Find Academic Supervisors

• Language Learning and Teaching
• Observational Research
• Educational Research
• +7 more

Dr. Nienke Smit is an Assistant Professor in the Department of Education at Utrecht University's Faculty of Social and Behavioural Sciences. Her research focuses on scaffolding processes, adaptive teaching, and classroom observational research from a complex dynamic systems perspective. Specializes in teacher-student interaction Expert in adaptive instruction and observational methods Collaborates with Data Science department Develops tools for classroom observation Research interests include language learning and teaching , judgment and decision-making in education , and professional development of teachers . She leads projects like Eye Get It (joint attention in classrooms) and a replication study on adaptive instruction effectiveness. Her work applies dynamic systems theory to second language development and foreign language pedagogy. Recent publications address translanguaging in multilingual classrooms, replication studies , and process-oriented research . She teaches at Utrecht's Graduate School of Teaching and works on initiatives to reduce teacher shortages through improved training programs.

• 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.

Aad van der VaartView profile

Professor

• Mathematical Statistics
• Bayesian Statistics
• Medical Imaging
• +3 more

Aad van der Vaart is a Professor of Stochastics at Leiden University's Mathematical Institute. He was awarded the prestigious NWO Spinoza Prize in 2015 for groundbreaking work in mathematical statistics, particularly Bayesian methods applied to medical imaging, genetic data, and complex models. His research bridges pure mathematical theory with applied domains like neuroscience and astronomy. Research Interests : Van der Vaart focuses on infinite-dimensional Bayesian statistics, nonparametric models, and statistical genetics. His work emphasizes rigorous mathematical analysis of prior distributions and their impact on data-driven conclusions. Applications include gene network modeling and PET scan image reconstruction. Key Contributions : Authored influential books on estimation theory; pioneered modern Bayesian approaches to high-dimensional data. His Spinoza Prize funds will support interdisciplinary research and hiring new talent in statistical methods. Awards : NWO Spinoza Prize (2015), recognized as a global leader in statistical theory. Future Directions : Expanding into astronomical data analysis and medical applications, leveraging Bayesian frameworks for big datasets.

• 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.

• Artificial Intelligence
• Medical Imaging
• Cardiac MRI Analysis
• +3 more

Qian Tao is an Assistant Professor at the Department of Imaging Physics , Faculty of Applied Sciences , Delft University of Technology . She previously worked at the Division of Image Processing, Department of Radiology, Leiden University Medical Center from 2009 to 2020. Academic Background: BSc in Electrical Engineering (Fudan University), MSc in Biomedical Engineering (Fudan University), PhD in Biometric Authentication (University of Twente) Research Interests: Focus on trustworthy AI methodologies for critical healthcare applications, including medical imaging for patient diagnosis and clinical intervention. Specializes in cardiac MRI analysis, image-guided interventions for cardiac arrhythmias, and AI in Radiology. Publication Trends: Recent work emphasizes motion correction in cardiac MRI, deep learning for image registration, and novel techniques like TRAFF2 mapping. Keywords include Medical Imaging , Machine Learning , Cardiac MRI , and Quantitative Analysis . Contact: Email: Q.Tao@tudelft.nl

• 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.

Mathias FunkView profile

Associate Professor

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

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

Ioannis AthanasiadisView profile

Professor

• Artificial Intelligence
• Machine Learning
• Agricultural Modeling
• +7 more

Ioannis Athanasiadis is a Full Professor and Chair of Artificial Intelligence at Wageningen University & Research (The Netherlands). He leads the Artificial Intelligence (AIN) group, focusing on advancing AI methods for global challenges in agriculture, ecology, and sustainability. Previously, he was faculty at the Dalle Molle Institute for Artificial Intelligence (IDSIA, Switzerland) and the Democritus University of Thrace (Greece). He holds a PhD (2005, cum laude) in Electrical and Computer Engineering from Aristotle University of Thessaloniki. His research integrates machine learning, knowledge engineering, and environmental modeling to address food security, climate adaptation, and ecosystem services. He leads initiatives like AgML (AgMIP's machine learning benchmarking effort) and coordinates European grants such as LTER-LIFE and CYBELE . Prof. Athanasiadis has supervised over 40 PhD/postdoc researchers and serves as Editor of Environmental Modelling and Software . He collaborates internationally on projects involving AI for crop modeling, digital twins, and sustainable agriculture. His team develops frameworks like Crop2ML and PyCrop2ML to enhance interoperability between process-based models and machine learning systems.

