جستجوی استاد راهنمای دانشگاهی

• Artificial Intelligence
• Privacy and Data Protection
• Trustworthy AI
• +۴ مورد دیگر

Prof. Dr. Pinar Yolum Birbil is a leading researcher in Responsible AI at the Faculty of Science , Utrecht University . Her work bridges Artificial Intelligence , Privacy and Data Protection , and Software Agents , focusing on Human-Centered AI and Trustworthy Systems . She is part of the AI & Data Science and Responsible AI research groups. PhD in Computer Science, North Carolina State University (2003) MS in Computer Science, North Carolina State University (2000) BSc in Computer Engineering, Marmara University (1998) Her research explores Privacy Preservation in collaborative systems, Computational Theory of Mind for human-agent coordination, and Norm-Based AI Systems . Recent projects include the Hybrid Intelligence Center and tools like PANOLA for privacy support. She investigates how AI can balance user autonomy , ethical norms , and societal values in applications ranging from urban planning to healthcare. Her scientific publications (2023-2025) span topics like Explainable Privacy , Trust in Hybrid Teams , and AI for Diabetes Management , appearing in venues such as JAIR , AAMAS , and ACM TOIT . She emphasizes collaborative AI , with contributions to multiagent simulations and privacy-preserving mechanisms . Scientific Awards : NC State University Alumni Hall of Fame (2017) Woman Entrepreneur of the Year (Microsoft Turkey & KAGIDER, 2017) Bogazici University Academic Encouragement Award (multiple years) Best Paper Award at ESAW 2009 She supervises a dynamic research group with PhD students working on Hybrid Intelligence , Computational Ethics , and Privacy Modeling . Her projects often involve interdisciplinary collaboration with institutions like TNO and the Transforming Cities Hub .

Tim Baarslagمشاهده پروفایل

استاد

• Automated Negotiation
• Multi-Agent Systems
• Artificial Intelligence
• +۴ مورد دیگر

Tim Baarslag is a Senior Researcher and group leader of the Intelligent and Autonomous Systems group at CWI (The Dutch research institute for Mathematics and Computer Science). He holds the title of Professor of Mathematics of Cooperative AI at Eindhoven University of Technology and serves as a Visiting Associate Professor at Nagoya University of Technology, Visiting Fellow at the University of Southampton, and Visiting Scholar at MIT. His research focuses on automated negotiation systems for collaborative decision-making in smart energy trading, IoT, autonomous vehicles, and digital privacy. Education : MSc (cum laude) and BSc (cum laude) from Utrecht University; PhD (cum laude) from Delft University of Technology Tim pioneered the COMBINE project (NWO Vidi grant) for coordinating multi-deal negotiations and developed the widely-used Genius negotiation environment. His work appears in prestigious venues like Science Magazine , Artificial Intelligence , and MIT Technology Review . He also leads the International Automated Negotiating Agent Competition and contributes to policy through memberships in The Young Academy and Netherlands Academy of Engineering . Recent research trends emphasize multi-deal negotiation protocols (2024), preference uncertainty modeling in privacy negotiations (2022), and scalable algorithms for handling outcome spaces as large as 10²⁵⁰ possibilities. His 2023 work on search algorithms for large negotiation domains has applications in energy trading and supply chain management. Scientific Awards : Cor Baayen Young Researcher Award (2017), Springer Theses Award (2016), multiple Best Paper Awards (AAMAS 2022, WI-IAT 2015, IJCAI 2014), and recognitions as Science Talent (2018), Academic Pioneer (2020), and Young Talent (2019) As a grant recipient , Tim leads NWO Vidi project COMBINE and previously held a Veni grant for preference uncertainty research. He mentors through organizing competitions, serving on conference PCs (AAAI, IJCAI), and reviewing in top journals like Artificial Intelligence . His work bridges theory and practice through the Genius framework and real-world implementations in smart grid and vehicular platooning.

Rineke Verbruggeمشاهده پروفایل

استاد

• Artificial Intelligence
• Logic and Cognition
• Multi-agent systems
• +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.

