جست‌وجوی استاد و پژوهشگر

• Algorithms
• Game Theory
• Automata Theory
• +۷ مورد دیگر

Marcin Jurdzinski is an Associate Professor (Reader) in the Department of Computer Science at the University of Warwick , UK. He has been a faculty member since 2004 and is a core member of the Foundations of Computer Science and Discrete Mathematics and its Applications research groups. University: University of Warwick School: Faculty of Science Department: Department of Computer Science Position: Associate Professor (Reader) Email: Marcin.Jurdzinski@warwick.ac.uk Office: CS2.19 His research lies at the intersection of algorithms, game theory, automata, and logic , with a strong emphasis on formal verification , model checking , and theoretical computer science . He is best known for his foundational work on parity games , including the development of small progress measures and discrete strategy improvement algorithms. The recent publications reveal a consistent focus on computational complexity in games and verification. Key themes include stochastic games, timed automata, bisimilarity, and quantitative analysis . His work often bridges theoretical insights with practical verification challenges, especially in real-time and probabilistic systems. He has supervised several PhD students and hosted postdoctoral researchers such as Laure Daviaud and Alexander Kozachinskiy. He has led EPSRC-funded projects including Solving Parity Games in Theory and Practice and Counter Automata: Verification and Synthesis . PhD Students: Aditya Prakash, Thejaswini K. S., Michail Fasoulakis, John Fearnley, Michal Rutkowski, Ashutosh Trivedi Postdocs: Laure Daviaud, Alexander Kozachinskiy He is actively involved in the academic community, serving on the steering committee of the Highlights of Logic, Games and Automata conference and on program committees for major venues such as CONCUR, ICALP, and LICS. He has also organized workshops including FORMATS and ICALP co-located events.

Lionel Levineمشاهده پروفایل

استاد

• Applied Mathematics
• Combinatorics and Discrete Geometry
• Probability and Statistics
• +۴ مورد دیگر

Lionel Levine is a Professor in the Department of Mathematics at Cornell University, affiliated with the College of Arts and Sciences. His academic research focuses on abelian networks, interacting particle systems, and the emergence of complex patterns from simple rules. He has held prestigious fellowships, including the Simons Fellowship and Sloan Research Fellowship, and has been honored with an endowed professorship. Levine's work bridges probability theory, combinatorics, and statistical physics, with notable contributions to the study of sandpile models and internal diffusion-limited aggregation (IDLA). Education: Ph.D. in Mathematics (2007), University of California, Berkeley. Research Interests: Applied Mathematics, Combinatorics, Probability, Abelian Networks, Sandpile Models, and their intersections with computer science and statistical physics. His research explores how local rules generate large-scale structures, such as in abelian networks and sandpile models. Awards and Honors: Simons Fellowship, Sloan Research Fellowship, Endowed Professorship in the College of Arts and Sciences. Teaching: Courses include Probability Theory (MATH 6710/6720), Topics in Probability: Math for AI Safety (MATH 7710), and undergraduate mathematics courses like Strategy, Cooperation, and Conflict (MATH 1340). Grants and Funding: Supported by the National Science Foundation (NSF), Simons Foundation, Sloan Foundation, and Institute for Advanced Study. Collaborations: Collaborates with prominent researchers such as Yuval Peres, Cris Moore, and Jim Propp. His work has been published in leading journals like the Annals of Probability and Duke Mathematical Journal. Future Work: Continues investigating AI safety, causal models, and multi-agent learning, including research on mathematical frameworks for transformer circuits and hidden incentives in AI systems.

James Martinمشاهده پروفایل

مدرس

• Probability Theory
• Statistical Physics
• Random Graphs
• +۹ مورد دیگر

James Martin is a Lecturer at the Department of Statistics, University of Oxford . He is affiliated with St Hugh's College and has been actively involved in organizing probability seminars since 2018. Research Interests Probability theory Random graphs and percolation Interacting particle systems Models of random growth and coagulation-fragmentation Queueing networks Combinatorial games Teaching Courses: Prelims Probability , Part A Probability , Part B Statistical Lifetime Models , Part C Probabilistic Combinatorics His publications focus on probability theory , statistical physics , and combinatorial structures . Recent work includes studies on last-passage percolation, multispecies exclusion processes, and integrable probability models. James Martin collaborates with researchers from institutions such as Uppsala University, University of Cambridge, Imperial College London, and Kyoto University. He has been a key organizer for the Oxford Probability Seminar since 2018.

