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Paul BeameView profile

Professor

• Computational Complexity
• Proof Complexity
• Satisfiability (SAT) Solving
• +11 more

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.

Jean-Marie LagniezView profile

Associate Professor

• Artificial Intelligence
• Constraint Programming
• SAT Solving
• +3 more

Jean-Marie Lagniez is an Associate Professor at the IUT de Lens, Université d'Artois, France. He holds a post-graduate degree in Algorithmic for Inference and Decision from the Informatics Graduate School of Artois University and completed his PhD at the CRIL Laboratory (Centre de Recherche en Informatique de Lens). His research focuses on integrating local search and backtracking methods in SAT and CSP, improving CDCL solvers, and model counting. He has held postdoctoral positions at the Institute for Formal Models and Verification (Johannes Kepler University Linz, Austria) and CRIL. His work spans constraint programming, artificial intelligence, and formal logic. Education: Post-graduate degree in Algorithmic for Inference and Decision, Université d'Artois. PhD in Computer Science, CRIL Laboratory, Université d'Artois. Research Interests: Jean-Marie's research emphasizes enhancing SAT solving techniques, constraint satisfaction, model counting, and parallel computing. He explores applications in belief merging, modal logic, and algorithmic improvements for efficient problem-solving. His contributions include distributed model counters (DMC) and hybrid approaches combining local search with CDCL. Publications: His work in 2018-2017 includes advancements in consensus-finding, distributed SAT solvers, and modal logic satisfiability, published in venues like IJCAI, CP, and AI Communications. These studies highlight his expertise in bridging theoretical foundations with practical algorithmic solutions.

Leslie Ann GoldbergView profile

Professor

• Algorithms
• Complexity Theory
• Randomized Algorithms
• +6 more

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.

Marijn HeuleView profile

Associate Professor

• Satisfiability (SAT) Solving
• Formal Verification
• Combinatorial Mathematics
• +5 more

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.

• Satisfiability (SAT) Solving
• Formal Verification
• Automated Reasoning
• +5 more

Marijn J.H. Heule is an Associate Professor at the School of Computer Science , Carnegie Mellon University . He received his PhD from Delft University of Technology in the Netherlands. His research focuses on solving hard combinatorial problems through Satisfiability (SAT) solving , with applications in formal verification, number theory, and extremal combinatorics. Education: PhD in Computer Science, Delft University of Technology, Netherlands Heule's work addresses fundamental challenges in SAT solving, including: Exploiting high-performance computing via the cube-and-conquer paradigm Validating results from SAT solvers using novel proof formats His research has produced 15+ recent publications (2025-2021) on topics like automated reasoning, formal verification, and combinatorial proofs. Notable achievements include: Best Paper Award at HVC 2011 (Cube-and-Conquer) 200 TB proof for the Boolean Pythagorean Triples Problem Co-editor of the Handbook of Satisfiability He has advised multiple PhD students including Emre Yolcu , Joseph Reeves , and Bernardo Subercaseaux . His tools like DRAT-trim and QRAT-trim have become standard in proof validation.

Guy BreslerView profile

Associate Professor

• Information Theory
• Statistical Inference
• Computational Complexity
• +2 more

Guy Bresler is Associate Professor in the Department of Electrical Engineering and Computer Science at MIT, with affiliations in LIDS, Theory of Computation, Center for Statistics, FODSI, and IDSS. He researches the interface of information theory, statistics, theoretical computer science, and probability, developing mathematical models to understand computational tractability of high-dimensional inference. His research characterizes relationships between combinatorial structure and computational tractability in inference problems, with applications in statistical physics, random graphs, and learning theory. Recent work establishes fundamental limits in statistical estimation and develops efficient algorithms for high-dimensional problems. Publications demonstrate consistent focus on computational-statistical tradeoffs across random graphs, Markov chains, neural networks, and graphical models. Techniques involve information-theoretic analysis, reduction methods, and phase transition characterization. He advises doctoral students Kiril Bangachev, Alina Harbuzova, Chenghao Guo, and Brice Huang. Previously advised researchers include Enric Boix-Adserà, Dheeraj Nagaraj, and Mina Karzand. He co-organized the Simons Institute program on computational aspects of high-dimensional inference.