Maria Birna van Riemsdijkمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Autonomous Agent Systems
• Human-AI Interaction
• +۷ مورد دیگر

Maria Birna van Riemsdijk is an Associate Professor in Intimate Computing at the University of Twente, Netherlands. Her research focuses on developing technologies that address human vulnerability in daily life through intimate computing , blending ethics with AI and robotics. She leads the Human-Media Interaction group and contributes to the Digital Society Institute. Awards: Vidi personal grant Dutch Prize for Research in ICT 2014 2020 IEEE Computer best paper award Leadership Roles: Editorial board member, Journal of Autonomous Agents and Multiagent Systems Board member, 4TU.NIRICT (ICT research consortium) Former board member, IFAAMAS (2012-2018) Her research bridges Artificial Intelligence , Human-AI Interaction , and Healthcare , emphasizing responsible design. Recent work explores conversational agents for behavior support, ethical frameworks, and AI in healthcare contexts. Key article themes include responsible computing , conversational strategies , and adaptable AI frameworks . She has contributed to 26 total research outputs and datasets in human-agent alignment and social situation modeling.

A.J. Vermeulenمشاهده پروفایل

استاد

• Game Theory
• Economic Theory
• Operations Research
• +۳ مورد دیگر

Dr. A.J. Vermeulen is a Professor of Mathematical Economics & Game Theory at Maastricht University, affiliated with the Department of Quantitative Economics in the School of Business and Economics. His research focuses on game theory, economic modeling, and strategic interactions in various contexts such as cooperative and non-cooperative games, algorithmic approaches, and applications in economics and operations research. His academic contributions span topics like graph-restricted games, behavioral strategies, strategic rationing, and multiagent learning in dynamic environments. He frequently collaborates with researchers such as János Flesch, Mathijs Stevens, and others. His work often appears in top-tier journals such as Games and Economic Behavior and Mathematics of Operations Research . Dr. Vermeulen is also involved in academic leadership, as evidenced by his role in the Graduate School of Business and Economics at Maastricht University.

Gerhard Weissمشاهده پروفایل

استاد

• Artificial Intelligence
• Computer Science
• Multiagent Systems
• +۵ مورد دیگر

Gerhard Weiss is a Full Professor of Artificial Intelligence and Computer Science at the Department of Advanced Computing Sciences (DACS), Faculty of Science and Engineering, Maastricht University (Netherlands) since 2009. He previously served as Chair of DACS (2010-2020), co-director of the Swarmlab robotics laboratory, and Honorary Professor at the University of Liverpool (2014-2017). Prior roles include Scientific Director at SCCH GmbH (Austria) and Assistant Professor at Technical University Munich (Germany).

• Algorithms
• Planning
• Constraints
• +۷ مورد دیگر

Mathijs de Weerdt is a Full Professor at Delft University of Technology, leading the Algorithmics Group within the Faculty of Electrical Engineering, Mathematics and Computer Science. His research focuses on developing advanced algorithms for planning and scheduling under uncertainty, with applications in energy systems, railway logistics, satellite operations, and agricultural supply chains. He bridges fundamental AI research with practical implementations through collaborations with Dutch National Railways (NS), Shell Recharge, and industry partners. Education: PhD in Multi-Agent Plan Merging (2003), MSc in Computer Science (Utrecht University, cum laude) Research Interests: Robustness in AI, Scalability of Optimization Algorithms, and Multi-Party Coordination His work integrates Stochastic Programming , Reinforcement Learning , and Constraint Programming to address challenges in energy transition and transportation. Recent 15 most recent publications emphasize surrogate modeling for EV charging optimization, multi-agent pathfinding in railways, and dynamic programming for decision trees. Scientific Awards: Recipient of the Erasmus Energy Forum Science Award (2016), Best Teacher Award in Delft Computer Science (2015), and honorable mentions for dissertation and paper awards. As a promotor , he guides over 20 PhD candidates in projects spanning smart grid algorithms, train unit shunting, and strawberry supply chain optimization. He leads large-scale initiatives like the NWO ESI-FAR project and co-chairs the Dutch AI Coalition's Energy & Sustainability working group.