Sanne KruikemeierView profile

Professor

• Digital Media
• Political Communication
• Social Media and Polarization
• +4 more

Prof. Sanne Kruikemeier is a Professor of Digital Media and Society at Wageningen University & Research (WUR). She leads the ERC Starting Grant (HUNTING) and a NORFACE consortium grant, coordinating research across four European universities (2020–2024). As director of the Digital Data and Democracy Lab and member of the AlgoSoc Gravitation Program, she explores digitalization's societal and democratic impacts. Her research focuses on data-driven political targeting, social media's role in polarization, privacy behavior, and digital journalism. She holds roles on the editorial boards of journals like Human Communication Research , International Journal of Press/Politics , and Digital Journalism . Awards include the KNAW Early Career Award and ICA Herbert S. Dordick Dissertation Award. Her work bridges digital media, political communication, and societal change, addressing challenges like misinformation and democratic engagement. Kruikemeier advises PhD candidates on projects like data-driven campaigning's impact on democracy and polarization strategies. She engages in public discourse through media commentary on social media's role in politics and news consumption trends. Her interdisciplinary approach integrates communication science with computational methods to analyze modern political and social dynamics.

• Human-Centered Design
• Sustainable Design
• Inclusive Design
• +5 more

Dr. Stella Boess is a Researcher at the Department of Industrial Design Engineering, Faculty of Industrial Design Engineering at Delft University of Technology. She focuses on interdisciplinary research bridging social sciences and engineering, particularly in sustainable renovation, accessibility, and health technology. Her work emphasizes user-centered design in residential environments, addressing challenges such as heat pump adoption and inclusivity for visually impaired individuals. She teaches courses like Inclusive Design and Prototyping for Interaction , and has collaborated on projects including the HiPP initiative for optimized patient experiences and the NWO usability project. She appeared in media such as NPO's Programme Reference Man in 2022. Her research interests include human-technology relations, sustainable building practices, and co-creation methodologies. She explores how design interventions impact occupant behavior and satisfaction, advocating for holistic approaches to integrate technology with human practices. Recent projects also address mobility design improvements for automotive interiors and inclusive medical solutions for the Global South. Research Projects: HiPP: Optimizing orthopedic patient care pathways NWO design for usability project REIL project: Enhancing rehabilitation interactions AAL project MyGuardian: Supporting aging populations Stella’s publications from 2022 to 2025 reflect a trend toward analyzing socio-technical dynamics in sustainable housing and mobility systems. She highlights the importance of stakeholder collaboration and participatory frameworks to ensure equitable outcomes. No scientific awards are listed, but her contributions to inclusive design and zero-energy renovation are notable.

