Find Academic Supervisors

• 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.

Sascha van SchendelView profile

Assistant Professor

• Data Protection Law
• Privacy Law
• Cybersecurity
• +12 more

Sascha van Schendel is an Assistant Professor in Data Protection & Cybersecurity at the Department of Law & Markets, Erasmus School of Law, Erasmus University Rotterdam. She is affiliated with the Erasmus Centre of Law and Digitalization and contributes to the Sectorplan SSH-Breed research initiative on the influence of digitalization on work, prosperity, and entrepreneurship. Her research lies at the intersection of law, technology, and fundamental rights, with a focus on data protection, privacy, algorithmic governance, and the regulation of emerging technologies in public and environmental domains. She has published widely on topics including GDPR compliance, privacy by design, smart energy systems, AI in criminal justice, and the legal implications of predictive policing. The recent publications reflect a strong trend toward the regulation of data in public infrastructure (e.g., energy grids), algorithmic accountability in law enforcement, and the integration of legal and technical perspectives in privacy-preserving systems. Her work spans environmental law, criminal procedure, and digital constitutionalism, demonstrating interdisciplinary reach. Scientific Awards: No awards explicitly mentioned in the provided text. Advising and Grants: While no formal PhD or Master’s students are listed, Dr. van Schendel has been involved in significant research projects such as the NWO-funded Megamind project on smart energy grids, indicating experience with competitive grant funding. She actively collaborates with legal scholars and contributes to public policy debates, including responses to national legislation like the Dutch Cybersecurity Bill. Labs and Teams: She is a core member of the Erasmus Centre of Law and Digitalization, a research hub focusing on the legal challenges of digital transformation. Her work is embedded in interdisciplinary collaborations involving law, technology, and public policy experts.

• Process Mining
• Healthcare Informatics
• Data Security
• +3 more

Dr. Jeewanie Jayasinghe Arachchige is a Lecturer in the Department of Computer Science at Vrije Universiteit Amsterdam, Faculty of Science. She teaches undergraduate courses including Bachelor Project Computer Science, Professional Development, and Software Engineering Processes for the academic year 2024–2025. Her research focuses on process mining , healthcare informatics , and data security . She applies process mining to analyze healthcare pathways and subpopulation treatment variations, develops explainable AI frameworks for predictive analytics, and examines data governance in emerging architectures like Data Lakehouses. Her work intersects legal informatics, particularly formalizing Sri Lankan civil court processes using ontology engineering. Recent publications highlight trends in balancing simplicity and complexity in process modeling, Industry 4.0 healthcare applications, and cybersecurity in model-driven web development. She has contributed to over 20 peer-reviewed articles since 2006, spanning topics from service-oriented architectures to value network analysis. Her teaching and research emphasize practical applications of IT in healthcare, legal systems, and enterprise environments. No ancillary activities are currently recorded.

• User-Generated Content Analysis
• Generative AI in Healthcare
• Online Platforms and Decision Making
• +3 more

Dr. Dicle Yagmur Ozdemir is an Assistant Professor of Business Information Management at the Rotterdam School of Management (RSM), Erasmus University. She joined RSM in September 2023 after earning a PhD in Management Science (Information Systems concentration) from the University of Texas at Dallas, a Master's in Industrial Engineering from Sabanci University, and a Bachelor's in Industrial Engineering from Istanbul Technical University. Her research focuses on user-generated content dynamics in online platforms and the application of generative AI in healthcare. She employs econometric modeling and natural language processing to study how novel information in reviews influences stakeholders' decisions, and designs algorithms to mitigate information overload. In healthcare AI, she experiments with generative AI's impact on patient-provider interactions. Her work has been presented at top conferences including CIST, WITS, ICIS, WCBA, and INFORMS. Key themes in her research include algorithmic fairness in content selection, the psychological effects of AI-driven health advice, and the mediation effects of review novelty on consumer behavior. She has collaborated internationally, with research outputs including 6 works since 2023. Notable contributions address the moderating role of review dissimilarity in credibility assessments and the paradoxical effects of positive/negative review valence in decision contexts.

