vice Director of Education at the Institute for Logic, Language and Computation (ILLC), University of Amsterdam, within the Faculty of Science. He joined as Assistant Professor in 2003, advanced to Associate Professor in 2011, and attained Full Professorship in 2014. His academic foundation includes a PhD in Computational Linguistics from Utrecht University, establishing his expertise in formal language modeling. Prof. Sima'an's research drives innovation in Computational Linguistics through rigorous exploration of syntactic structures, semantic processing, and machine translation systems. His work bridges theoretical frameworks with practical NLP applications, particularly in parsing technologies and multilingual processing, positioning him as a key contributor to European language technology initiatives. His distinguished recognition includes: Royal Netherlands Academy for Arts and Sciences (KNAW) Fellowship NWO Vidi Grant (2006) for pioneering early-career research NWO Vici Grant (2013) for groundbreaking senior research leadership He actively shapes the field through editorial stewardship of Machine Translation and Journal of Natural Language Engineering , alongside pivotal conference roles including MT Summit XIV Chair (2013) and ACL 2010 area chair for syntax/parsing. As core faculty in the Natural Language Processing & Digital Humanities (NLP&DH) research group, he advances collaborative projects integrating computational methods with humanities scholarship at LAB42's interdisciplinary hub.

• Computational Linguistics
• Natural Language Processing
• Machine Translation
• +3 more

Pim de Vink is a doctoral researcher at Eindhoven University of Technology , affiliated with the Biomedical Engineering department and Chemical Biology group. Supervised by dr. L.-G. Milroy and prof. L. Brunsveld , his work bridges supramolecular chemistry and chemical biology , focusing on host/guest chemistry for protein complex modulation. Education: B.Sc. in Chemistry (2014) from University of Amsterdam M.Sc. in Biomedical Engineering (2016) from TU/e Internship at Max Planck Institute for Molecular Physiology (2016) on gold-catalyzed synthesis Research Themes: His research develops switchable cucurbituril-based systems for light-controlled enzyme activation and artificial signaling networks. Key areas include protein-protein interaction stabilization , thermodynamic modeling , and allosteric nuclear receptor modulation . Publication Trends: Across JACS , Chemical Science , and RSC Chemical Biology , his work from 2017–2023 emphasizes supramolecular tools for biochemical applications. Notable contributions include 100-fold affinity enhancement of 14-3-3 ligands and UV-responsive cucurbituril release mechanisms . Grants: Funded by Netherlands Organization for Scientific Research (NWO) through Gravity program 024.001.035 and VICI grant 016.150.366.

• Supramolecular Chemistry
• Chemical Biology
• Protein-Protein Interactions
• +3 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.

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

Andre Berger is an Associate Professor of Operations Research at Maastricht University, affiliated with the QE Operations Research department within the School of Business and Economics. He holds a PhD in Mathematics from Emory University (2006) and completed a postdoc at Technical University Berlin. His research focuses on optimization algorithms, combinatorial optimization, and their applications in scheduling, network design, and operations research. Notable contributions include work on the many-visits Traveling Salesman Problem and cluster editing algorithms. Berger’s recent publications span scheduling theory, MRI-based clinical research collaborations, and theoretical advancements in facility location models. He is based at Tongersestraat 53, Maastricht, and can be reached via a.berger@maastrichtuniversity.nl. Education: MSc in Mathematics, Emory University (2003) PhD in Mathematics, Emory University (2006) Research Interests: Berger’s work bridges theoretical computer science and practical applications in operations research, emphasizing algorithm design for complex optimization problems. Key areas include scheduling algorithms, network flow optimization, and geometric optimization challenges such as the Apollonius problem in facility location. His interdisciplinary approach integrates mathematical programming with real-world scenarios in telecommunications and healthcare.

• Operations Research
• Optimization Algorithms
• Combinatorial Optimization
• +3 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 .