• Economic Theory
• Behavioral Economics
• Mechanism Design
• +۷ مورد دیگر

Shengwu Li is a Professor of Economics at Harvard University, specializing in economic theory and behavioral economics. His research focuses on designing simple and transparent economic systems, particularly addressing computational complexity challenges. He has contributed to mechanism design, auctions, and market design, emphasizing cognitive simplicity and bounded rationality. Key research interests include obviously strategy-proof mechanisms, cursed equilibrium extensions, and the effects of salary benchmarking. His work spans dynamic matching markets, fairness in bargaining, and the ethical dimensions of market design. Awards: Aliprantis Prize (2017), Exeter Prize (2018), EC'18 SIGecom Best Paper Award Notable Projects: Salary benchmarking studies, cursed equilibrium dynamics, and fair bargaining norms Literature Contributions: Maintains a curated page on obviously strategy-proof mechanisms and related literature His research integrates theoretical insights with empirical data, addressing real-world applications in labor markets, auctions, and negotiation systems.

• Algorithms
• Combinatorics
• Computational Complexity
• +۴ مورد دیگر

Xavier Molinero Albareda is a Professor at the University of Politècnica de Catalunya (UPC) , affiliated with the Terrassa Faculty of Optics and Optometry (FOOT) and the Department of Mathematics . He is a core member of the ALBCOM Research Group (Algorithms, Bioinformatics, Complexity and Formal Methods) and the GRTJ Research Group (Game Theory). Education: Holds a degree in Mathematics and a Doctorate in Mathematics from UPC. His academic career has been continuous with no indication of retirement or former status. Research Interests: Focuses on Algorithms , Combinatorics , Computational Complexity , and Game Theory , with applications to Social Networks . His work bridges theoretical foundations with practical applications in areas like voting systems, network analysis, and cognitive science. Recent projects include studies on typeface legibility, influence games in signed networks, and optimization of weighted voting mechanisms. Grants & Projects: Involved in competitive R&D projects such as ALGECOM (Algorithmics and Combinatorics) and ALINEX (Algorithms: Engineering and Experimentation). Collaborates on interdisciplinary initiatives like Complex Networks and Social Influence Analysis . Labs/Teams: Leads the Game Theory and Social Networks subgroup within ALBCOM, focusing on computational models for strategic interactions and network dynamics.

• Algorithmic Game Theory
• Stochastic Games
• Distributed Systems
• +۵ مورد دیگر

Hugo Gimbert is a Researcher at the LaBRI (Laboratoire Bordelais de Recherche en Informatique) within the Méthodes Formelles Team . His work bridges computational theory and practical applications, focusing on algorithmic game theory, stochastic processes, and formal methods in computer science. Research interests include: Decidability problems in distributed and stochastic games Partial observation in multi-player systems Cooperation and competition in bridging scenarios Social choice theory implementation Precision farming automation Probabilistic logics and humanoid robot control via MDPs Advising roles: PhD advisor for Soumyajit Paul, Edon Kelmendi, Quentin Rouxel, and Ludovic Hofer PhD co-advisor for Simon Mauras Former advisor for Youssouf Oualhadj Key projects: Stamina - Stabilisation monoids and regular language analysis Marmotte - CNRS committee digitalization platform Rhoban System - Real-time robotics for agriculture and soccer Parcoursup - Algorithmic college admission system for French government

Montserrat Pons Vallèsمشاهده پروفایل

استاد

• Game Theory
• Voting Systems
• Operations Research
• +۳ مورد دیگر

Montserrat Pons Vallès is a Senior academic at the Universitat Politècnica de Catalunya (UPC), affiliated with the Escola Politècnica Superior d'Enginyeria de Manresa (EPSEM) and the Departament de Matemàtica Aplicada III. She holds a Bachelor’s in Mathematics and a Doctorate in Mathematics, specializing in Game Theory and Voting Systems. Her research focuses on power indices, voting systems design, cooperative game theory, and applications to social choice and reliability systems. She is part of the GRTJ (Game Theory Research Group) at UPC, a leading team in mathematical and computational studies of decision-making processes. Her work integrates theoretical game theory with practical applications in operational research and reliability engineering. Notable contributions include extending Banzhaf indices for multi-level voting, analyzing power structures in weighted voting systems, and developing measures for component importance in reliability systems. She has collaborated extensively with Prof. Josep Freixas on topics like decisiveness indices, success metrics in voting, and probabilistic power analysis. Over 94 documented activities, Pons has published in journals like Annals of Operations Research and Theory and Decision, and presented at conferences such as the European Conference on Operational Research. Her projects include国家级 funded research on mathematical models for voting and cooperation in social networks and political science. Despite no listed awards, her h-index of 4.0 reflects sustained scholarly contribution. She advises on reliability systems and voting mechanisms, contributing to both academic and applied domains.

