جست‌وجوی استاد و پژوهشگر

Martin Vatshelleمشاهده پروفایل

دانشیار

• Graph Algorithms
• Parameterized Algorithms
• Algorithm Engineering
• +۹ مورد دیگر

Martin Vatshelle is an Associate Professor in the Department of Informatics at the University of Bergen (UiB) , Norway. He obtained his PhD from UiB in 2012 with a thesis titled New Width Parameters of Graphs . His research is centered on theoretical computer science, particularly in the design and analysis of graph algorithms. His main research interests include: Graph Algorithms Parameterized and Fixed-Parameter Tractable (FPT) Algorithms Algorithm Engineering Graph Theory, especially width parameters like boolean-width, clique-width, and branch decompositions Dynamic programming on structured graphs The recent publications of Martin Vatshelle reflect a strong focus on structural graph theory and algorithmic efficiency. His work frequently explores the computational complexity of graph problems, leveraging width parameters to design faster exact or parameterized algorithms. Themes such as boolean-width bounds, vertex partitioning, and satisfiability problems (#SAT, MaxSAT) are recurrent, indicating a deep engagement with both theoretical foundations and practical algorithmic improvements. There are no scientific awards mentioned in the provided texts. Martin Vatshelle has taught a variety of courses in algorithms, discrete mathematics, and complexity theory since 2004, including Algorithms, Data Structures and Programming , Complexity Theory , and Algorithm Engineering . There is no mention of research grants or supervised students in the provided materials. He collaborates extensively with researchers such as Jan Arne Telle and Sigve Hortemo Sæther. He is affiliated with the research group on Didactics within the Department of Informatics. No separate lab or research center is mentioned.

• Optimization
• Cryptography
• Artificial Intelligence
• +۴ مورد دیگر

Chu Min LI is a University Professor at the University of Picardy Jules Verne (UPJV), working in the Modélisation, Information et Systèmes (MIS) laboratory (UR UPJV 4290). Their research focuses on Optimization, Cryptography, and Artificial Intelligence, with particular expertise in MaxSAT (Maximum Satisfiability), Constraint Programming, and Combinatorial Optimization. Professor LI's research spans theoretical and applied computational problem solving. Key research areas include: MaxSAT and MinSAT solving techniques Constraint programming and satisfaction Combinatorial optimization algorithms Geometric packing problems AI-driven optimization methods Theoretical foundations of satisfiability Analysis of Professor LI's publications from 2023-2025 reveals a strong focus on advancing MaxSAT solving techniques with diverse applications including conference scheduling, assembly line balancing, and geometric packing problems. Their work consistently bridges theoretical insights with practical algorithmic improvements, demonstrating both depth in theoretical understanding and relevance to real-world problems across multiple domains. Professor LI has received significant recognition for their contributions, including a Best Paper Award at CP 2021 (27th International Conference on Principles and Practice of Constraint Programming). Professor LI leads substantial research projects including 'BforSAT' (Branching for SAT and beyond) and 'Massal'IA' (Propositional reasoning for large-scale optimization), indicating significant research funding and leadership. Their extensive collaborative network includes researchers such as Felip Manyà, Kun He, Jiongzhi Zheng, and Sami Cherif, suggesting an active research group and international connections.

Olivier Bailleuxمشاهده پروفایل

استاد پژوهشی

• Constraint Programming
• Stochastic Local Search
• Genetic Algorithms
• +۳ مورد دیگر

Olivier Bailleux is a Research Professor at the University of Burgundy within the Faculty of Science and Technology . His work focuses on computational logic and optimization. Teaching: C/C++ programming, constraint programming, logical programming Research: SAT resolution, constraint decomposition, genetic algorithms Team: Data Science Research Interests: SAT solvers, constraint programming, and algorithmic optimization. His projects explore efficient translations of complex constraints into Boolean models. Publications span topics like Pseudo-Boolean encoding, DPLL/CDCL algorithm comparisons, and minimal resolution refutations, reflecting interdisciplinary work in logic and artificial intelligence.