Jampel Dell'AngeloView profile

Associate Professor

• Water Governance
• Political Economy of Natural Resources
• Climate Change Adaptation
• +3 more

Jampel Dell'Angelo is an Associate Professor with ius promovendi in Water Governance and Politics at the Department of Environmental Policy Analysis, Institute for Environmental Studies (IVM), Vrije Universiteit Amsterdam. He holds concurrent roles as a Visiting Scholar at the University of California, Berkeley's Ecohydrology Lab, and an Environmental Governance Affiliate Scholar at SESYNC, Maryland. His research focuses on multilevel dimensions of water governance, climate adaptation in African irrigation systems, and transnational land investments' impacts. He leads the EU-funded NEWAVE project, coordinating 15 Early Stage Researchers across 10 institutions. Educated with a dual PhD in Environmental Science (Autonomous University of Barcelona) and International Cooperation (Sapienza University), he also holds advanced degrees from the LSE, Sapienza, Curtin, and the University of Siena. As Editor-in-Chief of World Development , he promotes interdisciplinary research on socio-environmental systems. His work contributes to UN SDGs related to clean water, sustainable cities, and responsible production. Research interests span water grabbing dynamics, socio-ecological resilience, and policy frameworks for equitable resource management. Recent projects address Mediterranean water scarcity solutions and the socio-political implications of global land rushes. He supervises PhD candidates exploring themes like water democracy, agrifood transitions, and environmental justice. Key contributions include pioneering analysis of 'water commons grabbing' and documenting the Global Water Grab Syndrome. His documentary work complements field research, such as Working Together: Research and Water Governance on Mount Kenya . Current projects emphasize innovative governance models and climate-resilient water management in transboundary contexts.

• 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.

J.D. JansenView profile

Professor

• Systems and Control Theory
• Subsurface Flow Mechanics
• Geothermal Energy
• +4 more

J.D. Jansen is a full Professor at Delft University of Technology (TU Delft) in the School of Civil Engineering & Geosciences, specializing in the Reservoir Engineering department. His research focuses on systems and control theory applied to subsurface flow mechanics, with applications in oil and gas production, geothermal energy, and induced seismicity. He actively contributes to academic networks through editorial roles, keynote presentations, and international collaborations. Active in computational geosciences (modeling, simulation, data analysis) Member of the Dutch Mining Council since 2016 Recipient of two Society of Petroleum Engineers awards in 2018 His work emphasizes optimization of subsurface processes, numerical modeling of porous materials, and seismicity mitigation. Recent publications highlight fault slip mechanics, benchmarking simulations, and stress pattern analysis in geothermal systems. Collaborations span geomechanics, reservoir engineering, and data assimilation domains. Scientific awards include: Distinguished Membership of the Society of Petroleum Engineers (2018) SPE Distinguished Achievement Award for Petroleum Engineering Faculty (2018) He leads research initiatives in induced seismicity, particularly in the Groningen Field, and contributes to model-based production optimization. Media engagements since 2020 demonstrate public outreach in energy transition topics.

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.

Jacob KrügerView profile

Assistant Professor

• Software Engineering
• Software Evolution
• Variant-Rich Systems
• +5 more

Jacob Krüger is an Assistant Professor at Eindhoven University of Technology , specializing in the development and evolution of variant-rich software systems. He holds a PhD from Otto-von-Guericke University Magdeburg (2021) and has held academic and research positions at institutions including Ruhr-University Bochum, Chalmers University of Technology, and the University of Toronto. His research focuses on the interplay between human cognition and software quality, particularly in complex systems requiring frequent adaptation. Education: PhD in Computer Science, Otto-von-Guericke University Magdeburg (2021) MSc Business Informatics, Otto-von-Guericke University Magdeburg (2016) Research Interests: Variant-Rich Systems Program Comprehension Software Product Lines Human Factors in Software Engineering Architecture Smells and Quality Assurance Articles Trends: Recent work emphasizes fork ecosystem visualization (VisFork tool), the impact of AI on scientific practices, and crisis-driven software development (e.g., Corona-Warn-App). Key themes include empirical studies, tool development, and industry collaboration. Awards: Best Dissertation Award (2022) Frank Anger Memorial Award (2019) Multiple conference best-paper and review awards Advising & Grants: Supervises 12+ PhD students across multiple institutions. Active in funding projects like INKleSS (German Research Foundation) and FOSD Meeting 2024 (NWO). Leads collaborations with ASML, Danfoss, and Axis AB. Labs/Teams: Member of the Software Engineering and Technology (SET) group at TU Eindhoven, focusing on industrial-strength software systems and cognitive aspects of development.