Yann Strozeckiمشاهده پروفایل

دانشیار

• Enumeration Complexity
• Algorithmic Game Theory
• Simple Stochastic Games
• +۷ مورد دیگر

Yann Strozecki is an Associate Professor (Maître de Conférences HDR) at the University of Versailles Saint-Quentin, where he is based in the DAVID Laboratory and leads the ALMOST research team focused on algorithms and stochastic models. He is currently on a part-time assignment at LIGM, Gustave Eiffel University, and has previously held positions at LIP6 (RO team), Paris-Sud University (ALGO team), and completed a postdoctoral fellowship at the University of Toronto's Theory Group. He earned his PhD from Paris Diderot (Paris 7) under Arnaud Durand. His research lies at the intersection of theoretical computer science and discrete mathematics, with core interests in: Enumeration complexity, especially delay and space constraints Algorithmic game theory, particularly simple stochastic games (SSGs) Graph and matroid algorithms Cheminformatics and molecular structure generation Sparse polynomials and algebraic complexity Analysis of his recent publications reveals a strong trend in developing efficient enumeration algorithms with provable delay and space bounds, advancing the theoretical foundations of output-sensitive computation. He also contributes to practical algorithms for Cloud RAN scheduling and cheminformatics, often combining theoretical rigor with real-world applications. His work on geometric amortization and strategy improvement in SSGs demonstrates innovation in algorithm design. Notable scientific contributions include: Generic strategy improvement methods for SSGs Polynomial-delay enumeration via closure operations Efficient deterministic scheduling for low-latency networks Tools for molecular cage generation in chemistry Yann Strozecki actively supervises PhD and master’s students, including Noé Demange, Maël Guiraud, and Xavier Badin de Montjoye. He co-organizes the ALMOST team seminar and has advised numerous interns in algorithmics and game theory. His research has been supported through collaborations with Nokia Bell Labs (CIFRE thesis) and interdisciplinary projects in cheminformatics and networking.

Kevin J.S. Zollmanمشاهده پروفایل

استاد

• Game Theory
• Agent-Based Modeling
• Philosophy of Science
• +۴ مورد دیگر

Kevin J.S. Zollman is the Herbert A. Simon Professor of Philosophy and Social and Decision Sciences at Carnegie Mellon University, housed in the Dietrich College of Humanities and Social Sciences. He directs the Institute for Complex Social Dynamics and holds affiliations with the University of Pittsburgh’s Center for Philosophy of Science and Ludwig-Maximilians Universität’s Munich Center for Mathematical Philosophy. He earned a Ph.D. and M.A. in Philosophy from the University of California, Irvine, and a B.S. in Philosophy from Kansas State University. His research integrates game theory, agent-based modeling, and philosophy of science to study social behavior across biological and cultural systems. Key areas include the evolution of ethical norms like cooperation/fairness, epistemic community design, and signaling theory applications in science and religion. Zollman’s work bridges academia and public engagement, exemplified by his popular book The Game Theorist’s Guide to Parenting , co-authored with Paul Raeburn. His articles (e.g., 'Honest Signalling Made Simple', 'Network Epistemology') explore topics like evolutionary dynamics, scientific peer review, and hybrid equilibria in signaling systems. He teaches philosophy, logic, and decision sciences at both undergraduate and graduate levels. As a leader in complex social systems research, Zollman’s contributions span theoretical and applied domains, emphasizing interdisciplinary methodologies to address collective learning and ethical behavior.

Christos Tzamosمشاهده پروفایل

دانشیار

• Computer Science
• Machine Learning
• Statistical Learning
• +۳ مورد دیگر

Christos Tzamos is an Associate Professor in the Department of Informatics and Telecommunications at the National and Kapodistrian University of Athens, and a researcher at Archimedes AI. He received his PhD from MIT and BS from National Technical University of Athens. His research bridges computer science, machine learning, statistics, and algorithmic economics. Research Focus: Machine learning theory, algorithmic mechanism design, optimization, and statistical methods with applications to economics. Current projects include active learning, adaptive information acquisition, and robust algorithm design. Awards: NSF CAREER Award (2022), NeurIPS Outstanding Paper Award (2019), George Sprowls Award for best CS PhD thesis at MIT (2017), multiple programming competition medals. Student Advising: Currently advising 4 PhD students and 1 postdoc, with 3 graduated PhD students now at Georgia Tech, Yale, and UT Austin.

