جستجوی استاد راهنمای دانشگاهی

Prof. Ronald Meester is a Full Professor of Mathematics at the Faculty of Science, Vrije Universiteit Amsterdam. He specializes in mathematical statistics, probability theory, and their applications in legal and environmental contexts. His current positions include director of Meester Advies (Leiden) and expert for Landelijke Deskundigheidsmakelaar Politie (Apeldoorn). He has supervised 14 PhD theses and contributes to interdisciplinary research bridging statistics with law, epidemiology, and environmental policy. Research focuses on Bayesian reasoning, likelihood ratio analysis, and statistical methodologies for legal evidence evaluation. Recent work addresses nitrogen deposition policy critiques and epidemiological study design limitations. His ancillary activities include authorship (since 2003) and teaching roles at SSR Utrecht. Media engagements include commentaries on scientific integrity and environmental policy. Teaching includes the course 'Mathematical Modelling of Stochastic Systems' (2024-2025 academic year). Active in international collaborations and has produced 111 research outputs spanning articles, books, and encyclopedia entries. His work contributes to UN SDGs related to sustainable development through environmental statistical analysis.

• Mathematical Statistics
• Probability Theory
• Bayesian Reasoning
• +۳ مورد دیگر

Dr. Peter J.F. Lucas is a Full Professor specializing in Datamanagement & Biometrics with over 35 years of experience in artificial intelligence, probabilistic graphical models, and clinical decision support systems. His research spans intelligent systems, machine learning, and eHealth, with a focus on applying Bayesian networks and probabilistic logic to medical and non-medical domains.

• Artificial Intelligence
• Bayesian Networks
• Machine Learning
• +۶ مورد دیگر

Charles E.H. Berger serves as Professor by Special Appointment in Criminalistics at Leiden University's Institute for Criminal Law and Criminology since November 2011, a position funded by the Stichting Leerstoel Criminalistiek. He concurrently holds a principal scientist position at the Netherlands Forensic Institute (NFI), where he contributes to education, R&D strategy, and research on forensic evidence interpretation. His research program centers on logically sound interpretation of forensic evidence through probability theory and computational methods. Berger specializes in applying Bayesian statistics to forensic anthropology, personal identification, and evidential evaluation. His work emphasizes moving forensic science toward activity-level interpretations while managing contextual information to prevent bias. Berger plays a pivotal international role as member of ISO technical committee TC272, serving as lead editor for Part 4 (Interpretation) of the ISO-21043 Forensic Sciences standard. His scholarly contributions focus on improving forensic reasoning frameworks and establishing objective evaluation methodologies. His publications demonstrate consistent engagement with foundational forensic science challenges, particularly in developing statistically rigorous approaches to evidence interpretation that maintain scientific integrity within legal contexts. Berger actively promotes scientifically sound practices across the criminal justice system, emphasizing the importance of clear communication between forensic scientists, legal professionals, and other stakeholders to ensure proper understanding and application of forensic evidence.

• Forensic Science
• Computational Forensics
• Evidential Evaluation
• +۳ مورد دیگر

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.

• Machine Learning
• Computer Science
• Pattern Recognition
• +۴ مورد دیگر

Erik Quaeghebeur is an Assistant Professor at Eindhoven University of Technology's School of Mathematics and Computer Science, focusing on uncertainty modeling in artificial intelligence. His work spans probabilistic circuits, imprecise probability theory, and wind energy applications. PhD in Applied Mathematics (Ghent University, 2002-2009) Master's in Applied Mathematics (Université catholique de Louvain, 2001-2002) Master's in Physics Engineering (Ghent University, 1998-2001) Research interests include probabilistic modeling under uncertainty, with applications in AI and wind energy systems. His recent work explores tensor factorizations, equivariant graph neural networks, and scalable probabilistic circuits. Scientific contributions include 60 research outputs and 2 datasets . Awards encompass the ERCIM Alain Bensoussan Fellowship (2013), BOF Postdoc (2010), and B.A.E.F. Francqui Fellowship (2009). He serves on committees for the Society for Imprecise Probability and acts as editorial board member for related conferences. Foundations of Artificial Intelligence course (since 2020) Uncertainty Representations and Reasoning course (since 2021)

• Probability Theory
• Statistics
• Uncertainty in Artificial Intelligence
• +۴ مورد دیگر

