Find Academic Supervisors

Nezihe Merve GürelView profile

Assistant Professor

• Machine Learning
• Computer Science
• Pattern Recognition
• +4 more

Nezihe Merve Gürel is an Assistant Professor in Computer Science at Delft University of Technology (TU Delft), affiliated with the Pattern Recognition & Bioinformatics Group within the Intelligent Systems Department of the Faculty of Electrical Engineering, Mathematics and Computer Science. Her research focuses on developing robust, reliable, and efficient machine learning methods with enhanced reasoning capabilities, bridging theoretical rigor and practical applications. She emphasizes data-centric approaches to improve ML systems. Education: PhD in Computer Science from ETH Zurich, MSc from EPFL (Switzerland). Research Interests: ML robustness, reliability, reasoning, data-centric ML, federated learning, and explainable AI. Her recent work includes certified robustness for retrieval-augmented models and time-efficient learning algorithms. She has contributed to the Journal of Data-centric Machine Learning Research as an executive editor and served as a reviewer for top ML conferences (NeurIPS, ICML, ICLR). She previously held roles at IBM Research, Stanford University's Human-Centered AI Lab, and Westlake Institute for Advanced Study. Her awards include the Generation Google Scholarship and Cisco Research Funding . Scientific Awards : Generation Google Scholarship (2021) Cisco Research Center University Funding Labs & Teams : She leads research in the Pattern Recognition Laboratory at TU Delft and collaborates with international institutions like Stanford and Westlake Institute for Advanced Study.

• Computational Neuroscience
• Machine Learning
• Neural Networks
• +5 more

Prof. Sander Bohte is a part-time full professor of Computational Neuroscience at the University of Amsterdam (Swammerdam Institute of Life Sciences) and an honorary full professor of Bio-inspired Neural Networks at the University of Groningen. He serves as a Scientific Staff Member and Group Leader in the Machine Learning department at CWI, Amsterdam. His work bridges computational neuroscience and machine learning with a focus on continuous-time information processing. Key research interests include: Spiking Neural Networks with predictive coding and multi-compartment models Biologically Plausible Learning in recurrent and deep architectures Working Memory modeling via reinforcement learning Neuromorphic Computing for real-time systems and GPU acceleration His recent publications highlight trends in neural adaptation , predictive coding , and SNN hardware-software co-design . Awards include the Veni Innovational Research Grant (2004) and ERCIM grant (2013) . He actively supervises MSc theses and leads grants like the NWO KIC project 'Selfhealing Neuromorphic Systems' (2024).

Sofía CaleroView profile

Professor

• Materials Science
• Computational Physics-Chemistry
• Renewable Energy
• +7 more

Prof. Sofía Calero is a Full Professor at the Eindhoven University of Technology (TU/e) and Vice Dean of the Department of Applied Physics & Eindhoven School of Education. She leads the Materials Simulation & Modelling group, focusing on computational methods for renewable energy and nanostructured materials. MSc (1995) and PhD (2000), University Complutense of Madrid Marie Curie Fellow (2001–2003), University of Amsterdam Ramón y Cajal Fellow (2004) and Full Professor (2017) at University Pablo de Olavide (Spain) Her research bridges computational physics-chemistry and industrial applications, developing force fields, algorithms, and simulation methods to reverse-engineer material properties. She specializes in adsorption , metal-organic frameworks , zeolites , and molecular simulation , contributing to SDGs like climate action and clean energy. Recent publications focus on halide perovskites , carbon dioxide capture , and nanostructured materials , with software tools like RASPA and iRASPA as key outputs. Articles span Nano Letters , Chem , and Journal of Physical Chemistry C . ERC Proof of Concept Grant (2018) Marie Curie Excellence Award (2005) Fellow of the Royal Society of Chemistry (2024) She has supervised 36 research works and taught courses like Advanced Materials Modelling and Mechanics . Her work involves collaborations with industries and institutions across Europe.

Jacco van OssenbruggenView profile

Professor

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

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.

