Find Academic Supervisors

• Extreme Ultraviolet Optics
• Laser Physics
• Plasma Spectroscopy
• +3 more

Muharrem Bayraktar is an Assistant Professor at the MESA+ Institute for Nanotechnology at the University of Twente, specializing in XUV Optics. His research focuses on extreme ultraviolet (EUV) optics, plasma spectroscopy, and adaptive optical systems. He leads projects involving EUV source metrology, piezoelectric thin film actuators, and laser-driven plasma diagnostics. Research Interests: Bayraktar’s work centers on developing advanced EUV light sources for nanolithography applications. He investigates plasma physics in tin-based EUV emitters, optimizing thin film materials for adaptive optics, and improving spectral characterization techniques. His group explores piezoelectric thin films for precision wafer tables and multilayer mirror systems to enhance EUV beam control. Awards: 3rd Place in Simon Stevin Fellow Contest (2016) Best poster award (2018) Best poster award (2019) Advising & Activities: Supervises research on EUV source development and piezoelectric actuators. Engages in international collaborations on plasma diagnostics and adaptive optics. Active in presenting at conferences on topics like ‘EUV Source Metrology’ and ‘Nanolithography Systems’. Labs/Teams: Leads the XUV Optics team within MESA+, collaborating with industry partners on EUV lithography systems and advanced optical components.

• Cybersecurity
• Data Encryption
• Access Control Systems
• +3 more

Willem Jonker is a Full Professor at the Digital Society Institute, specializing in Semantics, Cybersecurity & Services. His research focuses on encryption schemes, access control, and privacy-preserving technologies. He has contributed to over 120 publications, with recent work addressing CVE-to-CWE mapping, anomaly detection in network traffic, and functional encryption systems. His expertise aligns with UN Sustainable Development Goals related to secure digital systems and privacy. Jonker has supervised 10 students and actively participates in academic conferences, presenting on topics like secure data management and cryptographic protocols. Research interests include cryptographic protocols, secure data management, and cybersecurity solutions. Notable projects involve developing methods for detecting covert channels, enhancing data privacy in healthcare, and improving secure search over encrypted data. He has also contributed to standards in digital rights management and forensic image recognition.

Ilke CanakciView profile

Assistant Professor

• Cluster Algebras
• Combinatorics
• Algebra
• +3 more

Dr. Ilke Canakci is an Assistant Professor in the Department of Mathematics at Vrije Universiteit Amsterdam. She specializes in cluster algebras, combinatorics, and representation theory. Her research focuses on algebraic structures like perfect matchings, derived categories, and triangulations. She teaches Discrete Mathematics, Group Theory, and Linear Algebra courses. Key collaborators include researchers from institutions worldwide. Her recent work explores cluster categories for infinity-gons and infinite friezes related to annulus triangulations. Awards and grants are not explicitly mentioned, but her extensive publication record reflects active research in algebraic geometry and combinatorial mathematics. Research Interests: Cluster algebras, categorification of geometric structures, combinatorial patterns, representation theory of algebras, and applications of algebraic methods to geometric problems. Current projects involve extending Caldero-Chapoton maps and analyzing frieze patterns in non-traditional geometries.

Ellen PeetersView profile

Associate Professor

• Health & Education
• Management & Organisation
• Quantitative Methods
• +4 more

Dr. Ellen Peeters is an Associate Professor at the TIAS School for Business and Society , where she has served as Academic Director of the Pre-Master program since January 2022. She obtained her education in work and organizational psychology from: Ghent University (Belgium) KU Leuven (Belgium) - Ph.D. (2016) Her research integrates individual and organizational perspectives, with core themes including: Health & Education : Workforce well-being in healthcare settings. Management & Organisation : Change Management and HRM implementation Organizational Behavior and Development Leadership and Strategic Management Quantitative Methods : Business research methodologies. Cross-cutting focus on Corporate Social Responsibility , Sustainable Careers , Employability , and Resilience during organizational transitions. Her publications demonstrate consistent emphasis on career dynamics, HRM practices, and organizational justice, using mixed methods across healthcare, entrepreneurship, and industrial contexts. Recent work highlights resilience in career shocks, nursing self-scheduling impacts, and social capital in supply chains. She holds key academic roles: Editorial Board Member: Journal of Career Development Committee Representative: Society for Industrial and Organizational Psychology (Disability, Inclusion, Accessibility & Visibility)