Gamze Z. DaneView profile

Assistant Professor

• Urban Planning
• GIS and Decision Making
• Urban Informatics
• +3 more

Gamze Z. Dane is a tenured Assistant Professor at the Department of Built Environment of Eindhoven University of Technology (TU/e), affiliated with EAISI Mobility and EAISI Health. She leads the Digital City Program (2020-2024) and specializes in decision-support systems, GIS, urban informatics, and data analytics for sustainable urban development. Her research integrates citizens into urban decision-making using digital tools like VR twins and data-driven approaches. Education: PhD in Urban Planning, MSc in Geographical Information Systems (GIS) and Decision Making. Research Interests: Focuses on human-environment interaction, transdisciplinary urban projects, and the impact of digitalization on cities. She develops tools for public participation and uses big data to analyze citizen behavior and urban experiences. Projects: Principal Investigator for EU/national projects involving cities like Eindhoven, Bologna, and Lisbon. Notable projects include UBeX Urban Behavior eXtended reality lab (2024-2026) and ROCK (2017-2020). Awards: Cuperusprijs 2020 (2nd place for student thesis) Drivers of Change Exhibition 2021 ISPRS International Journal Cover Story (2020) Teaching & Innovation: Coordinates courses like Smart Cities and Urban Redevelopment. Developed online teaching materials using VR, drones, and mobile apps. Guest lectures at Istanbul Technical University and visiting scholar at National University of Singapore. Labs & Networks: Leads the UBeX lab exploring immersive technologies for urban analysis. Active in academic networks including Urban Planning journals and international conferences.

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.

Nelly V. LitvakView profile

Professor

• Algorithms for Complex Networks
• Applied Probability
• Stochastic Operations Research
• +5 more

Nelly V. Litvak is a Full Professor in Algorithms for Complex Networks at Eindhoven University of Technology (Mathematics and Computer Science). She works on mathematical methods and algorithms for complex networks (social networks, WWW) using random graph models. She joined TU/e as a part-time professor in 2017 after being an Associate Professor at the University of Twente since 2012. Affiliations: 4TU Applied Mathematics Institute, Data Science Center Eindhoven, CTIT Industry Partners: ABN-AMRO Bank, Philips Lighting, Thales Editorial Role: Managing Editor of Internet Mathematics Her research focuses on extracting value from network data across three areas: (1) Information extraction and prediction, (2) Mathematical analysis of network characteristics, and (3) Efficient algorithms for incomplete network data. Key topics include PageRank, HITS algorithm, random graphs, homophilic networks, and network epidemiology. Recent work (2022-2025) spans network growth mechanisms, fairness in ranking algorithms, educational pedagogy, and pandemic forecasting dashboards. She contributes to SDGs through data-driven approaches to societal challenges. Teaching activities include course development at TU/e and earlier institutions, with innovative methods for computer engineering students' statistical understanding.

Vedran DunjkoView profile

Professor

• Quantum Computing
• Quantum Machine Learning
• Quantum Artificial Intelligence
• +7 more

Professor Vedran Dunjko is a faculty member at the Leiden Institute of Advanced Computer Science (LIACS), Leiden University, with affiliations to the Leiden Institute of Physics (LION). He leads the Applied Quantum Algorithms group and co-founded the Quantum@LIACS initiative, focusing on the intersection of quantum computing, machine learning, and artificial intelligence. His research interests include quantum machine learning, quantum-enhanced reinforcement learning, quantum heuristics, and the application of AI to quantum computing challenges. Dunjko's work bridges theoretical foundations with experimental implementations on near-term quantum devices, exploring both quantum advantages in learning and the use of classical AI for quantum system design. The recent publications show a strong trend toward proving quantum advantages in learning tasks, optimization, and topological data analysis, with publications in Nature , Nature Communications , and NeurIPS . Key themes include quantum policy gradients, quantum TDA, and reinforcement learning for quantum circuit optimization. ERC Consolidator Grant (2024) PNAS Cozzarelli Prize (2018) Editor’s Suggestion in Physical Review Letters (2014, 2018) Featured in Physics (American Physical Society) (2014, 2018) Dunjko advises several PhD candidates and postdocs, including Rahul Bandyopadhyay, Sofiene Jerbi, and Lea Trenkwalder. He has received competitive grants, most notably the ERC Consolidator Grant in 2024. His group fosters international collaborations with institutions across Europe and industry partners. The Applied Quantum Algorithms group and the Quantum@LIACS team combine theoretical investigations with practical implementations on quantum hardware, focusing on scalable quantum algorithms and AI-driven quantum discovery.