David AbbinkView profile

Professor

• Human-Robot Interaction
• Haptics
• Shared Control
• +7 more

Professor David Abbink is a Full Professor of Haptic Human-Robot Interaction at Delft University of Technology, holding a joint appointment between the Department of Cognitive Robotics in the Faculty of Mechanical Engineering and Industrial Design Engineering since November 2023. He founded the Delft Haptics Lab and co-founded the Cognitive Robotics Department in 2017. Abbink leads the transdisciplinary research and innovation centre FRAIM, which was awarded the prestigious NWO Stevin Premie (Dutch Nobel Prize equivalent) in June 2024. Trained as a mechanical engineer specializing in biomechanics, Abbink's research focuses on human behavior adaptations when interacting with autonomous systems. He has published over a hundred scientific articles on human-robot interaction, haptics, shared control, tele-operation, driver assistance systems, and sensorimotor control. His research has been funded by industry partners (Nissan, Boeing, Renault), RVO (Brightsky project 2022-2026), and the Dutch Science Foundation NWO through personal grants (VENI 2010-2014, VIDI 2015-2019). Abbink's recent work centers on worker-robot relations as an academic focus, collaborating with organizations like Erasmus Medical Centre for nursing work, Schiphol and KLM for baggage handling, and KLM Engine Repair Services for maintenance work. He also serves as scientific director for the Centre for Meaningful Human Control, launched in October 2024. His work bridges engineering, social sciences, and practical applications to responsibly shape the future of work with emerging robotic capabilities. NWO Stevin Premie (2024) Best IEEE SMC journal paper on Cybernetics (2019) Top 25 scientific talents according to New Scientist (2015) Best teacher of Faculty 3mE (2013, 2014) Best teacher of Department of BioMechanical Engineering (seven consecutive years) Abbink has supervised over 110 MSc students and 11 PhD students. His educational contributions include developing the Master Programme in Robotics at TU Delft and receiving international recognition for his course 'The Human Controller.' He is also a prominent science communicator, featured on national television, radio, and major Dutch newspapers, and has delivered lectures at venues like The Royal Institution and Lowlands Festival. Despite his academic commitments, Abbink maintains a drummer persona, having recorded four albums and performed over 400 shows across three continents between 1999-2014.

Himanshu VermaView profile

Assistant Professor

• Human-AI Collaboration
• Cognitive Empathy
• Health and Well-being
• +5 more

Himanshu Verma is an Assistant Professor at the Knowledge and Intelligence Design Group within the Faculty of Industrial Design Engineering at Delft University of Technology. His research focuses on Human-AI Collaboration, Cognitive Empathy, and designing AI systems attuned to human needs. Prior to TU Delft, he held postdoctoral roles at the University of Fribourg, EPFL, and HES-SO Valais-Wallis, Switzerland. Education: PhD in Computer Science (EPFL, Switzerland), focusing on collaborative group interactions and shared environments. Postdoctoral research in Human-Computer Interaction and Ubiquitous Computing. Research Interests: Empathy-Centric Design for inclusive technologies. Social Signal Processing in human-AI interactions. Health, well-being, and accessibility in AI systems. Key Projects: Co-leads the PERISCOPE (H2020) research project. Designs tools like EmpathiCH and COCTEAU for empathy-driven decision-making. Teaching: Design Analytics (2023–2024). Empirical Design Research (2024). Labs & Teams: Active in the Knowledge and Intelligence Design Group, focusing on AI ethics, hybrid workspaces, and empathetic systems.

Asier MonevaView profile

Researcher

• Criminology
• Cybercrime
• Environmental Criminology
• +4 more

Dr. Asier Moneva is a Postdoctoral Researcher at the Netherlands Institute for the Study of Crime and Law Enforcement (NSCR) and The Hague University of Applied Sciences , specializing in cybercrime , environmental criminology , and situational crime prevention . His work focuses on offender decision-making in cyberspace, cybercrime victimization patterns, and the application of data science to crime analysis. Education : PhD in Criminology (2020), Master in Crime Analysis and Prevention (cum laude, 2017) from Miguel Hernández University. Current Role : Analyzing cybercrime patterns through environmental criminology frameworks and data science methodologies. Moneva's research examines longitudinal offending patterns in cybercrime, particularly through analyses of web defacement archives ( Zone-H data) and hacker behavior. His studies reveal extreme concentration of cybercrime among chronic offenders, with 2.9% of hackers responsible for 68.5% of defacements. He also investigates repeat victimization dynamics in digital environments and the effectiveness of warning banners as deterrents. Recent publications focus on ransomware payment decisions by SMEs, stolen data markets on Telegram, and the intersection of familial relationships with cybercrime involvement. His work combines quasi-experimental designs , crime scripting , and conjunctive analysis to develop prevention strategies.