Maarten GoosView profile

Professor

• Labor Economics
• Technological Change
• Economic Inequality
• +7 more

Maarten Goos is a Full Professor of Economics and Institutions at Utrecht University's Faculty of Law, Economics and Governance. He previously held positions at Erasmus University Rotterdam, University College London, KU Leuven, and had visiting roles at Princeton University, MIT, Boston University, and Fudan University. His research focuses on labor markets, technological progress, wage inequality, and institutional impacts. He is also an award-winning teacher, specializing in European macroeconomics, economic growth, and labor economics. Education: He earned his PhD from the London School of Economics (LSE). His academic journey includes roles at multiple prestigious institutions, reflecting deep expertise in labor and technological economics. Research interests include the interplay between technology and labor markets, specifically automation's effects on employment, wage polarization, and the role of institutions in shaping labor dynamics. He examines how skill-biased technological changes and globalization influence job structures and income distribution. His work also addresses the declining labor share in economies, exploring explanations rooted in firm behavior and productivity shifts. He collaborates with the European Commission, national policy institutes, and multinational corporations, contributing to policy initiatives and economic analyses. His research bridges theoretical models with empirical evidence, offering frameworks like the canonical CES model and task-based automation theories to dissect labor market trends. Though no specific awards are listed, his work is noted as award-winning in international publications. Advising/Grants: Goos has advised various organizations and contributed to policy projects, though formal advisee names or grant details are not explicitly stated. His teaching and research emphasize practical implications of economic theories for real-world labor market challenges and institutional reforms. Labs/Teams: Collaborates within Utrecht University's School of Economics and with external networks through European Commission projects and corporate partnerships.

Nadine KetelView profile

Associate Professor

• Labor Economics
• Educational Economics
• Economics of Crime
• +3 more

Dr. Nadine Ketel is an Associate Professor in Economics at Vrije Universiteit Amsterdam and Research Affiliate at Gothenburg University, IZA, and CEPR's Labour Economics Programme. She holds a PhD in Empirical Studies in Labor and Education Economics from the University of Amsterdam (2016). Her research focuses on labor economics, educational economics, and the economics of crime, primarily using natural and field experiments. Education: PhD in Economics, University of Amsterdam (2011-2015) MSc in Economics, University of Amsterdam (not explicitly dated) Research Interests: Dr. Ketel examines how educational policies, labor market dynamics, and crime victimization interplay. Her work employs experimental methods to evaluate policy impacts, such as admission policies' effects on educational equity and criminal victimization's socioeconomic consequences. Recent studies include spillover effects in educational choices and age-related victimization profiles. Grants & Awards: NWO Veni Grant (2024-2027): €280,000 for education admission policy research Vetenskapsrådet Grant (2018-2020): SEK 4.8M for crime victimization study Joop Hartog Thesis Award (2018) and Best Master's Thesis Award (2009) H. Gregg Lewis Prize (2024) for Journal of Labor Economics paper Teaching & Projects: Teaches Empirical Economics and Introduction to Econometrics. Leads the NWO-VENI project on educational equality and collaborates on NWO-VICI initiatives improving human capital allocation. Active in policy-oriented research, including welfare-to-work experiments and healthcare market analysis. Labs & Teams: Affiliated with Tinbergen Institute and contributes to interdisciplinary collaborations in labor and education economics. Engages with policy institutions like IZA and CEPR to translate research into practical solutions.