• Formal Methods
• Model Checking
• Satisfiability (SAT) Solving
• +۴ مورد دیگر

Tommi Junttila serves as a Senior University Lecturer in the Department of Computer Science at Aalto University, Finland, where he conducts cutting-edge research at the intersection of formal methods and computational logic. His academic profile demonstrates sustained contributions to theoretical computer science with practical applications in system verification and blockchain technology. His research program centers on advancing formal verification techniques, with core expertise in: Symmetry reduction algorithms for state space explosion SAT/SMT solving with specialized parity and XOR reasoning Bounded model checking of timed and asynchronous systems Blockchain protocol verification (notably DeFi lending pools) Canonical labeling tools for graph automorphism detection Recent work shows increasing focus on decentralized finance applications while maintaining foundational contributions to solver technology. Analysis of his publication trajectory (2011-2022) reveals consistent innovation in SAT solving methodologies, with symmetry reduction and parity reasoning forming persistent research threads. His 2022 work on DeFi lending pools represents a strategic expansion into blockchain verification, leveraging established formal methods expertise for emerging financial technologies. Tool development (bliss, PySMT) demonstrates commitment to practical research impact. No scientific awards were documented in the source materials. Similarly, no information regarding student supervision, grant funding, or laboratory affiliations was present in the provided text. His independent tool development (including bliss for graph canonical labeling and PySMT for SMT solver interfaces) indicates significant technical leadership within the formal methods community.

Jens Opitzمشاهده پروفایل

استاد

• Transportation Systems
• Railway Timetabling
• Optimization Algorithms
• +۳ مورد دیگر

Jens Opitz is a Professor at the Faculty of Transportation Science at Technical University of Dresden, where he is based at Hettnerstraße 1, 01069 Dresden (Room POT 105). He teaches courses including Theory of Transportation Systems and Statistics, Reliability Theory, Advanced Theory of Transportation Systems, Surface Transport Aviation and Simulations, and Actual Aspects in Optimization of Processes in Transportation and Logistics. His research focuses on transportation systems optimization, particularly in railway operations. Dr. Opitz has developed significant methods for generating synchronized timetables, integrating freight traffic into passenger timetables, and optimizing rail network operations. His work bridges theoretical optimization approaches with practical railway operations challenges, with applications in both passenger and freight rail transport. Dr. Opitz's publication record shows a strong focus on railway timetable optimization, with recurring themes in periodic scheduling, conflict resolution, and capacity utilization. His research has evolved from foundational work on modulo network simplex methods to more recent applications in complex railway station track allocation and integrated freight-passenger timetable planning. The publications demonstrate expertise in both theoretical algorithm development and practical implementation of railway optimization systems. His key research projects include Timetabling, Enhancement of existing methods for the generation of synchronized timetables, Integration of freight traffic into the generation of synchronized timetables, and Algorithms for synchronized timetable in railway traffic. These projects reflect his dedication to improving railway operations through advanced optimization techniques and software implementations like the TAKT program system for automatic routing in railway networks.

Paul Beameمشاهده پروفایل

استاد

• Computational Complexity
• Proof Complexity
• Satisfiability (SAT) Solving
• +۱۱ مورد دیگر

Paul Beame is a Professor and Associate Director for Facilities at the Paul G. Allen School of Computer Science & Engineering (University of Washington). He earned his B.Sc. in Mathematics (1981) , M.Sc. in Computer Science (1982) , and Ph.D. in Computer Science (1987) from the University of Toronto, followed by postdoctoral work at MIT (1986-87). His research spans computational complexity , proof complexity , quantum computing , and formal verification , with applications to databases and AI. Research Interests : Computational complexity theory, proof complexity, SAT-solving, quantum algorithms, time-space tradeoffs, communication complexity, circuit complexity, knowledge representation, probabilistic inference. Recent Publications : Focus on quantum time-space tradeoffs, multiparty communication complexity, formal verification of nonlinear arithmetic, and lower bounds for circuit and proof systems. Articles appear in ACM Transactions on Computation Theory , SIAM Journal on Computing , and conferences like STOC, FOCS, and NeurIPS. Teaching & Service : Active in theoretical computer science education and professional service, including program committee roles and tutorials. Personal : Engages in sports like squash and softball.