• Human-Algorithm Interaction
• AI Ethics
• Data-Driven Design
• +3 more

Dr. Dave Murray-Rust is an Associate Professor in Human-Algorithm Interaction Design at TU Delft's Faculty of Industrial Design Engineering. He explores the intersection of humans, data, and AI through design research, focusing on ethical AI systems and sociotechnical interactions. His work bridges computer science, design theory, and digital sociology, addressing challenges like algorithmic fairness and human-AI collaboration. He leads initiatives such as the AI Futures Lab and Data-Centric Design Lab, advancing methods for leveraging behavioral data in design processes. His research emphasizes experiential AI frameworks, metaphors for designers, and the legibility of AI systems. He has been honored with awards including Best alt.HRI 2024 and a CHI 2023 Best Paper Award for contributions to fairness perceptions in algorithmic decision-making. Murray-Rust teaches courses like the Speculative Design Studio and collaborates on projects like DCODE (Designing the Future of AI) and the BrightSky Project. His work extends to public engagement through installations like GeoPact and explorations of blockchain's societal impact. He holds an Honorary Fellowship at the University of Edinburgh.

Sara De VuystView profile

Assistant Professor

• Feminist Media Studies
• Queer Media Studies
• Ageing Studies
• +4 more

Sara De Vuyst is an Assistant Professor of Contemporary Visual Culture at Maastricht University’s Department of Literature and Art within the Faculty of Arts and Social Sciences. Her research focuses on feminist/queer media studies, ageing representations, and gender issues in media/journalism/technology. She previously held postdoctoral appointments at Ghent University (ERC project Later-in-Life Intimacies) and was a Visiting Professor at Vrije Universiteit Brussel. Education: PhD in Communication Studies (Ghent University) Professional Roles: Chair of ECREA’s Gender, Sexuality & Communication section National Coordinator for Global Media Monitoring (Belgium) Research Interests: Her work critically examines age/gender/sexuality intersections in media and art, with a focus on queer feminist resistance and digital spaces. She created the website LILI to challenge societal norms around ageing and identity. Key areas include: Queer ageing narratives Gendered digital journalism practices Feminist critiques of media representations Publications: Authored Hacking Gender and Technology in Journalism (2020), published widely in gender/media studies journals. Engages interdisciplinary methods combining quantitative/qualitative approaches. Advocacy: Actively addresses gender inequalities in media through policy work and educational initiatives. Serves as a thought leader in intersectional digital media ethics.

• Tomography
• Computational Imaging
• Computer Science
• +5 more

Joost Batenburg is a Professor at Leiden Institute of Advanced Computer Science (LIACS) , with a chair in Imaging and Visualization . He is affiliated with the Centrum Wiskunde & Informatica (CWI) and serves as Program Director for the interdisciplinary Society, Artificial Intelligence and Life Sciences (SAILS) initiative. His research focuses on tomographic image processing and reconstruction , where he has published over 80 journal articles and 60 conference papers. Current projects include Universal Three-dimensiOnal Passport for process Individualization in Agriculture (UTOPIA) and Center for Optimal, Real-Time Machine Studies of the Explosive Universe (CORTEX) , both funded by NWO grants. He leads the FleX-Ray Lab , a custom CT system integrated with advanced data processing algorithms. His research spans discrete tomography , real-time imaging pipelines , and AI-enhanced reconstruction methods , with applications in industrial inspection, agricultural analysis, and cultural heritage conservation. Recent articles demonstrate novel approaches to: Single-shot dynamic object tomography using level-set methods and motion modeling X-ray scattering quantification for defect detection in real-time systems Cross-modal image registration between CT scans and physical photographs Auto-differentiation in CT workflows combining classical and machine learning algorithms Scientific Awards: Dutch Award for ICT Research (2018) C.J. Kok Prize (2007) Philips Mathematics Prize (2006) He has supervised numerous PhD candidates including Mary Go, Eani Lachmansingh, and Zhichao Zhong, while maintaining editorial roles at IEEE Transactions on Computational Imaging and Journal of Mathematical Imaging and Vision . His work bridges theoretical mathematics with practical applications in agriculture, industry, and art conservation.

