Find Academic Supervisors

Prof. Jacco van Ossenbruggen is a Full Professor in Intelligent Information Systems at Vrije Universiteit Amsterdam (VU), affiliated with the Network Institute. He serves on the Management Board of ODISSEI, a national research infrastructure for social sciences and economics. His academic background includes a PhD in Computer Science (2001) from VU’s Faculty of Science, focusing on hypermedia processing. Research Interests: His work centers on cultural AI, FAIR data principles, ontology engineering, and semantic web technologies. Key areas include inclusive cultural heritage metadata, bias mitigation in AI systems, and knowledge discovery via linked data. Recent projects involve leveraging large language models (LLMs) for metadata enrichment and ontology construction. Key Contributions: He leads initiatives like the Cultural AI Lab, exploring AI applications for cultural heritage. His research bridges technical innovations (e.g., semantic integration of restricted-access data) with societal impacts (e.g., ethical AI frameworks for public-sector applications). Developed frameworks for evaluating entity alignment in knowledge graphs Pioneered FAIR-aligned data management plans for scientific communities Designed tools like Alter Heritage for collaborative metadata curation Grants & Projects: Principal Investigator of the ODISSEI Portal project (2020–2024), advancing open data infrastructures. Active in funding initiatives promoting reproducible research and ethical data practices. Labs/Teams: Cultural AI Lab at VU, focusing on AI-driven solutions for cultural heritage preservation and accessibility.

• Cultural Heritage
• Digital Libraries
• Ontology Engineering
• +7 more

Syeda Amna Sohail is an Lecturer at the University of Twente , affiliated with the Public Administration school and the Datamanagement & Biometrics department. Her research focuses on process mining, metadata management, and privacy-preserving techniques in healthcare contexts. She actively contributes to interdisciplinary projects addressing ethical challenges in AI and data governance. Key research interests include: Data privacy in healthcare processes Process mining applications for metadata analysis Ontology-based frameworks for FAIR data principles Ethical AI and surveillance technologies Recent work highlights collaborations with institutions like CAiSE and VMBO workshops. She has presented at conferences such as the 33rd International Conference on Advanced Information Systems Engineering and delivered invited talks on privacy value modeling. Her research has been published in peer-reviewed venues including Lecture Notes in Computer Science and MDPI journals. Professional activities include organizing workshops, contributing to conference proceedings, and participating in multidisciplinary initiatives aligning with UN Sustainable Development Goals. Her work emphasizes practical solutions for balancing privacy and utility in healthcare data systems.

• Process Mining
• Data Privacy
• Metadata Management
• +3 more

Joaquin Vanschoren is an Associate Professor of Machine Learning at Eindhoven University of Technology (TU/e), affiliated with the Faculty of Mathematics and Computer Science. He leads the Automated Machine Learning group and serves as Education Director for the Data Science program. His research focuses on democratizing AI, algorithm selection, and open science platforms like OpenML. He has received awards including the Dutch Data Prize and Amazon Research Award. Education: PhD in Engineering (KU Leuven, Belgium), MSc in Computer Science (KU Leuven). Research visits included IBM, Amazon Research, and universities globally. Research Interests: Machine Learning, Automated ML, Meta-learning, AI Safety, Data-centric AI. He co-founded OpenML and chairs MLCommons' AI Safety working group. Key Projects: NeurIPS Datasets and Benchmarks track, MLCommons initiatives, OpenML platform. Supervised 78 research works and authored 200+ papers. Awards: Dutch Data Prize (2016), Amazon Research Award (2019), Microsoft Azure Research Awards (2016–2017). Labs/Teams: OpenML open source team, MLCommons collaborations, Automated Machine Learning group at TU/e.

• Machine Learning
• Automated Machine Learning
• Algorithm Selection
• +4 more

Dr. Ronald Maria Siebes serves as Assistant Professor at the Faculty of Science, Vrije Universiteit Amsterdam, with affiliations to the Network Institute and Business Web and Media department. His research focuses on knowledge organization systems, semantic web technologies, and FAIR data principles. He leads projects involving interoperability frameworks for restricted data access, IoT-enabled smart buildings, and historical chronicle analysis. Current roles include managing Open Data Infrastructure initiatives and guiding PhD research in data governance. Education details are not explicitly provided in the text. Research interests emphasize ontology engineering, knowledge graph applications, and data management standards. Recent work explores FAIR Implementation Profiles for research data, IoT sensor integration in office environments, and dynamic knowledge graph embeddings. Active in 6 collaborative projects including smart grid integration and historical source analysis. Labs/Teams: Involved in Network Institute initiatives and Open PHACTS Foundation projects. Supervised 2 PhD theses (names not specified in text). Grant activities span €2.1M in EU Horizon and national funding for data infrastructure and knowledge engineering research.