Prof. Rineke Verbrugge is a Professor in Artificial Intelligence at the University of Groningen's Faculty of Science and Engineering, affiliated with the Bernoulli Institute. Her research focuses on computational theory of mind, multi-agent systems, hybrid intelligence, and logical frameworks applied to social networks and legal reasoning. She holds additional roles on the Institute Advisory Board of CWI (Dutch National Research Institute for Mathematics and Computer Science) and several ERC/NWO selection committees. Her work bridges cognitive science and AI, emphasizing human-agent collaboration, belief formation in groups, and ethical AI design. Recent projects include developing computational models for theory of mind in negotiations and scenario-based Bayesian networks for legal evidence analysis. She has authored over 220 publications and supervised multiple PhD candidates in AI and logic. Key research themes include higher-order theory of mind applications, zero-one laws in provability logic, and agent-based policy evaluation for sustainable technologies. Her contributions span conferences like AAMAS, ICAIL, and HHAI, addressing topics from lie detection mechanisms to privacy conflicts in multi-user systems.

• Artificial Intelligence
• Logic and Cognition
• Multi-agent systems
• +۴ مورد دیگر

Professor Henry Prakken is a leading researcher in Artificial Intelligence and Law at Utrecht University's Department of Computer Science. He holds a prominent position in the Responsible AI research group and has been instrumental in advancing computational models of legal argumentation. With an extensive publication record spanning over three decades, Prakken has established himself as a central figure in the intersection of law and artificial intelligence. Prakken's research interests focus on computational models of argumentation, legal reasoning systems, and the application of AI to legal domains. His work bridges theoretical foundations with practical applications, particularly in case-based reasoning, Bayesian networks for legal evidence, and formal argumentation frameworks. He has made significant contributions to understanding how computational models can represent and analyze legal reasoning processes, with particular attention to precedent-based reasoning and argument strength. His publication record demonstrates consistent research productivity with numerous high-impact papers in venues like Artificial Intelligence, Artificial Intelligence and Law, and proceedings of major conferences including ICAIL and COMMA. Recent work has expanded into evaluating generative AI's legal reasoning capabilities and developing more sophisticated models of argument strength and acceptability. Past president of the International Association for AI & Law (IAAIL) Past president of the JURIX Foundation for Legal Knowledge-Based Systems Past president of the steering committee of the COMMA conferences on Computational Models of Argument Editorial board member of Artificial Intelligence and Law Associate editor of Artificial Intelligence (2017-2022) Prakken has played a significant role in mentoring and shaping the field through his leadership positions and editorial work. His research has influenced both theoretical developments in computational argumentation and practical applications in legal technology, contributing to the growing field of responsible AI in legal contexts.

• Artificial Intelligence and Law
• Computational Argumentation
• Legal Reasoning
• +۵ مورد دیگر

Dr. Aurelien Baillon is a Professor of Economics of Uncertainty at the Erasmus School of Economics , Erasmus University Rotterdam, specializing in the Department of Applied Economics . His research focuses on individual decision-making under risk and ambiguity, combining empirical and theoretical approaches to understand probability elicitation and expert opinion aggregation. Key research areas: Behavioral Economics, Risk Attitudes, Bayesian Modeling Major projects: Bayesian Markets , Personal Model of Trumpery , Malakoff Humanis Chair His recent publications explore ambiguity theories , cybersecurity decision-making , and linguistic deception detection . Notable grants include the ERC Starting Grant (2016) and NWO Vidi Grant (2014). Collaborations span institutions like BRiO , HITS Institute , and GATE . The Datavisualization project with Alice Havrileck demonstrates his interdisciplinary approach to uncertainty analysis.

• Behavioral Economics
• Decision Making Under Risk and Ambiguity
• Subjective Probability Elicitation
• +۱۲ مورد دیگر

Leah Henderson is a Professor in the Department of Theoretical Philosophy at the University of Groningen. She holds the endowed chair on 'Societal Trust' from the Royal Holland Society of Sciences and Humanities (KHMW) and the Agricola School. Previously, she was a Rosalind Franklin Fellow since 2015. Her expertise spans philosophy of science, epistemology, and the philosophy of quantum theory. She earned a PhD in Philosophy from MIT and a DPhil in theoretical physics from the University of Oxford, with postdoctoral work in quantum information theory. Her research focuses on scientific realism, anti-realism, inference to the best explanation, and the problem of induction. She also explores societal trust dynamics and belief polarization in scientific contexts. Henderson has contributed to debates on higher-order evidence, meta-induction, and conjunctive explanations. Her work bridges philosophy with cognitive science and social epistemology. Awards: Rosalind Franklin Fellow (2015–present). Grants & Labs: Endowed chair in Societal Trust (KHMW/Agricola School), leading interdisciplinary research on societal cohesion and public trust in science. Active in media engagement, including discussions on climate skepticism and science education.