• Distributed and Cloud Computing
• Machine Learning
• Heterogeneous Systems
• +4 more

Ivor Spence is a Professor in the School of Electronics, Electrical Engineering and Computer Science at Queen's University Belfast. His academic role includes research and teaching in distributed and cloud computing, machine learning on heterogeneous systems, and benchmarks for satisfiability problems. He is actively involved in supervising PhD students, including Konstantin Bakanov and Ian McRitchie, focusing on topics such as heterogeneous computing and generative programming. His research interests span energy-efficient computing architectures, edge and federated learning systems, and algorithm optimization for heterogeneous hardware. He has contributed to projects like Energy-efficient Heterogeneous Computing at exaSCALE and FUSION/Numa Engineering , emphasizing practical applications in distributed systems and real-time analytics. Dr. Spence collaborates with industry partners through Knowledge Transfer Partnerships (KTPs), addressing challenges in edge computing and hardware-software co-design. His work has led to numerous publications in top-tier journals and conferences, including contributions to federated learning frameworks, DNN pruning systems, and video retrieval algorithms. He is affiliated with the Centre for Intelligent Sustainable Computing and has served on editorial boards and peer-review panels for IEEE Transactions and other venues. His research bridges theoretical computer science with practical innovations in high-performance and sustainable computing.

• Theoretical Computer Science
• Formal Verification
• Software Systems Verification
• +5 more

Georg Zetzsche is a tenure-track faculty member at the Max Planck Institute for Software Systems (MPI-SWS) in Kaiserslautern, Germany, where he heads the Models of Computation group. He joined MPI-SWS in November 2018 after postdoctoral positions at IRIF, Université Paris-Diderot (2017-2018) and LSV Cachan (2015-2017). He received his PhD in Computer Science from Universität Kaiserslautern under the supervision of Prof. Dr. Roland Meyer in 2015, with a dissertation in the Concurrency Theory Group. His research focuses on theoretical foundations of verification and synthesis of software systems, with particular emphasis on decidability and complexity issues of infinite-state systems. His work explores synthesis of finite-state abstractions of infinite-state systems (including separability problems, downward closures, and Parikh images), as well as decision problems for infinite groups where he applies methods from verification to gain insights on how to devise infinite-state models with pleasant analysis properties. Zetzsche's research output demonstrates expertise across formal verification, theoretical computer science, and programming language theory. His publications reveal a consistent focus on vector addition systems, reachability analysis, language theory, and decidability questions. His work often bridges theoretical foundations with practical verification problems, particularly in the context of infinite-state systems where traditional verification techniques face significant challenges. 2025 Salomaa Prize ERC Starting Grant for project FINABIS EATCS Best Paper Award at ETAPS 2023 EAPLS Best Paper Award at ETAPS 2021 Distinguished Paper Award at POPL 2021 EATCS Distinguished Dissertation Award He actively serves on program committees for major conferences including LICS 2026, MFCS 2025, DLT 2024, ICALP 2024, POPL 2024, LICS 2023, and many others. He has organized events such as Theorietag 2023 on automata and formal languages. His current group at MPI-SWS includes PhD students Pascal Baumann, Pascal Bergsträßer, Irmak Sağlam, Lia Schütze, and Yousef Shakiba, along with postdocs Moses Ganardi and Chris Köcher.

Divesh AggarwalView profile

Associate Professor

• Lattice Algorithms and Complexity
• Cryptography
• Pseudorandomness
• +6 more

Divesh Aggarwal is an Associate Professor in the Department of Computer Science at the National University of Singapore (NUS) and a Principal Investigator at the Centre for Quantum Technologies (CQT). He leads an active research group with multiple PhD students, postdocs, and collaborators focusing on theoretical computer science and cryptography. His research spans two primary themes: (1) fine-grained complexity and exponential algorithms for hard problems, particularly lattice problems, where he works on both finding faster algorithms and proving lower bounds; and (2) randomness extractors and their applications in cryptography, privacy amplification, and tamper-resilient systems. His work intersects cryptography, computational complexity, and quantum computing. Aggarwal's recent publications (2022-2025) demonstrate continued productivity in lattice-based cryptography, with significant contributions to non-malleable codes, quantum security, and hardness assumptions. His work appears consistently in top venues including STOC, FOCS, CRYPTO, and IEEE Transactions. The research shows a strong trend toward quantum-resistant cryptography and exploring the boundaries between classical and quantum computational hardness. He actively mentors students and researchers, with current PhD students including Zeyong Li, Rishav Gupta, Saswata Mukherjee, Aditya Morolia, and Ananta Mukherjee. His alumni have secured positions at institutions including NUS, IIT Delhi, and XJTLU. Aggarwal also organizes a weekly research seminar where his group discusses theoretical computer science topics. His teaching portfolio includes advanced courses such as Computational Complexity, Pseudorandomness, Design and Analysis of Algorithms, and Introduction to Quantum Computing. He serves on program committees for major conferences including CRYPTO, EUROCRYPT, and STOC, and on editorial boards for journals like Information Processing Letters.