Viktor VenhorstView profile

Associate Professor

• Demography
• Migration
• Labour Market Dynamics
• +4 more

Dr. Viktor Venhorst is an Associate Professor at the Faculty of Spatial Sciences, University of Groningen, specializing in demography, regional economics, and labour market dynamics. He holds dual expertise in Demography (MSc, Cum Laude) and Microeconomics (MSc), with a PhD in Spatial Sciences (Cum Laude, 2012). His research focuses on migration patterns, graduate labour market outcomes, and the interplay between education institutions and regional economies. Key roles include leading the StudentLines Centre for Educational Data and Research, serving as a Fellow at Maastricht University’s Research Centre for Education and the Labour Market (ROA), and co-editing volumes on interregional migration. His work has influenced Dutch policy, notably regarding medical specialist distribution and urban-rural linkages. Notable awards include the Gratama Science Award (2013) and the 2017 Faculty Teacher of the Year. He currently oversees six PhD students researching migration, financial decision-making in Indonesia, and urban development histories. His teaching spans statistics, regional labour market analysis, and population projections.

Andrew MillerView profile

Researcher

• Gravitational Waves
• Dark Matter Detection
• Primordial Black Holes
• +2 more

Dr. Andrew L. Miller is a postdoctoral researcher at Utrecht University and the National Institute for Subatomic Physics (Nikhef), focusing on gravitational wave detection and dark matter studies. His work bridges theoretical physics and computational methods within the LIGO/Virgo collaborations. PhD from Sapienza University of Rome and University of Florida MS in Physics from University of Florida BS in Physics from The College of New Jersey Andrew's research centers on gravitational waves from neutron stars , primordial black holes , and dark matter interactions . His methodological innovations include: Machine learning algorithms for detector noise classification Pattern-recognition techniques for continuous wave detection Semicoherent analysis for ultralight boson clouds Frequency-Hough transforms for binary inspirals His publications cover LIGO/Virgo data analysis, Einstein Telescope design, and LISA Pathfinder applications for dark matter detection. He has delivered tutorials on: Machine learning classification Parameter estimation in gravitational waves Frequency-Hough transforms Generalized search frameworks

• Computational Musicology
• Computational Humanities
• Music Information Retrieval
• +5 more

Peter van Kranenburg is an Assistant Professor in Music Information Computing at Utrecht University (The Netherlands) and a guest researcher at the KNAW Meertens Institute in Amsterdam. His work bridges computer science and musicology with a focus on computational approaches to music analysis. His research spans computational musicology, computational humanities, and music information retrieval. Van Kranenburg specializes in developing computational models for analyzing musical structures, particularly melodic similarity measures, folk song transmission patterns, and large-scale analysis of song traditions. His work often involves interdisciplinary collaboration between computer scientists and musicologists. His recent publications demonstrate consistent research in computational approaches to music analysis, with a focus on melodic similarity, folk song transmission, and computational modeling of musical traditions. His work spans both technical computer science aspects of music information retrieval and substantive musicological applications. Van Kranenburg has been involved in several significant research projects including the H2020 Polifonia-project (2021-2024), which focused on large scale analysis of European song traditions and curation of historic data on musical instruments, particularly pipe organs. His educational background combines technical and musicological expertise, having earned master's degrees in both Electrical Engineering (Delft University of Technology, 2003) and Musicology (Utrecht University, 2004), followed by a PhD from Utrecht University. His doctoral research developed melodic similarity measures and software tools for analysis of audio recordings of religious chant.

