Anand V Natarajan is the ITT Career Development Professor in Computer Technology and Assistant Professor in the Department of Electrical Engineering and Computer Science (EECS) at MIT, with affiliation to the Computer Science and Artificial Intelligence Laboratory (CSAIL). He holds a PhD in Physics from MIT (2018), advised by Aram Harrow, and previously served as a postdoc at Caltech's Institute for Quantum Information and Matter. His research focuses on theoretical quantum information, emphasizing quantum complexity theory (e.g., MIP* and QMA(2) classes), nonlocality (Bell inequalities, nonlocal games), and semidefinite programming hierarchies. He teaches courses such as Quantum Cryptography, Quantum Systems Engineering, and Introduction to Algorithms at MIT. Notable contributions include resolving the MIP* = RE problem and the FOCS 2019 Best Paper Award for NEEXP ⊆ MIP*. He advises PhD students in quantum computing topics and collaborates extensively on quantum verification protocols and entanglement testing.
Albert Atserias is a Professor in the Department of Computer Science at the Universitat Politècnica de Catalunya (UPC), affiliated with the Faculty of Informatics of Barcelona (FIB) and the ALBCOM research group (Algorithms, Bioinformatics, Complexity, and Formal Methods). He is also associated with the Institut de Matemàtiques de la UPC-BarcelonaTech. His research is central to theoretical computer science, with a strong emphasis on logic and complexity. Atserias's research interests span Computational Complexity, Logic in Computer Science, Finite Model Theory, Proof Complexity, and Constraint Satisfaction Problems . His work explores the fundamental limits of computation, the expressive power of logical languages over finite structures, and the complexity of proving mathematical statements. He investigates the algebraic and combinatorial properties of proof systems, the limits of efficient algorithms for constraint solving, and the theoretical foundations of databases. His research often bridges logic, algebra, and combinatorics to provide deep insights into computational phenomena. The trends in his recent publications show a sustained focus on the logical and algebraic underpinnings of computational problems. Key themes include the consistency and complexity of database queries , the power and limitations of proof systems (like resolution and sum-of-squares), and the expressive power of homomorphism counts in graph theory. His work on the hardness of automating resolution and the development of circular proof systems are particularly significant contributions to proof complexity. The 2024 PODS Best Paper Award for work on relational consistency underscores the impact and timeliness of his research. Among his notable scientific awards are the prestigious ICREA Acadèmia , the PODS 2024 Best Paper Award , the Premi Extraordinari de Doctorat (Extraordinary Doctoral Prize), and the Kleene Award for Best Student Paper . These accolades reflect both the excellence of his early work and his continued leadership in the field. Atserias has been a principal investigator on numerous competitive research projects, including funding from the European Research Council (ERC) and the Spanish Ministry of Science. He has advised doctoral students, such as Toni Hakoniemi, whose thesis on proof complexity he supervised. His extensive collaborative network includes leading researchers like Phokion Kolaitis, Anuj Dawar, and Victor Dalmau. He has also served on the scientific committees of major conferences, contributing to the academic community. He is a core member of the ALBCOM research group , a leading team at UPC focused on theoretical aspects of computer science, which provides a vibrant environment for research in algorithms, complexity, and formal methods. His work is also connected to the broader Institut de Matemàtiques de la UPC, fostering interdisciplinary collaboration between computer science and mathematics.
Standa Živný is a Professor of Computer Science at the University of Oxford and a Fellow and Tutor at Merton College. He has been a faculty member at Oxford since 2013 and was promoted to full professor in 2021. His research spans theoretical computer science and discrete mathematics, with a focus on algorithms, computational complexity, and constraint satisfaction problems (CSPs) in various forms, including optimisation, counting, and approximation. His research interests include the power and limitations of convex relaxations, sparsification, submodularity, and the algebraic and logical foundations of tractability in combinatorial problems. He has made significant contributions to understanding when and why certain problems can or cannot be efficiently solved using linear programming and other algorithmic paradigms. The recent trends in his publications show a deep engagement with approximation algorithms, hardness results, sparsification techniques, and the complexity of counting and promise problems. His work often lies at the intersection of algebra, logic, and optimisation, demonstrating the power of interdisciplinary approaches in theoretical computer science. ERC Consolidator Grant (NAASP, 2022–2027) ERC Starting Grant (PowAlgDO, 2017–2022) Royal Society University Research Fellowship (2013–2021) He actively supervises a large cohort of postdoctoral researchers and students, including PhD candidates, master’s, and undergraduate students. His leadership extends to academic service, where he serves as Editor-in-Chief of the SIAM Journal on Discrete Mathematics and holds editorial and committee positions in major journals and funding bodies. He has organised numerous workshops and research programmes at institutions such as Dagstuhl, the Isaac Newton Institute, and AIM. He is involved in major research initiatives, including a Simons Programme on symmetry in computation and an American Institute of Mathematics SQuARE on relaxations for promise CSPs.