Johannes Klaus FichteView profile

Associate Professor

• Computational Algorithmics
• Computational Complexity
• Parameterized Algorithms
• +4 more

Johannes Klaus Fichte is an Associate Professor at Linköping University, affiliated with the Department of Computer and Information Science (IDA) and the Artificial Intelligence and Integrated Computer Systems (AIICS) division. His research focuses on computational algorithmics, complexity, and practical applications such as parameterized algorithms for combinatorial problems, model counting of propositional formulas, Boolean satisfiability (SAT), and answer-set programming (ASP). He also has industry experience in healthcare data analysis. His work bridges theoretical foundations and practical implementations, with recent contributions to plan reasoning, bounded treewidth algorithms, and abstract argumentation frameworks. He collaborates with international researchers and publishes in top conferences like AAAI, ECAI, and KR. As part of the AIICS division, he contributes to teaching and research in AI, theoretical computer science, and integrated systems. His research trends emphasize algorithmic efficiency, complexity analysis, and interdisciplinary applications in healthcare and formal methods.

• Algebra
• Computational Complexity
• Theoretical Computer Science
• +3 more

Prof. Pawel M. Idziak is a distinguished academic at the Faculty of Mathematics and Computer Science, Jagiellonian University, where he holds a Professorship in the Department of Algorithmics. His primary research focuses on algebra, computational complexity, and theoretical computer science, with notable contributions to the study of algebraic structures, satisfiability problems, and modular circuits. Idziak has led and contributed to numerous grants, including managing the 'Numerical and Structural Invariants in Algebra, Logic and Constraint Satisfaction Problems' (2015–2022) and co-ordinating initiatives like 'Programmers of the Future 4.0'. His work bridges abstract algebra with computational challenges, addressing topics such as group theory, circuit satisfiability, and algorithmic complexity. His research interests span a broad spectrum of theoretical computer science and algebra, including the interplay between algebraic structures and computational problems. Idziak has advised over 20 PhD students, mentoring them in areas such as algorithm design, logic in computer science, and discrete mathematics. He has also contributed to foundational works like Generative Complexity in Algebra (2005) and co-authored influential papers in journals like SIAM Journal on Computing and Transactions of the American Mathematical Society . Idziak’s academic leadership is evident through his roles in institutional committees and his active participation in international conferences. His recent work (2024) on equation satisfiability in solvable groups highlights his ongoing contributions to advancing computational algebra and complexity theory.

Heng GuoView profile

Associate Professor

• Algorithms
• Computational Complexity
• Approximate Counting
• +5 more

Heng Guo is an Associate Professor in Algorithms and Complexity at the School of Informatics, University of Edinburgh. He leads the ERC starting grant project New Approaches to Counting and Sampling (NACS), which runs from 2021 to 2026. Previously, he has worked and studied at Berkeley, London, Madison, and Beijing. His research lies at the intersection of theoretical computer science, combinatorics, and statistical physics. Guo's research focuses on algorithms from a complexity perspective, particularly computational counting and sampling. He is renowned for his work on the Lovász local lemma, Markov chain Monte Carlo methods, phase transitions in computational complexity, and complexity classifications. His approach often involves discovering unseen links between different areas of theoretical computer science. Key contributions include confirming a conjecture of Gorodezky and Pak through partial rejection sampling, establishing rapid mixing for Swendsen-Wang dynamics, and developing a polynomial-time approximation algorithm for all-terminal network reliability. His publication record shows a strong trajectory of impactful research in top venues including FOCS, STOC, SODA, J. ACM, and SIAM Journal on Computing. His work on the all-terminal network reliability problem won the Best Paper Award at ICALP 2018. Guo has organized several significant workshops including JerrumFest 2025, MCMC 2.0 (Shonan seminar), and a STOC 2020 workshop on new frontiers of approximate counting. These events highlight his leadership role in the theoretical computer science community. Best Paper Award at ICALP 2018 EATCS Distinguished Dissertation Award 2016 Guo has advised several PhD students including Giorgos Mousa, Jiaheng Wang, and Graham Freifeld, and mentored postdocs such as Weiming Feng, Vishvajeet Nagargoje, and Konrad Anand. His ERC grant supports multiple research associates working on counting and sampling problems. He has taught courses including Computational Complexity, Randomness and Computation, and Algorithmic Game Theory at the University of Edinburgh.