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

Pascal Mettes is a tenured Assistant Professor at the University of Amsterdam within the Informatics Institute, specializing in Artificial Intelligence. He leads groundbreaking research in hyperbolic deep learning, a field he has significantly advanced through theoretical developments and practical applications in computer vision and multimodal learning. His research focuses on three primary domains: hyperbolic vision-language models that address the hierarchical nature of language-vision relationships; hierarchical deep learning using hyperbolic embeddings that naturally accommodate exponential growth patterns; and robust deep learning in hyperbolic space that improves out-of-distribution detection and network resilience. Mettes has established himself as a leading figure in this emerging field through numerous publications at top-tier conferences including CVPR, ICCV, ICML, NeurIPS, and ICLR. His recent work demonstrates how hyperbolic geometry provides natural solutions to fundamental limitations in modern deep learning, particularly regarding hierarchical data structures that cannot be adequately represented in Euclidean space. The publication trends show increasing impact and recognition in the computer vision and machine learning communities, with multiple papers receiving oral presentations and best paper nominations. Best paper nomination ESWC25 for 'Designing Hierarchies for Optimal Hyperbolic Embedding' Finalist MM 2023 Best Open-Source Software Competition (for HypLL) Multiple reviewer awards across major conferences including CVPR, ICLR, ECCV, ICML, and NeurIPS MM 2016 Best Doctoral Student Award TRECVID 2015 Winner Multimedia Event Detection Benchmark Mettes actively mentors eight PhD students working on hyperbolic learning and related topics, while also securing significant research funding including ELLIs PhD Award, NWO ClickNL, Google Perception Academic Funding, and Data Science Centre PhD Grants. He serves in prominent academic roles as Program Chair for International Conference on Multimedia Retrieval 2026 and has organized multiple workshops on hyperbolic learning at major conferences. His leadership in establishing hyperbolic deep learning as a recognized research direction is evident through his survey paper in IJCV 2024 and the development of the HypLL library for hyperbolic learning.

• Hyperbolic Deep Learning
• Computer Vision
• Vision-Language Models
• +3 more

Prof. Dr. Arwen Deuss is a full Professor at the Faculty of Geosciences, Utrecht University , specializing in Seismology . Her research focuses on mapping Earth's deep interior using global seismology, with particular emphasis on mantle discontinuities, core structure, and whole Earth oscillations. She integrates seismological data with mineral physics, geodynamic modeling, and geochemistry to understand planetary evolution. Key research areas: Earth's Deep Interior, Global Seismology, Mantle Discontinuities, Inner Core Anisotropy Teaches courses in Theoretical Seismology, Earth Systems, and Planetary Interior Structure Developed open-source tools like FrosPy for normal mode analysis Her recent work explores 3D mantle attenuation, tilted transverse isotropy in the inner core, and seismic wave coupling. She leads projects connecting seismic tomography with geodynamic processes and maintains active collaborations in international seismological research.

• Global Seismology
• Earth's Deep Interior
• Mantle Discontinuities
• +4 more

Christian Bick is an Associate Professor at the Department of Mathematics, Vrije Universiteit Amsterdam (VU Amsterdam). He holds visiting roles as a Visiting Research Fellow at the University of Oxford's Mathematical Institute, Honorary Associate Professor at the University of Exeter, and Visiting Fellow at the Institute for Advanced Study (TUM-IAS), Technische Universität München. His research focuses on dynamical systems and applications, particularly in network dynamics, coupled oscillator networks, and higher-order interactions. He has received prestigious awards such as the Marie Curie Intra-European Fellowship (2015) and the Hans Fischer Fellowship (2019). Education and Career: Bick obtained his PhD from Georg-August-Universität Göttingen (2012) and held postdoctoral positions at Rice University and the University of Exeter. His work bridges theoretical and applied mathematics, with interdisciplinary collaborations in neuroscience, physics, and engineering. Research Interests: Bick explores dynamics of coupled oscillator networks, asynchronous networks, and higher-order interactions. His recent work includes studies on heteroclinic networks, chimera states, and synchronization phenomena in complex systems. He leads projects like BeyondTheEdge (Marie Skłodowska–Curie Doctoral Network) and has contributed to grants such as the EPSRC New Investigator Award (2020–2023). Teaching: He teaches Dynamical Systems at VU Amsterdam and has lectured on Stochastic Processes, Mathematical Methods, and Dynamical Systems and Chaos at the University of Exeter and Oxford. Awards and Grants: His honors include the DAAD Doktorandenstipendien (2010, 2012) and Fulbright support (2008). Active grants include projects on higher-order networks and neurodegenerative disease modeling.

• Dynamical Systems
• Coupled Oscillator Networks
• Network Dynamics
• +3 more

Dr. Eiko Fried is an Associate Professor at Leiden University's Faculty of Social and Behavioural Sciences, where he works at the intersection of clinical psychology, psychiatry, epidemiology, methodology, and complexity science. His research focuses on improving psychological science through open science practices and innovative measurement approaches. PhD in clinical psychology, Free University of Berlin Postdoctoral training at KU Leuven and University of Amsterdam Promoted to Associate Professor at Leiden University in 2021 Key research areas include: Psychopathology measurement and classification Network analysis in mental health research Ecological momentary assessment (EMA) methodology Open science advocacy and implementation Dynamic systems modeling in psychology Transdiagnostic approaches to mental disorders Recent publications demonstrate expertise in: Symptom network analysis across disorders Improving depression measurement standards Transdiagnostic assessment protocols Mental health data integration challenges Psychological theory construction Methodological innovations in clinical research

• Clinical psychology
• Psychiatry
• Epidemiology
• +6 more