• Optimization
• Metaheuristics
• Artificial Intelligence
• +۳ مورد دیگر

Noureddine Bouhmala is an Associate Professor in the Department of Information and Communication Technology at the University of Agder. His research focuses on optimization algorithms, metaheuristics, and their applications to combinatorial problems such as MAX-SAT, constraint satisfaction, and clustering. He is affiliated with the CAIR Centre for Artificial Intelligence Research. Research interests include evolutionary algorithms, multilevel paradigms, and hybrid metaheuristics. Notable work involves developing algorithms for continuous optimization, predictive maintenance, drone traffic planning, and SAT-encoded industrial problems. He has collaborated with researchers across disciplines, including engineering, logistics, and emergency evacuation modeling. His publications span journals like Journal of Heuristics , IEEE Transactions , and Applied Intelligence , with contributions to conferences such as IntelliSys, ICCSA, and SITA. His work emphasizes algorithmic innovation and real-world problem-solving in domains like logistics, smart cities, and computational science.

Michael Geneserethمشاهده پروفایل

استاد

• Computational Logic
• Enterprise Management
• Computational Law
• +۴ مورد دیگر

Michael Genesereth is a Professor of Computer Science at Stanford University and a professor by courtesy in the Stanford Law School. He serves as director of the Logic Group at Stanford and is the founder and research director of CodeX - the Stanford Center for Legal Informatics. Genesereth is renowned for his groundbreaking work on Computational Logic and its diverse applications in Enterprise Management, Computational Law, and General Game Playing. His academic journey includes an Sc.B. in Physics from M.I.T. and a Ph.D. in Applied Mathematics from Harvard University (1978). These foundational studies paved the way for his influential career at the intersection of logic, computer science, and law. Genesereth's research program spans from theoretical foundations of logic programming to practical implementations across multiple domains. His work on General Game Playing has established frameworks enabling AI systems to understand and play games based purely on logical descriptions of rules. In Computational Law, he pioneers approaches for representing legal rules in machine-processable formats to automate compliance checking and legal reasoning. His Logic For All initiative has successfully introduced logic education to high schools across the United States, with teachers reporting significant improvements in students' preparedness for college-level coursework. The publication pattern reveals a sustained research trajectory focused on logic foundations, with recent work expanding into practical applications in computational law, insurance portfolio management, and knowledge representation systems. His 2022-2025 publications demonstrate continued innovation in logic programming frameworks and their real-world implementations. Genesereth has founded multiple technology companies including Teknowledge, CommerceNet, Mergent Systems, and Symbium, translating theoretical work into practical solutions. His educational impact extends through widely adopted textbooks and his free massive open online course (MOOC) on Introduction to Logic, which has enrolled hundreds of thousands of students globally. His current initiatives include the International Logic Olympiad, launched in 2024, which engages high school students worldwide in logic problem-solving competitions. This effort builds on his observation that high school students consistently perform well in his university-level logic courses, demonstrating the readiness of secondary students for formal logic education.

• SAT Solvers
• Reinforcement Learning
• Machine Learning
• +۳ مورد دیگر

Chunxiao Li is a Sessional Lecturer at the University of Waterloo. Their research focuses on SAT solvers, reinforcement learning, and computational complexity. Key areas include CDCL algorithms, proof complexity, and machine learning applications in optimization. Research interests revolve around improving SAT solver efficiency through theoretical analysis and algorithmic innovations. Notable work explores restart policies, clause learning, and hierarchical structures in Boolean formulas. Publications emphasize bridging machine learning with SAT solving, analyzing solver performance through complexity-theoretic lenses, and developing practical algorithmic improvements. No scientific awards or grants are explicitly mentioned. No advising relationships or laboratory affiliations are provided in the text.