Martina SeidlView profile

Professor

• Artificial Intelligence
• Symbolic AI
• Quantified Boolean Formulas (QBF)
• +3 more

Martina Seidl is a Professor at the Johannes Kepler University Linz , serving as Head of the Institute for Symbolic Artificial Intelligence . She leads research initiatives in formal verification, quantified Boolean formulas, and symbolic AI. Key Projects : Industrial problem solving using symbolic AI (2025–2026), Cluster of Excellence "Bilateral AI" (2024–2029), LOGTECHEDU (2018–2020) Leadership Roles : PhD Committee member at TU Wien, Associate Editor for the Artificial Intelligence Journal Her research focuses on automated reasoning , QBF solving , and formal methods in computer science. She has developed tools like PyQBF and Booleguru for propositional logic and constraint solving. Recent publications analyze semantic feature model differences, solution counting for QBF families, and tree-based model counters. She contributes to educational programs through lectures on formal models, SAT solving, and neurosymbolic AI. Scientific activities include organizing workshops like "Alles Logisch?" and participating in program committees. Current funded projects emphasize interdisciplinary AI applications and logic-based educational technologies.

Yap RolandView profile

Associate Professor

• Constraint Programming
• Optimization
• Combinatorial Problems Modelling
• +5 more

Yap Roland is an Associate Professor at the School of Computing, National University of Singapore (NUS), and a member of the Institute of Operations Research and Analytics (IORA). His research focuses on constraint programming and solving, optimization, combinatorial problems, vehicle routing, and big data applications. He actively contributes to advancing methodologies in computational logic, software security, and algorithm design. His work spans theoretical foundations of constraint satisfaction (CSP/SAT) and practical applications in database systems, graph neural networks, and transportation logistics. Notable contributions include benchmarking tools like OSS-Bench for coding LLMs, novel approaches to detecting logic bugs in graph databases, and enhancing security through randomized pointer techniques. His research bridges algorithmic theory and real-world challenges in AI, cybersecurity, and efficient resource allocation. Yap Roland has published extensively in top-tier venues such as the International Conference on Principles and Practice of Constraint Programming (CP) and the International Conference on Theory and Applications of Satisfiability Testing (SAT). His recent work emphasizes scalability, fairness in machine learning, and robustness against memory errors in software systems.

Stefan SzeiderView profile

Professor

• Algorithms
• Computational Complexity
• Theoretical Computer Science
• +4 more

Stefan Szeider is a full professor and chair of the Algorithms and Complexity Group at the Faculty of Informatics, Technische Universität Wien (TU Wien). He also serves as a visiting scientist at UC Berkeley's Simons Institute for the Theory of Computing. His academic journey includes positions at the University of Durham (UK) and the University of Toronto (Canada), and he earned his Mathematics PhD from the University of Vienna in 2001. Dr. Szeider's research focuses on designing efficient algorithms for problems in Artificial Intelligence, automated reasoning, and combinatorial optimization. He leads several initiatives, including the Vienna Center for Logic and Algorithms (VCLA), and has secured funding from the ERC, EPSRC, FWF, and others. His Erdős number is 2, reflecting his collaborative network in mathematics and computer science. Key achievements include the first ERC Starting Grant awarded to an Austrian computer scientist (2009), and awards such as the Highlighted Paper Award at SAT 2023 and Best Paper at CP 2020. He advises numerous PhD students and postdocs, fostering the next generation of researchers in algorithms and complexity. Notable contributions extend beyond academia to public outreach, including initiatives like the 'Algorithms Think Differently' educational program and the 'Algorithms in 60 Seconds' video competition. His work bridges theoretical foundations and practical applications, influencing both academic and real-world computational challenges.