Mykola PechenizkiyView profile

Professor

• Data Science
• Machine Learning
• Predictive Analytics
• +5 more

Mykola Pechenizkiy is a Full Professor at the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e), holding the Data Mining Chair. He also serves as an Adjunct Professor in Data Mining for Industrial Applications at the University of Jyväskylä. His research focuses on predictive analytics, data mining, and responsible AI, addressing real-world challenges in industry, healthcare, and education. He leads the Customer Journey research program at the Data Science Center Eindhoven, emphasizing ethical and transparent analytics. Academically, he holds a PhD from the University of Jyväskylä (2005) and has held visiting researcher positions at institutions like Columbia University and NYU. He has co-authored over 300 peer-reviewed publications and serves on editorial boards and committees for leading conferences (e.g., AAAI, IJCAI). He is the President of the International Educational Data Mining Society (IEDMS). His research interests include concept drift adaptation, sparsity techniques in neural networks, and fairness-aware AI. He has led projects such as the TKI PPS KPN Smart Two initiative and collaborates with industries like ASML, Philips, and Rabobank. His work contributes to UN SDGs, particularly in sustainable development through AI-driven solutions. Awards: Best Demo Paper Award (IEEE ICDE 2023), Best Paper Awards (ALA 2022, LoG 2022), and SensorKDD 2009 recognition. Grants/Projects: Active projects include TKI PPS KPN Smart Two (2019–2025) and Smart One W&I TKI KPN Flagship (2018–2022). Labs/Teams: Affiliated with EAISI Health, SIKS Scientific Board, and the University of Waikato’s AI Institute.

Laura MarusterView profile

Assistant Professor

• Process Mining
• Process Modelling
• Healthcare Networks
• +5 more

Laura Maruster is an Assistant Professor at the Faculty of Economics and Business, University of Groningen, Netherlands. She holds an MSc from the West University of Timisoara, Romania, and a PhD in Technology Management from Eindhoven University of Technology, Netherlands. Her research focuses on process mining, process modelling, and healthcare networks, with applications in operations research and data science. She collaborates extensively with industry and public sector partners on projects like the Casimir initiative (RuG and Gasunie). Teaching areas include business processes, data mining, and research methodology. Recent work includes studies on healthcare logistics optimization and process mining beyond traditional workflows. Her publications appear in leading journals such as BMJ Open , IEEE Transactions on Engineering Management , and Computers in Industry . Research interests span healthcare networks, emergency medical services analytics, and enterprise process optimization. Notable recent contributions include analyzing interhospital patient transfers and redesigning engineering design processes using data-driven methods.

Syeda Amna SohailView profile

Lecturer

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

Guy G. DrijkoningenView profile

Associate Professor

• Applied Geophysics
• Seismic Experiments & Modelling
• Seismic Data Acquisition
• +3 more