Thibault Lejembleمشاهده پروفایل

دانشیار

• 3D Point Cloud Analysis
• Pattern Recognition
• Curvature Estimation
• +۲ مورد دیگر

Thibault Lejemble is an Associate Professor at EPITA specializing in 3D data analysis. His research develops efficient algorithms for processing large point clouds from LiDAR and photogrammetry, with applications in pattern recognition, reconstruction, and GPU-accelerated computing. Current investigations focus on curvature estimation, discrete topology, and relationships between mathematical morphology and topological data analysis. Publications showcase innovations in point cloud processing libraries, neural networks for edge detection, and differential estimators, reflecting consistent advancement in computational geometry and real-time 3D data analysis techniques.

Leslie Ann Goldbergمشاهده پروفایل

استاد

• Algorithms
• Complexity Theory
• Randomized Algorithms
• +۶ مورد دیگر

Leslie Ann Goldberg is Professor of Computer Science at the University of Oxford and Senior Research Fellow at St Edmund Hall. She has held academic positions at the University of Liverpool (2006-2013) and the University of Warwick (1995-2006), and previously worked at Sandia National Labs (1992-1995). Currently serving as Head of Department (sabbatical planned for 2025-26), she leads research in theoretical computer science with focus on algorithms and complexity theory. Her research interests span algorithms for approximately counting and randomly sampling combinatorial structures , analysis of Markov-chain based sampling algorithms , complexity of counting , and stochastic processes in computer science . She specializes in randomized algorithms, particularly their mathematical analysis regarding runtime and accuracy. Current projects include contentions resolution via backoff protocols, random sampling and approximate counting algorithms, counting complexity theory, and analyzing processes on networks like the Moran process. Professor Goldberg has published over 100 papers in top theoretical computer science venues, with recent work focusing on spin systems, graph homomorphisms, subgraph counting, and network processes. Her publications show consistent output in premier venues including ICALP (where she has won three Best Paper Prizes), SODA, STOC, and RANDOM. ERC Advanced Grant 'Mapping the Complexity of Counting' (2014-2019) Best Paper Prize at ICALP 2012, 2010, and 2006 UK Distinguished Dissertations in Computer Science (1991-1992) She actively supervises PhD students and collaborates with researchers including Andreas Galanis, Marc Roth, John Lapinskas, and Paulina Smolarova. Her work bridges theoretical computer science with statistical physics, combinatorics, and network theory, with applications to database systems, evolutionary dynamics, and communication protocols.

• Constraint Programming
• Optimization Algorithms
• Artificial Intelligence
• +۳ مورد دیگر

Peter Nightingale is a Senior Lecturer in Artificial Intelligence at the Department of Computer Science, University of York. His research focuses on constraint satisfaction and optimization, including applications in design, resource allocation, planning, and combinatorial mathematics. He holds a Ph.D. in Computer Science from the University of St Andrews. Before joining York, he was a Senior Research Fellow at St Andrews (2007–2018) and served as a Lecturer at York from 2018 to 2023. His work emphasizes improving constraint model representations and automating solver design through tools like Conjure and Savile Row. His key research areas include constraint programming, automated modelling, and optimization algorithms. He contributes to foundational techniques in SAT encoding selection, local search methods (Athanor), and constraint solver architecture (Dominion). Peter’s work bridges theoretical advancements with practical applications in scheduling, statistical inference, and combinatorial problem-solving. His recent publications highlight innovations in automated constraint model reformulation, graph convolutional networks for argumentation frameworks, and cross-paradigm modelling techniques. These efforts aim to enhance computational efficiency and broaden the applicability of constraint-based methods across diverse domains.

• Computer Science
• Algorithms
• Constraint Satisfaction Problems (CSP)
• +۴ مورد دیگر

