جست‌وجوی استاد و پژوهشگر

James Mcquillanمشاهده پروفایل

استاد

• Satisfiability of Boolean expressions
• Combinatorics
• Algorithms
• +۱۴ مورد دیگر

James Mcquillan is a Professor of Computer Science at the School of Computer Sciences , Western Illinois University. His research spans theoretical and applied computer science, with a focus on combinatorial structures and their applications in computational problems. Ph.D. , University of Western Ontario (1994) Book Author : Cryptography, Information Theory, and Error-Correction: A Handbook for the 21st Century (2021, Wiley) Research interests include: Core areas: Satisfiability of Boolean expressions, Combinatorics, Finite geometries, Desargues configurations, Graph labellings, Hyperovals Applications: Cryptography, Error correction, Pattern matching in strings, Bioinformatics Teaching awards highlight his excellence in graduate and undergraduate education. His recent work in Discrete Mathematics (2025) explores graph theory and combinatorial algorithms. Scientific contributions include Every even cycle of order at least 8 has a mirror labeling (2025) Awards : 2020-2021: College of Business and Technology Faculty Award for Excellence in Teaching 2018-2019: School of Computer Sciences Graduate Teacher of the Year 2017-2018: School of Computer Sciences Undergraduate and Graduate Teacher of the Year

• Formal Verification
• Model Checking
• Automated Reasoning
• +۹ مورد دیگر

Georg Weissenbacher is a Full Professor of Computer Science at Vienna University of Technology (TU Wien), working in the Institute of Logic and Computation within the Faculty of Informatics. He leads the Formal Methods in Systems Engineering research group and has established himself as a leading researcher in formal verification and automated reasoning. His educational background includes a DPhil from Oxford University (2008-2010), research at ETH Zürich (2005-2010), and a Master's degree from TU Graz (completed by 2003). He completed his Habilitation at TU Wien in 2016 with a thesis on Logical Methods in Automated Hardware and Software Verification. Weissenbacher's research focuses on developing automated tools for software and hardware verification, with particular emphasis on detecting and explaining bugs in complex systems. He is renowned for his work on heisenbugs - bugs that disappear when analyzed, which are particularly challenging in concurrent and multi-core systems. His research bridges theoretical foundations in logic with practical applications in software engineering, with significant contributions to interpolation-based verification techniques and SAT/SMT solving applications. His recent publications show a clear progression from traditional software verification toward emerging challenges in AI security, neural network verification, and sophisticated concurrency models. The research trajectory demonstrates increasing sophistication in handling complex systems properties, with a growing emphasis on probabilistic guarantees and formal methods applied to modern computing challenges. OOPSLA'18 Distinguished Paper Award for 'Randomized Testing of Distributed Systems with Probabilistic Guarantees' Weissenbacher has advised numerous PhD students and postdocs, including current researchers Mai AL-Zu'bi, Katalin Fazekas, and Sarah Sallinger. His research has been supported by significant grants including the Vienna Research Groups for Young Investigators (2011), the National Research Network 'Rigorous Systems Engineering' funded by FWF, and a Microsoft Research PhD Scholarship (2016). He actively contributes to the academic community through his service as co-chair for major conferences including CAV 2018 and FMCAD 2017. As leader of the FORSYTE research group at TU Wien, Weissenbacher oversees a vibrant research team working at the intersection of logic, verification, and practical software engineering challenges. The group is currently involved in the Doctoral College on Automated Reasoning, funded by FWF, which aims to train the next generation of researchers in this critical field.

Matthias Walterمشاهده پروفایل

استادیار

• Operations Research
• Optimization
• Mathematical Programming
• +۵ مورد دیگر

Matthias Walter is an Assistant Professor in the Department of Mathematics of Operations Research. His research focuses on optimization, mathematical programming, and algorithm design, with applications in transportation, combinatorial optimization, and logistics. He contributes to the SCIP Optimization Suite and has developed the Combinatorial Matrix Recognition Library. His work spans topics such as linear programming relaxations, pseudo-Boolean solving, and multilinear optimization. Key research interests include operations research, integer programming, and algorithmic solutions for complex optimization problems. He has collaborated on projects like optimizing parcel transportation and analyzing congestion games. His recent publications address challenges in flow shop scheduling, graph realization, and pseudo-Boolean functions. Walter actively participates in academic activities, organizing events like the Mathematical Olympiad in Saxony-Anhalt and presenting invited talks on topics such as McCormick relaxations. His contributions to computational tools and theoretical advancements highlight his role in advancing optimization methodologies.