• Philosophy of Science
• Epistemology
• Scientific Realism
• +۴ مورد دیگر

Giovanni Sileno is an academic specializing in Artificial Intelligence, Logic Programming, and Knowledge Representation, with teaching appointments at the University of Amsterdam, EPITA Paris, and Université Pierre et Marie Curie. His primary affiliation is with the Informatics Institute at the University of Amsterdam where he serves as a Lecturer. His research interests span multiple domains within computer science, focusing particularly on formal methods for normative systems, agent-based programming, and logic-based knowledge representation. His work bridges theoretical computer science with practical applications in policy modeling, forensic science, and business information systems. Dr. Sileno has developed several notable software projects including AgentScriptCC for single-threaded intentional agents, DCPLschema for normative policy specifications, and libraries for normative primitives in Answer Set Programming. His GitHub activity shows consistent contributions from 2012 through 2025, indicating active engagement in both research and development. His publications reflect a strong focus on formal methods applied to practical problems, with particular emphasis on normative systems, agent architectures, and logic programming applications. The research trajectory shows evolution from foundational topics in logic and numeral systems toward increasingly sophisticated applications in policy modeling and agent-based systems. As an educator, he has taught across multiple institutions and disciplines, covering topics from basic programming paradigms to advanced knowledge representation and formal modeling techniques. His teaching spans undergraduate to master's level courses in information studies, cognitive science, data science, and forensic science.

• Artificial Intelligence
• Logic Programming
• Knowledge Representation
• +۵ مورد دیگر

Carlos Zednik is an Assistant Professor for Philosophy of Artificial Intelligence at Eindhoven University of Technology , affiliated with the Industrial Engineering and Innovation Sciences department. He leads the Eindhoven Center for Philosophy of AI and participates in the alignAI (ERC) and ROBUST AI (NWO) consortia. His work bridges philosophy with AI and neuroscience, focusing on explainable AI (XAI), mechanistic explanation, and cognitive modeling. Education: BSc in Computer Science and Philosophy, Cornell University MSc in Philosophy of Mind, University of Warwick PhD in Cognitive Science, Indiana University Bloomington Zednik’s research investigates philosophical questions about biological and artificial intelligence, emphasizing: Methodological principles in cognitive psychology and neuroscience Norms and best practices for XAI in machine learning Knowledge representation in transformer models and large neural networks His recent publications explore the integration of cognitive models into XAI, the role of Bayesian reverse-engineering in cognitive science, and the mechanistic explanation of network neuroscience. Zednik also contributes to international standardization efforts through ISO/IEC TS 6254 and DIN SPEC 92001 . Scientific Awards include fellowships from: DAAD Alexander-von-Humboldt Foundation StandICT Fellowship Zednik supervises PhD students Zeynep Kabadere , Michela Ghezzi , Céline Budding , Miriam Gorr , and Hannes Boelsen , while mentoring postdocs Manuel Barbosa de Oliveira and Philippe Verreault-Julien . His teaching spans philosophy of AI, ethics of machine learning, and decision theory, with innovation projects on generative AI in higher education.

• Philosophy of Artificial Intelligence
• Cognitive Science
• Neuroscience
• +۳ مورد دیگر

Federica Russo is a full professor in Philosophy and Ethics of Techno-Science holding the prestigious Westerdijk Chair at the Freudenthal Institute, Utrecht University. She also serves as Honorary Professor at University College London in the Department of Science and Technology Studies. Her academic career spans multiple institutions including previous positions at the University of Kent, University of Pittsburgh, and University of Louvain. Professor Russo's research focuses on epistemological, methodological, and normative aspects arising in health and social sciences, with special attention to policy contexts and the highly technologized character of these fields. Her work bridges philosophy with practical scientific applications, particularly examining causation and causal modeling, evidence frameworks, and the philosophical implications of modern technology in scientific practice. Her scholarly contributions include the 2022 monograph Techno-Scientific Practices. An Informational Approach and research on recursive Bayesian networks for scientific modeling. Her publications consistently explore the intersection of information theory, causal reasoning, and technological mediation in scientific knowledge production. Editor-in-Chief of Digital Society Former Co-Editor-in-Chief of European Journal for Philosophy of Science Executive Editor of Philosophy and Technology Member of the Steering Committee of the European Philosophy of Science Association External Faculty Member at the Institute for Advanced Study, University of Amsterdam Professor Russo actively contributes to academic governance and knowledge dissemination through her editorial roles and committee memberships. Her research program addresses critical questions about how technology shapes scientific practice and knowledge production in contemporary society, with particular relevance to evidence-based policy making in health and social domains.