• Cognitive Neuroscience
• Working Memory
• Temporal Integration
• +4 more

Elkan Akyürek is a Professor of Cognitive Neuroscience and Chair of the Department of Experimental Psychology at the University of Groningen. He leads a research group focused on understanding the neural mechanisms underlying working memory, temporal integration, and attention. His work employs EEG, behavioral experiments, and computational modeling to explore how sensory information is integrated, maintained, and processed in the brain. He has been instrumental in advancing methodologies like impulse perturbation and concealed information testing, with applications in cognitive neuroscience and forensic psychology. Research interests center on cognitive neuroscience, particularly in the domains of working memory maintenance, temporal processing, and the neural correlates of conscious awareness. He investigates how attention modulates perception and memory, with a focus on adaptive mechanisms in visual and auditory systems. His lab also explores the effects of nutritional interventions (e.g., cocoa flavanols) on cognitive performance. Recent research highlights include studies on concealed information detection using EEG and eye-tracking, adaptive forgetting dynamics in working memory, and the neural basis of temporal integration. His work has been published in high-impact journals like *Nature Neuroscience*, *Psychological Review*, and *NeuroImage*, and he has secured grants from the Dutch Science Foundation (NWO) and the Police and Science program. Dr. Akyürek has supervised numerous PhD students and postdocs, fostering collaborations with institutions globally. He is actively involved in science outreach, including educational initiatives to demystify cognitive neuroscience for secondary students. His lab’s interdisciplinary approach integrates psychology, neuroscience, and computational modeling to address fundamental questions about human cognition.

Nikolay YakovetsView profile

Assistant Professor

• Databases
• Data Intensive Systems
• Graph Databases
• +3 more

Nikolay Yakovets is an Assistant Professor at the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e). His research focuses on databases and data-intensive systems with specialization in graph data management, query processing optimization, and high-performance data engineering. He leads academic courses including Data Modeling, Database Technology, and Engineering Data-Intensive Systems. Education background includes: PhD in Computer Science from York University (2017) MSc and BSc in Computer Science from York University Research expertise spans: Foundational database technologies Graph query optimization algorithms Cardinality estimation methods Knowledge graph construction High-performance data processing architectures Publication trends show consistent focus on graph database systems, with recent works advancing property graph management, cardinality estimation techniques, and ontology-driven knowledge graphs. Research demonstrates strong emphasis on practical system efficiency and theoretical foundations. Active in student supervision with 41 supervised works recorded. No awards mentioned in source materials.

• Data Stream Mining
• Data Cleaning
• Machine Learning Explainability
• +7 more

Dr. A.A.A. Qahtan is an Assistant Professor in the Data Intensive Systems research group within the Department of Information and Computing Sciences at Utrecht University's Faculty of Science. His academic appointment focuses on advancing research and education in data-intensive computing with particular expertise in data stream mining, data cleaning, and explainability of machine learning techniques. Dr. Qahtan completed his PhD studies at KAUST (King Abdullah University of Science and Technology) under the supervision of Xiangliang Zhang and Soujin Wang. Prior to joining Utrecht University, he worked as a postdoc at QCRI (Qatar Computing Research Institute) where he developed pattern functional dependencies (PFDs) for data cleaning. His research spans several critical areas in data science: Data Stream Mining and Real-time Processing Data Cleaning and Quality Assessment Pattern Recognition and Functional Dependencies Outlier and Anomaly Detection Concept Drift Detection in Streaming Data Fairness in Machine Learning Systems Missing Data Imputation Techniques Dr. Qahtan's publication record demonstrates consistent contributions to top-tier venues including PVLDB, KDD, ICDE, and SIGMOD. His recent work shows a progression from foundational data cleaning techniques to advanced applications in categorical data analysis, fairness in AI, and cryptocurrency market analysis. His research bridges theoretical foundations with practical applications across multiple domains. Dr. Qahtan actively contributes to academic education at Utrecht University, teaching courses including Data Analytics, Data Science and Society, Data Wrangling and Data Analysis, and Databases across multiple academic years from 2019 to 2024.