Tom van Dijkمشاهده پروفایل

استادیار

• Formal Methods
• Algorithm Design
• Model Checking
• +۴ مورد دیگر

Tom van Dijk is an Assistant Professor in the Department of Formal Methods and Tools at the University of Twente. He holds a PhD and MSc in related fields. His research focuses on formal methods, algorithm design, model checking, decision diagrams, and parity games. Key contributions include work on reactive synthesis, parity game solvers (e.g., Oink and Knor), and multi-core computing techniques. His research interests include algorithm complexity analysis, symbolic methods, and formal verification. Notable achievements include the SYNTCOMP awards (2021–2023) and the Best Paper Award at SPIN 2017. He has published widely on topics such as parity game algorithms, decision diagram optimizations, and parallel computing frameworks like Sylvan and LTSmin. Recent articles highlight advancements in parity game solving strategies, reactive synthesis competitions, and worst-case complexity analysis. He actively contributes to open-source tools and datasets, including repositories on Zenodo and GitHub. His work aligns with UN Sustainable Development Goals through contributions to efficient computational methods and formal verification techniques.

• Algorithms and Complexity
• Discrete Mathematics
• Structural Graph Theory
• +۲ مورد دیگر

Dr. Igor Razgon serves as an Associate Professor in the Department of Computer Science at Durham University, where he conducts foundational research at the intersection of discrete mathematics and theoretical computer science. His work bridges abstract graph theory with practical applications in artificial intelligence systems and database optimization. His research program centers on structural graph theory, algorithms and complexity, with particular emphasis on tree-width parameters, hypertree decompositions, and constraint satisfaction frameworks. This work establishes critical connections between graph structural properties and computational tractability boundaries, directly impacting query optimization in database management systems and knowledge representation in AI. Analysis of his 2021-2025 publications reveals consistent focus on dichotomy theorems, fractional decomposition methods, and width parameters for hypergraphs. His research demonstrates how structural graph properties determine computational complexity thresholds, with direct applications to database query optimization and constraint-based reasoning systems. Professional recognition includes: Nerode Prize (2020) for contributions to computational complexity theory While his publications indicate significant collaborative work with leading researchers in discrete mathematics, the available information does not specify doctoral advisees, grant funding sources, or laboratory affiliations. His research trajectory suggests ongoing investigation into structural parameters for combinatorial problem solving.

• Multi-agent systems
• Real-Time Systems
• Explainable AI (XAI)
• +۵ مورد دیگر

Davide Calvaresi is an Associate Professor at HES-SO Valais-Wallis (University of Applied Sciences and Arts Western Switzerland) in the Engineering and IT school within the Computer Science and Communication Systems department. His research focuses on multi-agent systems , real-time systems , explainable AI (XAI) , and blockchain for trustworthy applications in healthcare and safety-critical domains. Current projects include EXPECTATION (Personalized Explainable AI for decentralized agents) and past projects like Axe Santé 2020 (interdisciplinary health research) and Simulator of multi-agent systems (timing reliability analysis). Collaborations include researchers from University of Bologna, University of Luxembourg, and Ozyegin University. Recent publications focus on swarm intelligence in IoT , ethical AI for aging populations , and explainable health coaching systems Technical contributions include DEXiRE (rule extraction from neural networks), SCoDES (blockchain-based consent management), and HAExA (parsimonious XAI architecture)

• Boolean Satisfiability (SAT) Solvers
• Formal Verification
• Distributed Protocols
• +۷ مورد دیگر

Karem Sakallah is a Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan, College of Engineering. His research focuses on formal verification, SAT solvers, and distributed protocols, with a strong emphasis on symmetry breaking and scalable verification techniques. He mentors Ph.D. students by fostering curiosity, collaborative problem-solving, and clear technical communication. Research highlights: Quantified symmetric minimization, SAT-based verification of distributed systems, symmetry detection in graphs, and automated inductive invariant inference. Teaching philosophy: Encourages students to view research as an adventure, prioritizes teaching them to identify gaps in literature, write effectively, and present solutions elegantly. Conference attendance: Supports participation in top-tier venues like FMCAD, SAT, CAV, and VMCAI, covering associated costs through research funding.