Dr. Oliver Kullmann is an Associate Professor in the Department of Computer Science at Swansea University, Faculty of Science and Engineering. His work focuses on theoretical computer science, particularly in satisfiability (SAT) solving, constraint satisfaction problems, and algorithm design. He has contributed to advancements in SAT-solving techniques like Cube-and-Conquer and has published extensively on topics such as quantified Boolean formulas, minimal unsatisfiable subformulas (MUSes), and parallel computing. Research Interests: Dr. Kullmann’s research spans algorithmic approaches to SAT and CSP, including the development of efficient solving methods, formal verification, and parallel computing optimizations. His work emphasizes practical applications of theoretical results, such as the Boolean Pythagorean Triples problem and GPU-accelerated algorithms for combinatorial problems like the N-Queens puzzle. Publications highlight his contributions to SAT theory and applications, with a focus on foundational aspects like autarkies, clause-set minimization, and hypergraph-based techniques. His work also integrates interdisciplinary methods, such as leveraging linear algebra and graph theory for SAT decision problems. Dr. Kullmann supervises PhD and MRes students in areas including SAT solving algorithms, general-purpose programming languages, and verification tools. He teaches modules such as Algorithms (CS-270) and the Logic and Computation Project (CS-700). His research platform, the OKlibrary, supports holistic SAT-solving research.

Ruben Martinsمشاهده پروفایل

استادیار

• Program Synthesis
• Software Verification
• Security
• +۷ مورد دیگر

Ruben Martins is an Assistant Professor at Carnegie Mellon University, focusing on constraint programming, program synthesis, analysis, and verification. His work aims to enhance programmer productivity and automate data science tasks through synthesis techniques. Education: Ph.D. (2013) from Technical University of Lisbon; Postdoc at University of Oxford (2014-2015) and UT Austin (2015-2017). Research Interests: Program Synthesis, Software Verification, Security, Decision Procedures, Boolean Satisfiability, MaxSAT, and their applications in real-world optimization. Article Trends: Recent publications emphasize integrating large language models (LLMs) with synthesis techniques for automated repair and refactoring, alongside advancements in MaxSAT solvers like Open-WBO. His work spans venues such as POPL, PLDI, FSE, and SAT. Scientific Awards: Distinguished Paper Award at PLDI 2018; Gold Medals in MaxSAT Competitions for Open-WBO. Current Roles: Committee Member in OOPSLA Review Committees across multiple conferences.

Marijn Heuleمشاهده پروفایل

دانشیار

• Satisfiability (SAT) Solving
• Formal Verification
• Combinatorial Mathematics
• +۵ مورد دیگر

Marijn Heule is an Associate Professor in the Computer Science Department at Carnegie Mellon University. He received his PhD from Delft University of Technology in the Netherlands. His academic career has been focused on advancing the theory and practice of satisfiability (SAT) solving and its applications. Dr. Heule's research primarily centers on solving hard combinatorial problems in formal verification, number theory, and extremal combinatorics. His work has made significant contributions to both theoretical foundations and practical implementations of SAT solvers. He has developed award-winning SAT solvers, and his preprocessing techniques are incorporated into state-of-the-art SAT solvers used worldwide. His current research focuses on two major challenges: exploiting high-performance computing for SAT solving and validating results from SAT solvers and related tools. Dr. Heule pioneered the "cube-and-conquer" paradigm, a novel parallel SAT solving approach that enables linear time speedups on many hard problems. His first publication on this topic won the best paper award at HVC 2011. He also designed a new proof format with a corresponding fast proof checker for SAT and QBF solvers. This proof logging format has been mandatory for SAT Competitions since 2013, significantly increasing confidence in tool correctness. His work on the Boolean Pythagorean Triples problem, which produced a 200 TB proof that was validated, demonstrated that proof logging and verification is feasible even for the most complex problems. Dr. Heule is one of the editors of the 900+ page "Handbook of Satisfiability," which has become a standard reference in the SAT community. He serves as an Associate Editor of the Journal on Satisfiability, Boolean Modeling and Computation and previously co-chaired the SAT 2015 conference in Austin. Best paper award at HVC 2011 for cube-and-conquer publication Multiple best paper awards/nominations at major conferences including IJCAR, SAT, TACAS Work featured in New York Times, Quanta Magazine, Nature, and other major media outlets Dr. Heule has advised several PhD students including Emre Yolcu, Joseph Reeves, Bernardo Subercaseaux, Cayden Codel, James Gallicchio, and Amar Shah. He has developed important software tools including DRAT-trim (a proof checking utility), QRAT-trim, and implementations of the cube-and-conquer paradigm that have become standard in the SAT solving community.