Paul MullerView profile

Associate Professor

• Labor Economics
• Job Search
• Program Evaluation
• +5 more

Paul Muller is an Associate Professor at the Department of Economics, Vrije Universiteit Amsterdam, and a research fellow at the Tinbergen Institute. He previously held an Assistant Professor position at the University of Gothenburg and earned his PhD from Vrije Universiteit Amsterdam in 2016. His research focuses on empirical labor economics, particularly job seeker-employer matching, labor market policies (disability, childcare, migration), and the evaluation of job search assistance programs. He received an NWO-Vidi grant (2024) for studying labor market scarcity in the Netherlands. Education: PhD in Economics, Vrije Universiteit Amsterdam (2016). Research Interests: Job search behavior and strategies Experimental and quasi-experimental evaluation methods Disability insurance and labor supply disincentives Automated labor market information tools Childcare policy impacts on labor participation Recent Research Trends: Focus on behavioral economics in job search decisions Analysis of policy instruments using RCTs and natural experiments Investigation of wage announcement effects on labor market dynamics Awards: NWO-Vidi Grant (2024) Advising & Grants: Supervised 1 PhD thesis (van der Meijden, M.) Principal Investigator for NWO-VIDI project on labor market scarcity Contributed to NWO-VICI project on efficient labor-school allocation Labs/Teams: Active collaboration through the Tinbergen Institute and VU Amsterdam's economics department.

Bas van der KlaauwView profile

Professor

• Empirical Microeconomics
• Public Policy Evaluation
• Labor Markets
• +3 more

Prof. Bas van der Klaauw is a Full Professor of Policy Evaluation at Vrije Universiteit Amsterdam's School of Business and Economics and Director of the Tinbergen Institute, a joint research school with Erasmus University Rotterdam and University of Amsterdam. He holds an Economics PhD from VU Amsterdam and has held visiting roles at University of Pennsylvania and Johns Hopkins University. His research focuses on empirical microeconomics, public policy evaluation, labor markets, school choice, and intergenerational mobility, leveraging microeconometric methods for causal analysis. He has received prestigious grants including an ERC Starting Grant (2008) and NWO-VICI Grant (2016). Teaching includes Econometrics II and Applied Microeconometrics at the Tinbergen Institute, alongside undergraduate courses in Microeconomics and Mathematical Economics. Ancillary roles include advisory positions at Centraal Bureau voor de Statistiek, SEO Amsterdam Economics, and Rabobank. He co-leads projects on school allocation efficiency and labor market interventions, collaborating with institutions like IZA-Bonn and CEPR-London. His research output spans 129 publications, emphasizing policy evaluation and experimental methods. Notable works include analyses of school assignment mechanisms, medical education returns, and labor market speeddating experiments. He has supervised 11 PhD theses and contributed to policy debates via media commentary on school segregation, tuition fees, and job search policies. Key achievements include grants totaling €4M+, editorial roles at journals like the Journal of Applied Econometrics, and media outreach addressing societal impacts of education and labor policies. His work aligns with UN SDGs related to quality education and decent work.

Elisabetta PeriView profile

Assistant Professor

• Biomedical Signal Processing
• Electrophysiological Signals
• Non-obtrusive Patient Monitoring
• +3 more

Elisabetta Peri is an Assistant Professor in the Signal Processing Systems group at the Eindhoven University of Technology (TU/e), affiliated with the Biomedical Diagnostics Lab and EAISI Health. Her research focuses on biomedical signal processing for non-obtrusive patient monitoring through electrophysiological signals and sweat sensing. M.Sc. in Biomedical Engineering (2013), Ph.D. in Bioengineering (2017) from Politecnico di Milano Her work spans biomedical signal processing , sweat sensing , sleep staging , and cardiovascular monitoring . She develops algorithms for non-invasive diagnostics in hemodialysis, diabetes, and sleep disorders. Key article trends include: Wearable device integration (2025) Sweat-based biomarker estimation (2024-2025) Transfer learning for sleep disorder detection (2025) Projects include: PISANO (Perioperative Innovations, Sleep Apnea, Newborn Monitoring) SEDAS (Sweat Sensing for Sepsis) PICASSO (Perinatal/Cardiovascular/Sleep Medtech)