• Smart Energy Markets
• Congestion Management
• Artificial Intelligence in Energy Systems
• +۲ مورد دیگر

Prof.dr.ir. J.A. la Poutré is a professor at the Faculty of Electrical Engineering, Mathematics and Computer Science, specializing in intelligent electrical power grids. His work bridges computer science, energy economics, and power systems engineering. Research Interests : Smart energy market design and fair pricing mechanisms Congestion management in power distribution networks AI-driven optimization of energy systems Demand response and deferrable load coordination Research Outputs : His publications demonstrate expertise in applying multiagent systems, hybrid congestion models, and real-time forecasting to energy systems. Recent work focuses on balancing fairness and welfare in grid management while enabling carbon-free energy transitions through AI. Supervision : He has supervised 5 academic works, though specific student names are not detailed in the provided text.

• Applied Data Science
• Human-centered Artificial Intelligence
• Privacy in Collaborative Systems
• +۴ مورد دیگر

Dr. Onuralp Ulusoy is a Researcher at Utrecht University's Faculty of Science, specifically within the Software Technology for Learning and Teaching department. Based at the Buys Ballot Building in Utrecht, he focuses on the intersection of privacy, artificial intelligence, and collaborative systems. His research spans Applied Data Science and Human-centered Artificial Intelligence, with particular emphasis on privacy mechanisms in online environments. Ulusoy's work explores how privacy norms emerge and can be managed in collaborative settings, especially within social networks. His publication record shows a clear trajectory in privacy research, evolving from foundational work on privacy auctioning mechanisms to more recent applications in learning analytics. His most cited work, 'PANOLA: A Personal Assistant for Supporting Users in Preserving Privacy' (2022), demonstrates practical applications of his theoretical frameworks. Recent publications indicate an expansion into educational technology with tools like 'mAIchart' for primary school educators. As a researcher at Utrecht University, Ulusoy has established himself as a specialist in privacy-preserving collaborative systems, with publications spanning top conferences in multi-agent systems, access control, and social network analysis.

• Formal Argumentation
• Explainable Artificial Intelligence
• Logic
• +۲ مورد دیگر

Dr. Annemarie Borg is an Assistant Professor at the Faculty of Science , Utrecht University, specializing in Responsible AI within the Responsible AI Group . Her research bridges formal argumentation theory with real-world AI applications. Research Focus: Formal argumentation frameworks Explainable artificial intelligence Logic-based AI in legal contexts Dynamic argumentation models Human-centered AI design Publications highlight her work on: Contrastive explanations in argumentation Stability and relevance in incomplete frameworks Case-based reasoning for legal AI Hypersequent-based logical argumentation Agent-based modeling of scientific biases Contact: a.borg@uu.nl

Matthijs Spaanمشاهده پروفایل

استاد

• Safe and Robust Reinforcement Learning
• Planning Under Uncertainty
• Sequential Decision Making
• +۵ مورد دیگر

Matthijs Spaan is a Professor of Reliable AI Algorithms at Delft University of Technology , where he co-directs the Sequential Decision Making group in the Department of Intelligent Systems (EEMCS faculty). Previously, he served as an Associate Professor in the Algorithmics group at TU Delft and as a Senior Research Scientist at the Institute for Systems and Robotics, Instituto Superior Técnico (Lisbon). He holds a PhD in Computer Science (2006) and an MSc in Artificial Intelligence (2002) from the University of Amsterdam. His research focuses on safe and robust reinforcement learning , planning under uncertainty using POMDPs/Dec-POMDPs, and sequential decision-making algorithms . He has contributed to embedding epistemic uncertainty in deep reinforcement learning, safe policy improvement, and constrained decision-making frameworks for smart energy systems, robotics, and traffic optimization. His work includes 15+ key publications in top venues like AAAI, IJCAI, ICAPS, and AAMAS, spanning 2024 to 2011. He has advised four PhD students to completion and co-organized major workshops such as the Lorentz workshop on Rigorous Automated Planning (2022) and AAAI 2022 program. His professional service includes editorial roles at AI Magazine and Journal of Artificial Intelligence Research , area chair positions, and leadership in IJCAI, ICAPS, and IFAAMAS.

• Artificial Intelligence
• Social AI
• Human-Computer Interaction
• +۵ مورد دیگر

Bernhard Hilpert is a Visiting Fellow at the Faculty of Science, Vrije Universiteit Amsterdam, specializing in Artificial Intelligence and Social AI. His research bridges machine learning and healthcare applications. Research Interests: Focuses on Reinforcement Learning agents' transparency Virtual therapeutic agents for mental health Human-AI interaction models Biofeedback and facial expression analysis Patient-centered healthcare technology Recent Work Trends: Combines AI with clinical applications, particularly in outpatient depression care and multiagent system modeling. Collaborations: Works with healthcare professionals and AI researchers on deploying virtual agents in therapeutic contexts.