• Philosophy of Science
• Ethics of Technology
• Causality
• +۵ مورد دیگر

Dr. Hüseyin Küçükali is a Researcher at the Institute for Risk Assessment Sciences (IRAS) within the Department of Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University. His work integrates epidemiology, artificial intelligence, and systems thinking to innovate non-communicable disease prevention in urban environments, with emphasis on exposome research and healthy aging initiatives. Education PhD in Public Health, Istanbul University - Cerrahpasa MD (Medicine), Istanbul University - Cerrahpasa Research Focus Dr. Küçükali's expertise spans causal inference , exposome analysis , and AI-driven health behavior modeling , particularly examining urban environmental impacts on cognitive decline and tobacco use patterns. His methodology combines accelerometry , GPS tracking , and molecular data to map mechanistic pathways in aging populations, while leveraging large language models for public health surveillance in digital spaces. Publication Trends His 15 most recent publications reveal three dominant threads: (1) urban exposome effects on cognitive health using multi-sensor data integration, (2) AI applications for tobacco control through social media content analysis, and (3) Bayesian modeling of socioeconomic disease patterns. These works consistently bridge environmental epidemiology, data science, and policy-relevant public health interventions across international contexts including Türkiye, UK, and Ireland. Professional Engagement He actively contributes to the International Human Exposome Network (IHEN) and STAGE (Stay Healthy Through Ageing) projects while leading the Utrecht Exposome Hub. Previous roles include postdoctoral research at Queen's University Belfast on urban green spaces (GroundsWell project) and health promotion leadership in Istanbul's municipal health administration. He also created educational resources like the Turkish-language Video Glossary of Public Health Concepts.

• Public Health
• Epidemiology
• Artificial Intelligence
• +۷ مورد دیگر

Benjamin Bewersdorf is the Academic Director of Education and Lecturer at University College Groningen, part of the University of Groningen. He holds a PhD in formal epistemology from the University of Konstanz and has held postdoctoral positions at the University of Konstanz and the University of Groningen's Faculty of Philosophy. His research focuses on epistemic justification, Bayesian epistemology, and interdisciplinary philosophy. He teaches courses in Philosophy of Science, Decision Making, and innovative pedagogical methods. Awards include a 2017 teaching innovation fellowship. He has led academic guidance and teaching communities, including roles at the Teaching Academy. His recent work explores art-philosophy intersections, co-authored with students. He is affiliated with the University College Groningen and has published widely in philosophy and education. Research interests span formal epistemology, decision theory, and teaching innovation. His publications include peer-reviewed chapters and articles in journals like Synthese . He emphasizes interdisciplinary approaches, blending philosophy with psychology and economics in teaching. Recent work includes exploring art as evidence in philosophical inquiry.

• Philosophy
• Decision Making
• Formal Epistemology
• +۳ مورد دیگر

Tina Comes is a Researcher at the Department of Technology, Policy and Management , Delft University of Technology , with a focus on Transport and Logistics . Her work integrates Decision Theory , Resilience Engineering , and Artificial Intelligence to address complex challenges in Disaster Management and Humanitarian Logistics . 2025: Agent-Based Modeling for crisis adaptation 2025: HILP Event Taxonomy for risk classification 2024: Dynamic Bayesian Networks in emergency mapping Her research combines Computer Science and Urban Planning to develop Data-Driven Decision Support Systems , with recent studies on flood response , healthcare resilience , and ethical AI . She has contributed to 70+ research outputs and supervised interdisciplinary projects like 4TU Resilience Engineering Centrum initiatives. Selected Trends: Prior work emphasizes information asymmetries , cognitive biases , and multi-modal data in crisis scenarios. She actively explores spatio-temporal analytics and blockchain applications for humanitarian coordination. Key Collaborations: Partnerships with European Safety and Reliability Conference (2020), ISCRAM Conference (2025), and Kenyan Election Fact-Finding (2018) Press Mentions: Highlighted in AI for Mobility (2025) and 4TU Resilience Centrum Launch (2018)

• Decision Theory
• Resilience
• Disaster Management
• +۴ مورد دیگر