Julian Bradfieldمشاهده پروفایل

مدرس ارشد

• Concurrency
• Modal Logic
• Temporal Logic
• +۶ مورد دیگر

Julian Bradfield is a Reader in Computer Science in the School of Informatics at the University of Edinburgh. He serves as Director of the Laboratory for Foundations of Computer Science (LFCS) and has been on the teaching staff since 1992. His academic journey began with a Mathematics degree from Cambridge (B.A. 1985, M.A. 1988), followed by a Ph.D. in Computer Science from the University of Edinburgh (awarded 1991). His educational background includes: B.A. in Mathematics from Cambridge (1985) M.A. in Mathematics from Cambridge (1988) Ph.D. in Computer Science from the University of Edinburgh (1991) Bradfield's research has evolved significantly over his career. Initially focused on computer science topics like fixpoint logics and concurrency, his interests have increasingly turned to linguistics, particularly phonology, since the mid-2000s. He has made notable contributions to the study of the Khoisan language !Xoon, applying his expertise in concurrency to linguistic analysis. His interdisciplinary approach bridges computer science, logic, and linguistics, creating innovative frameworks for understanding both computational systems and natural language phenomena. His recent publications show a clear shift toward linguistic research, particularly in phonology, while maintaining connections to his earlier work in logic and concurrency. The articles demonstrate a progression from theoretical computer science to applied linguistic analysis, with several papers focusing on the phonological structures of Khoisan languages, especially !Xoon. His work often combines formal logical frameworks with empirical linguistic data, creating bridges between disciplines that are typically separate. Bradfield actively supervises Ph.D. students and has contributed to various research projects throughout his career. He has developed connections between logical frameworks and linguistic analysis, particularly in applying concepts from concurrency theory to phonological processes. His role as Director of LFCS indicates significant administrative responsibilities alongside his research and teaching duties. He teaches "Informatics 1 - Introduction to Computation" and has developed materials for courses on Formal and Computational Approaches to Phonology. His teaching reflects his interdisciplinary expertise, connecting foundational computer science concepts with applications in linguistics.

Andreas Venerisمشاهده پروفایل

استادیار

• Digital Systems Verification
• Circuit Synthesis
• Boolean Satisfiability
• +۳ مورد دیگر

Andreas Veneris serves as an Assistant Professor in the Department of Informatics at the School of Information Sciences and Technology, Athens University of Economics and Business (AUEB). His academic career is rooted in computer engineering and theoretical computer science, with a focus on digital systems and computational methods. Education: Diploma in Computer Engineering and Informatics (1991), University of Patras M.Sc. (1992), University of Southern California Ph.D. (1998), University of Illinois at Urbana-Champaign Research Focus: Dr. Veneris specializes in the verification and synthesis of digital systems and circuits, with particular expertise in Boolean satisfiability solvers. His work bridges theoretical computer science with practical engineering applications, focusing on developing efficient algorithms and data structures for complex computational problems in hardware design and verification. His research intersects with formal methods, computational logic, and electronic design automation, contributing to advancements in reliable hardware systems development. Professional Activities: Based in the Antoniadou Wing, 3rd floor at AUEB, Dr. Veneris contributes to both undergraduate and postgraduate education in computer science. His work connects with various research groups and laboratories within AUEB's Department of Informatics, which participates in numerous national and European research projects. The department maintains strong industry connections and has produced notable alumni working at leading technology companies worldwide.