Guy G. Drijkoningen is an Associate Professor in Applied Geophysics at Delft University of Technology (TU Delft), Faculty of Civil Engineering and Geosciences. He is actively involved in teaching and research within the Department of Applied Geophysics & Petrophysics. Education: MSc, Delft University of Technology, The Netherlands PhD, Cambridge University, UK Research Focus: His work centers on Seismic Experiments & Modelling , particularly in exploration and shallow-subsurface contexts. Key areas include: Seismic data acquisition on land Continuous seismic monitoring Shallow shear-wave imaging (land and marine) Seismic wave propagation in porous media Current projects leverage advanced sensor networks (e.g., LOFAR), full-waveform inversion for tunnel-boring machines, and novel vibrator technologies. Publications Trend: Recent works (2011–2016) emphasize seismic modeling, inversion techniques, and experimental validation across marine and terrestrial environments. Topics span poroelastic wave theory, ambient-noise interferometry, and innovative seismic source design, reflecting a blend of theoretical and applied geophysics. Scientific Awards: Best-paper award Geophysics 2015 for "A seismic vertical vibrator driven by linear synchronous motors" Professional Memberships & Editorial Roles: Member: Society of Exploration Geophysicists (SEG) Member: European Association of Geoscientists and Engineers (EAGE) Associate Editor: Geophysics Teaching: He teaches undergraduate and graduate courses including Introduction to Geophysics, Reflection Seismology, and specialized PhD-level modules on seismic data analysis.

Hans HeesterbeekView profile

Professor

• Infectious Diseases
• Theoretical Epidemiology
• Mathematical Modelling
• +3 more

Prof. Dr. ir. Hans Heesterbeek is a full Professor of Theoretical Epidemiology at Utrecht University's Faculty of Veterinary Medicine. He holds a dual appointment in the Department of Farm Animal Health within the Population Health Sciences sector. His research focuses on the dynamics of infectious diseases at the intersection of biology, medicine, and mathematics, with emphasis on wildlife epidemiology and complex systems. He chairs Utrecht University's Committee for Research Integrity and has held leadership roles in departments like Animals in Science and Society. Education: MSc Phytopathology (Wageningen University, 1986), MSc Mathematics (University of Amsterdam, 1988), PhD in Mathematical Biology from Leiden University (1992) Affiliations: Editor-in-Chief of Epidemics journal, Senior Editor at Proceedings of the Royal Society B , Chair of ZonMw's Open Competition grant program Research interests include: Mathematical modeling of disease spread Ecological epidemiology of zoonotic pathogens Role of wildlife in disease transmission Historical analysis of epidemic understanding Key contributions: Co-developer of the R₀ reproduction number framework, foundational to global epidemiological modeling. Active in interdisciplinary work linking theoretical ecology to societal systems. Currently writing a book on the history of epidemic science. Grants: Vici laureate (€1.3M, 2005-2010). Organizes biannual Epidemics conferences. Advises on public health policy during outbreaks like the 2020 COVID-19 pandemic.

• Software Engineering
• Technical Debt Management
• Software Architecture
• +3 more

Paris Avgeriou is a Professor of Software Engineering at the University of Groningen, affiliated with the Faculty of Science and Engineering and the Bernoulli Institute. He leads the Software Engineering and Architecture research group and serves as Editor-in-Chief of the Journal of Systems and Software . His expertise spans technical debt management, software architecture, self-adaptive systems, and embedded systems design. Avgeriou holds an office at Nijenborgh 9, Groningen, and actively advises academic institutions and funding bodies globally. Research Interests: Avgeriou's work focuses on advancing software architecture principles, technical debt lifecycle management, and the integration of AI in software engineering. His research emphasizes practical solutions for improving software quality, maintainability, and system dependability, particularly in embedded and self-adaptive contexts. Recent Contributions: Recent studies include frameworks for benefit-cost-risk decision-making in self-adaptive systems, automated technical debt management using ML, and tools for tracing architecture-related debt. He collaborates internationally, contributing to standards like the Copenhagen Manifesto for human-centered AI in software engineering. Grants & Awards: While no specific awards are listed, his editorial role and frequent conference contributions reflect recognition in the field. He chairs conference tracks and oversees workshops, fostering early-career researchers and artifact evaluation. Labs & Teams: His group is part of the Bernoulli Institute, working on platforms like SDK4ED for embedded systems and tools such as DebtViz for technical debt monitoring. The team explores intersections between systems engineering and software architecture in complex systems-of-systems.