Daniel Karapetyanمشاهده پروفایل

استادیار

• Combinatorial Optimization
• Artificial Intelligence
• Data Science
• +۱۷ مورد دیگر

Daniel Karapetyan is an Assistant Professor at the School of Computer Science , University of Nottingham, and a member of the Computational Optimisation and Learning Lab . His research spans Artificial Intelligence , Data Science , Operational Research , and Optimization , with applications in transportation , logistics , satellite mission planning , and access control . Education: PhD in Computer Science, Royal Holloway, University of London (2007–2010) BSc/MSc in Computer Science, Bauman Moscow State Technical University (2001–2007) His research interests focus on the automated design of heuristic algorithms , multi-objective optimization , and parameter tuning for machine learning and combinatorial problems. He integrates Large Language Models (LLMs) and hyperparameter optimization into practical systems, addressing real-world challenges in airport sequencing , TV ad scheduling , and electric vehicle range prediction . Notable scientific contributions include the CORS Practice Prize (2014) for ferry scheduling work and pioneering fixed-parameter algorithms in security-related optimization problems. His publications emphasize combinatorial optimization , Markov Chain methods , and automated algorithm configuration . Teaching roles include module convener for COMP3008: Knowledge Representation and Reasoning , personal tutoring for COMP1002 , and supervision of COMP2002: Software Engineering Group Project . He also offers PhD supervision in areas like AI for optimization , interpretability in ML , and emergency department coordination .

Adrian Vladuمشاهده پروفایل

پژوهشگر

• Optimization
• Convex Geometry
• Continuous Optimization
• +۴ مورد دیگر

Adrian Vladu is a permanent researcher at CNRS, affiliated with the Institute of Research in Fundamental Computer Science (IRIF) at Université Paris Cité. He holds a PhD in Mathematics from MIT (2017), advised by Jonathan Kelner and Aleksander Mądry, followed by postdoctoral work at Boston University. His research focuses on optimization (convex/non-convex) and deep learning, emphasizing algorithm design with provable guarantees. Recent work explores refining interior point methods and scalable training techniques for deep models. Education: PhD in Mathematics (MIT, 2017); Postdoctoral Associate (Boston University). Research interests include combining convex geometry, continuous optimization, and linear algebra to address discrete problems. He also investigates deep learning's theoretical underpinnings, particularly generalization and training efficiency. Current projects aim to develop simple, implementable algorithms with strong theoretical foundations. Grants: Supported by CNRS and the French National Research Agency. Job Market: Actively seeking tenure-track faculty or industry research roles in optimization, algorithms, or machine learning. Notable contributions include STOC/FOCS/SODA publications on optimization algorithms and ICLR/ICML work on adversarial attacks and distributed training.

• Applied Stochastic Process
• Optimization
• Operations Research

Hiroaki Mohri is a Professor at Waseda University's School of Commerce, where he has been serving since 2023 after previously holding positions as Associate Professor (2001-2022) and Assistant Professor (1999-2001). He earned both his Master of Science and Doctor of Engineering degrees from Tokyo Institute of Technology. His academic career includes visiting professorships at the University of Bonn Research Institute for Discrete Mathematics (2005-2007). Waseda University, Professor (2023-present) Waseda University, Associate Professor (2001-2022) Waseda University, Assistant Professor (1999-2001) University of Bonn, Visiting Professor (2005-2007) Mohri's research spans applied mathematics with a focus on stochastic processes, optimization, and operations research. His work demonstrates strong interdisciplinary connections between mathematical theory and practical applications in network reliability, financial securities, and infrastructure management. He has made significant contributions to cooperative game theory applications in network design problems and reliability engineering. His publication record shows a consistent research trajectory with recent work focusing on catastrophic failure models, network reliability evaluation, and damage analysis from multiple shock types. Mohri has successfully bridged theoretical mathematics with practical applications in infrastructure management, political conflict analysis, and financial systems. His research demonstrates how mathematical modeling can address complex real-world problems across diverse domains. Mohri is an active member of several professional organizations including the Mathematical Association of America, Game Theory Society, Japan Society for Industrial and Applied Mathematics, and the Operations Research Society of Japan. He has led numerous research projects including 'An Interdisciplinary Study on the Effect of Non-Military Engagement in Preventing Escalation of Conflicts' and 'International involvement in escalating conflicts: Mediation theory and the case of the former Soviet Union.' Additionally, he has organized international student exchange programs to former Soviet Union countries, focusing on international relations, logistics, and multicultural societies.