Ralf PeetersView profile

Professor

• Signal and Image Processing
• Systems and Control Theory
• Mathematical Modelling
• +7 more

Ralf Peeters is a Full Professor in Mathematics of Knowledge Engineering at Maastricht University's Faculty of Science and Engineering , Department of Advanced Computing Sciences. He serves as Vice-Dean of Research and Director of the STEM Graduate School, while leading the university's team at the inter-university research school DISC and co-chairing the Mathematics Centre Maastricht. Education: PhD in Mathematics (Free University, Amsterdam, 1994) Technical Mathematics (Delft University of Technology, 1988) Research Interests span applied mathematics, systems and control theory, signal/image processing, artificial intelligence, and biomedical engineering applications. His work bridges mathematical techniques with real-world challenges in healthcare and industrial systems. Recent Publications highlight advancements in deep learning for cardiac signal reconstruction, tensor-based signal decomposition, and recurrence plot analysis. These works integrate machine learning with clinical diagnostics, particularly in electrocardiographic imaging and arrhythmia characterization. Key Collaborations: Mathematics Centre Maastricht Dutch Mathematics Platform Dutch Institute of Systems and Control Leadership Roles: Vice-Dean of Research (FSE), Director of STEM Graduate School, Head of DISC-affiliated team, and Co-Chair of Mathematics Centre Maastricht. He has supervised over 25 PhD projects, emphasizing applied research across health and industrial domains.

Afra AlishahiView profile

Professor

• Computational Linguistics
• Language Acquisition
• Neural Models of Language
• +5 more

Afra Alishahi is a Full Professor at Tilburg University's Department of Cognitive Science and Artificial Intelligence within the Tilburg School of Humanities and Digital Sciences. Her research focuses on computational models of human language acquisition and grounded language learning, leveraging neural models to explore how language processing and acquisition occur. She has held roles including Assistant Professor at Tilburg University (since 2011) and Postdoctoral Fellow at Saarland University (2008-2011). Her work bridges computational linguistics, cognitive science, and artificial intelligence, with contributions to understanding language learning mechanisms through models that integrate visual, auditory, and linguistic data. Education: PhD (university unspecified), with prior academic roles in Iran and Germany. Awards: CoNLL 2017 Best Paper Award, 2023 Outstanding Paper Award, NWO Aspasia Grant (2015), and NWO Natural Artificial Intelligence Grant (2015). Her research has been supported by grants such as the Dutch National Research Agenda-funded project on interpreting deep learning models for text and sound. Research Interests: Grounded language learning, interaction effects in language acquisition, and neural model interpretability. Key areas include multi-modal learning (e.g., linking speech to visual scenes), computational modeling of child language learning, and probing neural networks for linguistic knowledge. She co-organized workshops like BlackboxNLP (2018-2020) and has authored over 60 publications, including influential works on phonology encoding in neural models and gender disambiguation in machine translation. Teaching: Courses include Cognitive Models of Language Learning , Computational Linguistics , and Language, Cognition & Computation . She advises master's theses and leads projects in data science and AI. Lab/Team: Leads research on computational modeling, collaboration with interdisciplinary teams (e.g., with Grzegorz Chrupała, Afsaneh Fazly), and involvement in initiatives like the Interpreting Deep Learning Models for Text and Sound project.

Rianne ConijnView profile

Assistant Professor

• Learning Analytics
• Human-Technology Interaction
• Artificial Intelligence
• +6 more