Yiannis Kyratsisمشاهده پروفایل

دانشیار

• Digital Health
• Artificial Intelligence in Healthcare
• Health Policy
• +۷ مورد دیگر

Yiannis Kyratsis is an Associate Professor at the Erasmus School of Health Policy & Management, Erasmus University Rotterdam. His academic work centers on digital health, artificial intelligence in healthcare, and health policy, with a focus on workforce and professional identity impacts. Institution: Erasmus University Rotterdam School: Erasmus School of Health Policy & Management His research interests span digital health adoption, AI in medical imaging, professional identity, pandemic response, and public health governance. He explores how technological innovations affect healthcare professionals and systems, especially in radiography and rehabilitation contexts. The recent articles demonstrate a consistent focus on the human and organizational dimensions of digital health and AI. Themes include professional identity under technological change, patient experiences in chronic illness, and policy responses to public health crises. His work often employs qualitative and interdisciplinary methods, engaging with stakeholders across healthcare and education sectors. Yiannis Kyratsis has contributed to editorial leadership, including a guest editorial in Frontiers in Digital Health . While no specific awards are listed, his publications have garnered attention on academic platforms and social media. He actively collaborates with researchers across Europe and beyond, particularly in projects related to AI implementation and pandemic governance. His work contributes to UN Sustainable Development Goals, especially in health and well-being. No information is available on student advising or grant funding in the provided text.

Ulle Endrissمشاهده پروفایل

استاد

• Artificial Intelligence
• Collective Decision Making
• Computational Social Choice
• +۵ مورد دیگر

Ulle Endriss is a Professor of Artificial Intelligence and Collective Decision Making at the Institute for Logic, Language and Computation (ILLC) at the University of Amsterdam. He leads the COMSOC Group and is a member of both the Theoretical Computer Science research unit of the ILLC and the Centre for Explainable, Responsible and Theory-driven AI (CERTAIN). Endriss has held academic positions since 2005, progressing from Assistant Professor (2005-2011) to Associate Professor (2011-2019) and finally Full Professor since 2019. Endriss's research focuses on formal methods in AI, particularly in multiagent systems and knowledge representation, with special interest in computational social choice—the intersection of AI with economics and political science. His work spans voting theory, fair division, participatory budgeting, and game theory. He is actively involved in the ADDI project on digital democracy and regularly contributes to major AI conferences including AAMAS, IJCAI, and AAAI. His recent publications demonstrate a strong focus on computational social choice, with particular emphasis on voting systems, participatory budgeting mechanisms, and the theoretical foundations of collective decision making. His research combines theoretical rigor with practical applications in democratic processes and resource allocation problems. Runner-up for the Best Paper Award (2023) Best Paper Award (2016) Best Paper Award (2012) Best Paper Award (2005) Finalist for the Best Paper Award (2014) Finalist for the Best Paper Award (2008) IJCAI-JAIR Best Paper Prize 2016 Endriss regularly teaches courses on Computational Social Choice and Game Theory for MSc Logic and MSc AI programmes. He makes all his teaching materials openly available, consistent with his commitment to open access in both research and education. He has supervised numerous Master's theses that have led to published research. His work extends to outreach through platforms like Game-Academy.org and Pabuviz.org, which help explain complex voting concepts to broader audiences.

• Computer Science
• Mathematics
• Social Sciences
• +۶ مورد دیگر

J. M. Meylahn is an Assistant Professor at the University of Twente, affiliated with the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) and the Applied Mathematics Department's Stochastic Operations Research group (EEMCS-AM-MOR). Their research focuses on multiagent learning and interdisciplinary intersections of computer science, mathematics, and social sciences. Expertise: Reinforcement Learning, Social Dilemma, Learning Algorithm, Interaction, Organisations Education: Theoretical Physics (Stellenbosch University), Mathematics PhD (Leiden University, 2019) Research interests: Multiagent systems, stochastic operations research, learning algorithms in social contexts