Szemerédi Endreمشاهده پروفایل

استاد

• Discrete mathematics
• Combinatorics
• Theoretical computer science
• +۱ مورد دیگر

Endre Szemerédi is a Hungarian mathematician and computer scientist, currently serving as a Permanent Research Fellow at the Alfréd Rényi Institute of Mathematics (Hungarian Academy of Sciences) and holding the New Jersey Professor of Computer Science position at Rutgers University since 1986. His career spans prestigious institutions including Stanford, Caltech, and the Institute for Advanced Study. Expertise: Discrete mathematics, combinatorics, theoretical computer science, and number theory. Education: M.Sc. (1965, Eötvös Loránd University), Ph.D. (1970, Moscow State University under Israel Gelfand). Research legacy encompasses foundational contributions to combinatorics, graph theory, and computational complexity. His work on Hamiltonian cycles in random graphs , parallel sorting networks , and the Blow-up Lemma revolutionized extremal combinatorics and algorithm design. Scientific honors include: 2012 Abel Prize and Széchenyi Prize 2008 Rolf Schock Prize and Steele Prize 1982 Member of Hungarian Academy of Sciences , 2010 Member of US National Academy of Sciences 1975 Pólya Prize , 1973 Rényi Prize , multiple Grünwald Prizes .

• Quantified Boolean Formulas
• Proof Complexity
• SAT Solving
• +۲ مورد دیگر

Tomáš Peitl is a University Assistant at the Vienna University of Technology's Institute of Logic and Computation. His research focuses on quantified Boolean formulas (QBF), proof complexity, SAT solving, and dependency schemes. He teaches courses on Algorithms and Data Structures, Algorithmics, and Structural Decompositions. Dr. Peitl has developed specialized tools including the QBF solver Qute which implements dependency learning and reflexive resolution-path dependency schemes. His current research examines decision heuristics in QCDCL and hardness characterizations of QBF resolution systems. Recent publications explore symmetry breaking techniques in quantified graph search, QCDCL decision strategies, and the generation of hard SAT instances. He maintains collaborations through conferences like SAT and IJCAI, and contributes to theoretical foundations of automated reasoning.

• Automated Reasoning
• Knowledge Representation and Reasoning
• Computational Logic
• +۵ مورد دیگر

Uwe Egly is an Associate Professor at the Department of Knowledge-Based Systems, Faculty of Informatics, Technische Universität Wien (TU Wien). His research focuses on automated reasoning, proof theory, knowledge representation, and computational logic, with a strong emphasis on quantified Boolean formulas (QBFs), argumentation frameworks, and applications of AI in engineering. He leads projects funded by the Austrian Science Fund (FWF) and the Vienna Science and Technology Fund (WWTF), including the Boolean project (2011–2019) and FAME (2011–2014). Egly is known for developing QBF solvers like DepQBF and contributing to SAT-solving techniques. He teaches courses such as Abstract Argumentation , Formal Methods in Computer Science , and Quantum Computing . His research interests span proof complexity, satisfiability checking, and AI-driven algorithms for path planning. He has advised numerous students on theses involving quantum algorithms, QBF solver optimizations, and argumentation frameworks. Egly’s work bridges theoretical computer science with practical applications, including contributions to deformation monitoring systems and circuit synthesis using SAT-based methods. He is involved in international workshops and conferences, such as SAT, FMCAD, and Dagstuhl Seminars, and has edited proceedings for events like SAT 2014 . His collaborations include projects on scenario-based testing of UML diagrams and semantics-aware model versioning. Egly’s interdisciplinary approach integrates logic, artificial intelligence, and computational methods to solve complex theoretical and applied problems.

Ciaran McCreeshمشاهده پروفایل

پژوهشگر ارشد

• Graph Theory
• Combinatorial Optimization
• Constraint Programming
• +۵ مورد دیگر

Ciaran McCreesh is a Research Fellow in the School of Computing Science at the University of Glasgow. His research focuses on solving hard combinatorial problems in practice, particularly in graph theory and subgraph finding, leveraging symbolic AI techniques like constraint programming and Boolean satisfiability. He explores closing the gap between theoretical worst-case complexity and practical performance through empirical algorithmics and computational experiments. His work also addresses algorithm reliability via proof logging, parallel hardware exploitation (bit-parallelism, multi-core computing), and algorithm engineering to improve solver accessibility. Research interests: Combinatorial optimization, constraint programming, proof logging, parallel computing, algorithm reliability. Developed the Glasgow Subgraph Solver, a constraint programming-based tool for hard subgraph isomorphism problems. Publications span graph computation models, certified solvers, and algorithmic advancements. His work emphasizes practical algorithmic improvements with rigorous validation methods. Supervised students include Matthew McIlree and José Antonio Rodríguez Bacallado.