• Linked Data
• Data Management
• Ontology Engineering
• +4 more

Kate Mancey is an Assistant Professor of Music and Media at Utrecht University's Department of Media and Culture Studies , affiliated with the Institute for Cultural Inquiry . Originally from the UK, she holds a BA and MA in Music from the University of Liverpool and a PhD in Music Theory from Harvard University. Research Interests: Her work explores intersections of music, technology, and society, combining computer-aided analysis with traditional musicology. Key projects include analyzing human-technology relationships through everyday sounds (smartphones, appliances), virtual reality music dynamics, and digital humanities datasets like CoSoD for popular music collaborations. Publications Trends: Recent work spans interdisciplinary topics from emergency medicine (music interventions for pain relief) to virtual reality audiovisual analysis and historical sound studies in commerce. Scientific Awards: Kennedy Memorial Trust Fellowship Harry and Majorie Ann Slim Memorial Fellowship Sandra Ohrn Dissertation Fellowship Funding & Collaboration: Supported by multiple fellowships for research in Tokyo, Osaka, and the Smithsonian Institute. Collaborator on projects like Boston Rock City (linked data) and music-related legal consultancy.

• Musicology
• Science and Technology Studies
• Media Studies
• +5 more

Ayushi Rastogi is an Assistant Professor at the University of Groningen, affiliated with the Software Engineering group in the Bernoulli Institute under the Faculty of Science and Engineering. She holds a PhD from IIIT-Delhi and has conducted postdoctoral research at TU Delft and the University of California, Irvine, with additional experience as a visiting researcher at Microsoft Research. Her research focuses on data analytics and AI-driven solutions for software engineering challenges, particularly in open-source ecosystems and developer communities. Key interests include psychological safety in OSS, pull request dynamics, and fairness in software practices. She actively contributes to EDI initiatives through Informatics Europe and the Netherlands' IPN EDI committee. Her work combines empirical software engineering and repository mining to address real-world software challenges. Notable contributions include analyzing fork sustainability in developer communities and exploring code review velocity. She has received the MSR Rich Holt Early Career Achievement Award 2025 and serves as an Associate Editor for IEEE Software. Her GitHub repository 'fsoc' investigates fork impact on developer community sustainability, and she leads projects like OpenDataology for AI dataset compliance. Awards include the 2022 Best Disruptive Paper Award (ISSRE) and supervision of the MSR 2024 Distinguished Doctoral Award-winning thesis by Dr. Gunnar Kudrjavets. She chairs MSR 2025 and frequently presents on topics like gender equality in tech and burnout prevention. Her research spans compiler analysis, memory management, and EDI policy design in ICT sectors.

• Computer Science
• Software Engineering
• Empirical Software Engineering
• +5 more

Prof. Franciska de Jong is a Full Professor of e-Research for the Humanities at Utrecht University's Department of Languages, Literature and Communication, part of the Faculty of Humanities. She previously served as Executive Director of CLARIN ERIC (2015-2022), the European research infrastructure for language resources, and now acts as a Senior Advisor there. Her research focuses on digital libraries, text mining, cross-language retrieval, and cultural heritage preservation. She holds a PhD in theoretical linguistics and has extensive industry experience at Philips Research (1985-1992). She has held leadership roles in national organizations including the Netherlands Organization for Scientific Research (NWO) and the National Library of the Netherlands (KB), and currently chairs the NWO Advisory Committee for Digitalization Research. She is leading the Horizon Europe project EOSC Focus, addressing sustainability of the European Open Science Cloud. Her work spans interdisciplinary collaboration, policy development, and infrastructure governance in digital humanities and computational social sciences. Education: Dutch Language & Literature (Utrecht University), PhD in Theoretical Linguistics. Key Roles: Board member of Netherlands eScience Center (2014–2023), Chair of Lorentz Center's Computational Science Advisory Board (2016–2021), Steering Board member of Open Science-NL (2023–present). Activities: Organized CLARIN Annual Conferences (2016–2019), Digital Humanities conferences, and workshops on parliamentary data analysis.

• Digital Libraries
• Text Mining
• Cross-Language Retrieval
• +3 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.

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

Simon Scheider is an Associate Professor of GIS in the Department of Human Geography and Spatial Planning at Utrecht University, Netherlands. His research focuses on conceptual modeling of geographic data, semantic web technologies, and geospatial analysis. He holds a Ph.D. in Geoinformatics from the University of Münster (2012) and has held postdoctoral roles at UC Santa Barbara, ETH Zurich, and other institutions before joining Utrecht in 2016. He received tenure in 2018 and became Associate Professor in 2024. Key achievements include an ERC Starting Grant (2018) for geographic question-answering research and an ERC Consolidator Grant (2024) for automatic geoQA systems. He leads the NWO-funded Exposome-NL project (since 2020), simulating urban policy impacts on citizen health. Scheider co-organized AGILE 2023 and COSIT 2024, and serves on editorial boards for journals like Applied Ontology and ISPRS International Journal of Geo-Information. Research interests span spatial semantics, geocomputation, and human-centered AI. Recent work addresses validity in spatio-temporal models, extensive/intensive quantities in geographic data, and integrating LLMs with GIS. His teaching includes Advanced GIS, Spatial Data Analysis (ADS), and National GI Minor courses.

• Geographic Information Science
• Data Modelling
• Geocomputation
• +5 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.

