جست‌وجوی استاد و پژوهشگر

Stefan Herzogمشاهده پروفایل

پژوهشگر

• Decision-Making
• Artificial Intelligence
• Collective Intelligence
• +۶ مورد دیگر

Stefan Herzog is a Senior Research Scientist and Head of the Research Area Boosting Decision-Making at the Max Planck Institute for Human Development in Berlin. He leads interdisciplinary projects integrating psychology, artificial intelligence, and computational social science to address global challenges like misinformation, climate change, and AI's societal impact. PhD in Psychology (2009, University of Basel) M.Sc. in Psychology (2005, University of Basel) B.Sc. in Psychology (2003, University of Basel) His research focuses on boosting human decision-making through: Hybrid human-AI collective intelligence Strengthening resilience against disinformation Behavioral interventions in digital environments Transparent, non-manipulative policy design Self-nudging strategies Methodological innovation in social science Recent publications emphasize AI ethics , digital sovereignty , and democratic resilience . He has secured significant funding from the EU Horizon program, DFG, and Volkswagen Stiftung. Scientific recognition includes the Hillel Einhorn New Investigator Award (2010).

Philippe Monginمشاهده پروفایل

استاد

• Economics
• Philosophy
• Economic Theory
• +۴ مورد دیگر

Philippe Mongin is a Senior Research Fellow at the Centre National de la Recherche Scientifique (CNRS) and has been a Professor at HEC Paris (School of Economics and Decision Sciences) since 2006. He holds an agrégation in philosophy and a PhD in economic science, with research spanning economic theory, formal logic, and decision-making models. Research Interests: Mongin’s work focuses on instrumental rationality, collective aggregation of judgments and preferences, and formal logic applications in decision theory. His publications span journals like Journal of Economic Theory , Economics and Philosophy , Synthese , Games and Economic Behavior , and Journal of Philosophical Logic .

Ronald de Haanمشاهده پروفایل

استادیار

• Theoretical Computer Science
• Parameterized Complexity Theory
• Artificial Intelligence
• +۸ مورد دیگر

Ronald de Haan is an Assistant Professor at the Institute for Logic, Language & Computation (ILLC) , University of Amsterdam, with primary affiliation in Theoretical Computer Science (TCS) and secondary affiliation in Mathematical & Computational Logic (MCL) . Since December 2019, he has held this position, following a postdoctoral role at the same institution from 2017 to 2019. He completed his PhD at the Algorithms and Complexity Group at Technische Universität Wien in 2016. Education: PhD in Computer Science, Technische Universität Wien (2016) MSc in Computational Logic, European Master's Program in Computational Logic (2010–2012) BSc in Cognitive Artificial Intelligence & BA in Linguistics, Utrecht University (2007–2010) Research Interests: His work lies at the intersection of theoretical computer science and artificial intelligence , with a strong emphasis on parameterized complexity theory . He explores the computational complexity of problems in AI, knowledge representation & reasoning, and computational logic. Specific areas include the Polynomial Hierarchy, subexponential-time complexity, the Exponential Time Hypothesis, and parameterized compilability. Scientific Awards: E.W. Beth Dissertation Prize 2017 for his PhD thesis "Parameterized Complexity in the Polynomial Hierarchy" Shortlisted for the Heinz Zemanek Prize 2018 Nominated for the GI-Dissertationspreis 2016 by the German Informatics Society Teaching & Supervision: He has taught a wide range of courses at the University of Amsterdam, including Computational Complexity , Knowledge Representation and Reasoning , and Recursion Theory for MSc Logic and MSc AI programs. He also supervises student research projects and theses, offering topics in ASP, complexity theory, and logic programming. Academic Service: He has served on the program committees of top-tier AI and logic conferences such as AAAI, IJCAI, KR, ECAI, and AAMAS, and co-organized events like PhDs in Logic VII.

• Decision Support Systems
• Operations Research
• Machine Learning
• +۳ مورد دیگر

Konrad Kułakowski is a Professor at the Department of Applied Informatics within the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering at AGH University of Science and Technology in Kraków. His research spans multiple domains including decision support systems, operations research, and robotics, with a focus on pairwise comparisons methods and their applications in optimization problems and automated systems. Affiliation: AGH University of Science and Technology School: Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering Department: Applied Informatics His research interests center on improving accuracy and resilience in pairwise comparisons methods, detecting manipulation in decision-making processes, and optimizing path planning for automated guided vehicles (AGVs) in constrained environments. His work bridges theoretical advancements in decision analysis with practical applications in robotics, real-time systems, and biomedical engineering. Key trends in his recent publications include: Advancements in heuristic algorithms for pairwise comparisons matrices Applications of Monte Carlo simulations for method validation Path planning optimization for AGVs in irregular layouts Detection of manipulation in peer assessment frameworks Resilient aggregation techniques for secure judgments in AHP

• Decision Theory
• Social Choice Theory
• Multicriteria Decision Making
• +۴ مورد دیگر

Olivier Cailloux serves as a Lecturer at LAMSADE (Laboratoire d'Analyse et Modélisation de Systèmes pour l'Aide à la Décision) within Université Paris-Dauphine, part of PSL University. His academic career spans computer science and decision theory, with significant contributions to the Decision Deck project as a founding member. This open-source initiative provides practical tools for decision-making methodology practitioners and educators. Cailloux's research expertise centers on decision theory and social choice, with particular emphasis on classification aggregation, voting systems, and multicriteria analysis. His work bridges theoretical foundations with practical applications, ranging from economic design principles to bioinformatics implementations. The interdisciplinary nature of his research is evident in collaborations spanning economics, computer science, and molecular biology, particularly in genomic analysis of the BRCA1 gene. His publications demonstrate a consistent focus on formal frameworks for deliberated judgment and robust decision support systems. Analysis of Cailloux's publication record reveals strong trends in computational social choice and decision support methodologies. His recent work (2023-2024) focuses on classification aggregation without unanimity requirements, representing cutting-edge developments in social choice theory. Earlier contributions established foundations for preference modeling with incomplete information and formal frameworks for deliberated judgment. His interdisciplinary approach is particularly notable in bioinformatics applications where decision theory principles are applied to genomic analysis. Cailloux maintains active research collaborations across multiple institutions, as evidenced by his co-authored publications with researchers from diverse fields. His work with the Decision Deck project demonstrates commitment to creating accessible, open-source tools for both academic and practical applications of decision science. The laboratory environment at LAMSADE provides a fertile ground for his interdisciplinary research, connecting theoretical computer science with real-world decision challenges.