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

Mattias Guns is an Associate Professor in the Department of Computer Science at the Faculty of Engineering Science, KU Leuven. He is a core member of the Declarative Languages and Artificial Intelligence (DTAI) research unit and holds affiliations with Leuven.AI and the KU Leuven Institute for Mobility (LIM). He serves on the Council of the Faculty of Engineering Science and the Programme Committees for Artificial Intelligence and Mobility and Supply Chain. His research centers on bridging Artificial Intelligence with constraint-based optimization, focusing on Explainable AI, Predict-and-Optimize frameworks, and machine learning integration for constraint solving. Key interests include human-centric explainability in decision systems, perceptual reasoning, and energy-efficient optimization models. His work addresses fundamental challenges in program synthesis, scheduling, and trustworthiness of AI planning systems. Recent publications reveal strong trends in fusing machine learning with declarative problem-solving paradigms. Notable themes include LLM-driven constraint modeling, mutational testing for solvers, step-wise explanation generation, and preference learning for unsatisfiable constraints. His research consistently targets real-world applications in supply chain optimization, inventory management, and perceptual reasoning systems. As principal investigator, he leads multiple major projects: TED-AI: Trustworthy Explanations for Decision Making in AI (2025) Towards Human-Centric Explainable Constraint Solving (2025-2028) SAELING: Energy Optimization via Learning (2024-2027) From Natural Language to Constrained Optimization (2023-2027) He has supervised PhD student Mulamba Ke Tchomba on machine learning-enhanced constraint solvers for perceptual reasoning. Within the DTAI research group, he contributes to KU Leuven's leadership in declarative AI through collaborative work on constraint programming foundations and applications. His team actively develops open-source tools like CMPpy for prediction-optimization integration and participates in European AI initiatives through Leuven.AI.

Sourav Chakrabortyمشاهده پروفایل

استاد

• Theoretical Computer Science
• Boolean Functions
• Quantum Complexity
• +۴ مورد دیگر

Sourav Chakraborty is a Professor in the Advanced Computing and Microelectronics Unit (ACMU) of the Computer and Communication Sciences Division at the Indian Statistical Institute (ISI), Kolkata, India. He joined ISI in July 2018 after serving as faculty at Chennai Mathematical Institute from 2010-2018. Previously, he held postdoctoral positions at Centrum Wiskunde & Informatica (CWI) in Amsterdam and Technion in Israel. Education: Ph.D. in Computer Science, University of Chicago (2008) M.S. in Computer Science, University of Chicago (2005) B.Sc. in Mathematics, Chennai Mathematical Institute (2003) Research Focus: Professor Chakraborty specializes in Theoretical Computer Science with emphasis on classical and quantum complexity of Boolean functions, including sensitivity analysis, property testing, and quantum database search. His work extends to graph algorithms, electronic commerce mechanisms, and coding theory. His research explores fundamental questions in computational complexity through innovative mathematical frameworks. Publication Trends: Recent work demonstrates a strong focus on property testing, sampling algorithms, and complexity theory, with significant contributions to streaming algorithms, Boolean function analysis, and quantum query complexity. His publications frequently appear in top theoretical computer science venues and exhibit consistent innovation in algorithm design and complexity boundaries. Awards & Honors: Praise from Donald E. Knuth for streaming algorithms research Inclusion in Oded Goldreich's 'my choices' list for Conditional Sampling and Huge-Object Model work Chakraborty's function named in his honor for Sensitivity Conjecture contributions Academic Service: Teaches courses in discrete mathematics and theoretical computer science, with detailed course materials available through institutional pages. Organized workshops including the 2020 Workshop on Sensitivity and Query Complexity at ISI.