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

Pantelis Karapanagiotis is a Postdoctoral Researcher at the Faculty of Economics and Business, University of Groningen. He holds an external position as Research Affiliate at the Leibniz Institute for Financial Research SAFE in Frankfurt, Germany, since July 2021. His research focuses on Mathematical and Computational Economics Econometrics Financial Data Modeling Historical Financial Data Analysis Human-Robot Interoperability Collective Action in Multinational Projects His recent publications span topics including Ontology frameworks for dynamic task allocation Estimation methods for market equilibrium Wage gaps in industrialized nations Historical firm-level financial databases

• Mathematical Economics
• Econometrics
• Computational Economics
• +5 more

Hugo Ledoux is an academic affiliated with the Faculty of Architecture and the Built Environment at Delft University of Technology, specializing in Urban Data Science. His research focuses on 3D geospatial modeling, including CityGML standards, terrain analysis, and automated reconstruction of urban structures. He has contributed to projects like the DeltaDTM coastal terrain model and the cjdb database solution for CityGML. Education: Not explicitly detailed in text, but inferred through academic roles and publications. Research interests emphasize 3D geoinformation systems, remote sensing applications, and urban data science. His work addresses challenges in 3D city models, building reconstruction, and geospatial validation tools like Val3dity. Recent efforts include improving global terrain models using ICESat-2 and GEDI lidar data. Publications span automated building reconstruction workflows, terrain accuracy assessments, and semantic-guided facade modeling. Awards include the Best Presentation at 3DGeoInfo 2020 and the U.V. Helava Award for Best Paper in 2011. Ledoux has supervised 4 academic works and actively participates in conferences, editorial activities, and open-source software development for geospatial applications. Labs/Teams: Involved in TU Delft’s 3D geoinformation research, contributing to tools like 3dfier and CityJSON for 3D data interoperability.

• 3D Geoinformation
• Urban Data Science
• Remote Sensing
• +3 more

Indika Kumara is a Researcher at Tilburg University with expertise in Data Analytics , Data Governance , and Cloud Computing . His work focuses on decentralized data architectures, privacy engineering, and machine learning applications in infrastructure-as-code analysis.

• Data Analytics
• Data Governance
• Cloud Computing
• +7 more

Prof. Abe de Jong is a Professor of Corporate Finance at the University of Groningen's Faculty of Economics and Business and holds a concurrent position as Professor of Finance at Monash University (Australia). His research focuses on corporate finance, financial history, and business history, with particular emphasis on historical institutional impacts, taxation, and capital structure dynamics. He leads major research projects including 'Collateral Damage: The Financial Economics of Slavery' (NWO, 2025-2029) and 'Taking Stock: The Amsterdam Exchange and Dutch Growth' (NWO, 2021-2026). Key research interests include corporate governance evolution, Dutch financial systems, and long-term economic trends. His work bridges historical analysis with contemporary corporate finance challenges, often utilizing archival data to uncover patterns in corporate behavior. Notable publications address topics such as convertible bonds, Nazi-occupied corporate taxation, and asset sale disclosures. He has secured significant grants from the Netherlands Organization for Scientific Research (NWO), focusing on financial metadata creation and colonial economic history. His pedagogical contributions include developing frameworks to integrate historical sensibility into managerial decision-making. Abe de Jong actively collaborates with international institutions and maintains affiliations in both the Netherlands and Australia.

• Corporate Finance
• Financial History
• Business History
• +3 more

Eleanor Hyde is a Researcher at the Department of Genetics, University Medical Center Groningen, University of Groningen. She is actively engaged in cutting-edge research on data infrastructure for biomedical studies, with particular focus on exposome research and data harmonization across international cohorts. Education: PhD in Bioinformatics or related field (inferred from research profile) Prior academic training in epidemiology and data science (inferred from research profile) Dr. Hyde's research spans multiple critical areas in modern biomedical science, with emphasis on developing frameworks for secure data analysis across distributed databases. Her work on the Armadillo server and DataSHIELD platform addresses fundamental challenges in privacy-preserving analytics for sensitive health data. She has made significant contributions to the MINERVA project, which aims to improve metadata standards for observational studies across Europe. Her longitudinal analysis work examines social determinants of health across multiple countries and life stages. Her recent publications demonstrate a strong trend toward developing infrastructure for federated analysis of large-scale epidemiological data, with particular attention to exposome research and mental health trajectories. These works combine advanced computational approaches with population health perspectives to address complex questions in public health. Scientific Recognition: Active contributor to major European research initiatives including LongITools and MINERVA Regular presenter at academic conferences on data harmonization Research cited in multiple high-impact publications Dr. Hyde actively collaborates with researchers across Europe on large-scale epidemiological projects. Her recent presentation on 'Data harmonisation: The WHY and HOW of harmonising data across cohorts' demonstrates her leadership in methodological approaches to cross-cohort research. She participates in multiple international consortia focused on improving data infrastructure for public health research, with particular emphasis on exposome studies and mental health trajectories across the life course. Her work bridges technical data science challenges with substantive public health questions, making her a valuable collaborator in interdisciplinary research teams.

• Exposome Research
• Data Discoverability
• Federated Analysis
• +5 more