Rianne Conijn is an assistant professor in the Human-Technology Interaction group at Eindhoven University of Technology (TU/e), Netherlands. Her research bridges data-driven methodologies (machine learning, statistical modeling) with human-centered design to enhance learning analytics, explainable AI, and writing process analysis. She holds a joint PhD (cum laude) from Antwerp University and Tilburg University, and an MSc (cum laude) in Human-Technology Interaction from TU/e. Academic Background: MSc (2015, TU/e, cum laude), PhD (2020, Antwerp University & Tilburg University, cum laude). Research Focus: Learning analytics, keystroke logging, explainable AI for education, data dashboards, and self-regulated learning dynamics. Teaching: Courses in Advanced Research Methods, Human-AI Interaction, Behavioral Research Methods, and AI ethics in education. Her recent publications explore parallel language planning in writing, longitudinal self-regulated learning strategies, and generalizability of academic performance prediction models. She leads an NWO Veni project on Human-Centered AI in education, emphasizing tailored explanations for student-AI collaboration. Scientific awards include cum laude distinctions for her MSc and PhD, and the NWO Veni grant. Collaborative work spans institutions in the Netherlands, Norway, and the U.S., with applications in intelligent tutoring systems and ethical AI deployment in exams. Key trends across her work: integration of machine learning with educational theory, leveraging keystroke data for cognitive process insights, and prioritizing actionable, explainable AI systems for student support. Publications span journals like the Journal of Experimental Psychology: General , Computers and Education , and IEEE Transactions on Learning Technologies . Scientific Awards: NWO Veni grant for Human-Centered AI in education Cum laude for MSc and PhD Grants & Collaborations: National Science Foundation grants (2016868, 2302644) for biometric feedback in writing UK Research and Innovation grant (ES/W011832/1) for real-time AI scaffolding TU/e Boost! Program grant for self-regulated learning analysis Labs & Teams: EAISI Foundational (Eindhoven AI Systems Institute) Human Technology Interaction group at TU/e Collaboration with Norwegian Reading National Center (University of Stavanger) Project teams for Waterproof ITS and ProWrite grants

• Digital Humanities
• Media and Diaspora
• Media History
• +5 more

Dr. Jasmijn van Gorp is a Senior Lecturer in the Department of Media and Culture Studies at Utrecht University's Faculty of Humanities. She specializes in Digital Humanities , Audiovisual Heritage , and Digital Culture with a focus on Television History and Eastern European Media . As co-founder of the CLARIAH Media Suite, she develops digital research infrastructure for audiovisual heritage in the Netherlands. PhD in Social Sciences from the University of Antwerp (Belgium) MA in Communication Sciences from KU Leuven (Belgium) Her research examines digital methods for film and television studies , metadata in digital archives , and AI-generated analysis of broadcast schedules . She leads projects like Re-Frame (2021-2025) and AI TaDa , exploring the reuse of audiovisual archives in journalism and algorithmic metadata generation. Recent work includes tutorials on Data Visualization and Flow Analysis using the Media Suite. She advocates for critical digital tool literacy in education and co-authored the Digital Skills learning trajectory for Utrecht's BA programs. Her teaching includes Digital Television History and Programming and Curation at BA and MA levels, supervising theses in film and television studies. As workpackage leader for CLARIAH-PLUS WP5 , she integrates computer vision , automatic speech recognition , and linked data into sustainable tools for cross-media research. She trains researchers via the Media Suite Learn initiative and collaborates on digital infrastructure projects with institutions like NISV and CLARIAH.

Andreas WeberView profile

Associate Professor

• Science and Technology Studies
• History of Science
• Digital Humanities
• +4 more

Andreas Weber is an Associate Professor at the University of Twente's Digital Society Institute , specializing in the Knowledge, Transformation & Society (KiTeS) research group . His work examines the long-term historical and global relationship between Science, Technology, and Society , with particular focus on colonial histories of natural history, chemistry, and sustainability , as well as computational technologies for contextualizing digitized archives . He leads the HAICu project (2023–2029) on digital cultural heritage and coordinates STS PhD training for the Netherlands Graduate Research School (2019–2024). MA & PhD in History (2005 & 2012), Leiden University Assistant Professor (2017–2023), University of Twente Andreas' research integrates digital humanities with colonial science history , emphasizing global histories of minerals , digital humanism , and AI's societal context . His 15 most recent publications (2016–2025) explore topics like colonial bias in natural history collections , FAIR data implementation , and semantic annotation of handwritten archives , spanning disciplines from history of science to computer science and museum studies . He has received 7 scientific awards , including multiple Best Teacher Awards (2020–2023) and the IEEE eScience Best Poster Award (2018). Andreas supervises PhD and postdoctoral projects while engaging in media commentary on colonial heritage issues and co-organizing international conferences like Hydrogen Pasts and Futures (2024).