Andrei Krokhin is a Professor in the Department of Computer Science at Durham University, UK. His academic roles include being a member of the Algorithms and Complexity Research Group. He holds a PhD in Mathematics from Ural State University (Russia) and has held positions at Warwick University and Oxford University. His research focuses on computational complexity, constraint satisfaction problems (CSP), universal algebra, and combinatorics. Education: PhD in Mathematics, Ural State University, 1990s Research Interests: Professor Krokhin investigates the mathematical and algorithmic foundations of CSP, emphasizing complexity classification and approximation. His work bridges universal algebra, logic, combinatorics, and graph theory. Key themes include algebraic approaches to CSP, constraint optimization, and the interplay between computational complexity and structural mathematics. Awards: EPSRC Advanced Research Fellowship (2006) Principal organizer of the 2006 Oxford Workshop on Mathematics of Constraint Satisfaction Invited plenary speaker at ISMVL 2003 (Tokyo) Invited lectures at NATO ASI Summer School (2003) Advising & Grants: Supervises PhD students (e.g., Yiming Qiu) and leads EPSRC-funded projects like 'Promise Constraint Satisfaction Problems: Structure and Complexity.' He recruits students for research on CSP complexity and approximation. Labs/Teams: Member of the Algorithms and Complexity Research Group at Durham University, collaborating internationally on CSP theory and applications.
Dr. Jakub Opršal is a Research Fellow at the University of Birmingham specializing in the theoretical foundations of computer science and mathematics. His research focuses on the computational complexity of constraint satisfaction problems (CSPs) and their variants. Previously, he held postdoctoral positions at ISTA (2022-23), Oxford (2021-22), Durham University (2018-21), TU Dresden (2016-18), and Jagiellonian University (2016), establishing a strong international research profile. Dr. Opršal received his PhD from Charles University in Prague in 2016 under the supervision of Libor Barto. His doctoral work laid the foundation for his ongoing contributions to universal algebra and computational complexity theory. Dr. Opršal's research integrates advanced mathematical frameworks including universal algebra , homotopy theory , category theory , and mathematical logic to analyze constraint satisfaction problems. He has made significant contributions to understanding the computational complexity of CSPs, particularly through topological methods and algebraic structures. His work often establishes dichotomy theorems and proves hardness results for various CSP variants, with increasing focus on promise constraint satisfaction problems. Analysis of Dr. Opršal's publication record reveals a sophisticated evolution in methodology, with recent work increasingly incorporating category-theoretic approaches and topological techniques to tackle fundamental questions in computational complexity. His research demonstrates a consistent pattern of bridging abstract mathematical concepts with concrete computational problems, particularly in establishing connections between algebraic structures and computational hardness. Dr. Opršal actively seeks PhD students and has organized significant academic events including the Birmingham CSP Meeting (2024). He serves on program committees for major theoretical computer science conferences and collaborates extensively with researchers across Europe, including prominent institutions like Oxford, Durham, and ISTA. As a key organizer of the Birmingham Constraint Satisfaction research group, Dr. Opršal contributes to a vibrant international research community. He participates in the CSP World Congress series and maintains active collaborations that advance the theoretical foundations of constraint satisfaction problems through interdisciplinary approaches combining computer science, mathematics, and logic.
Tomáš Jakl is a mathematician and computer scientist affiliated with the Czech Technical University (CTU). His research focuses on the intersection of topology, algebra, and category theory, with applications in theoretical computer science and logic. He is currently conducting the Marie Skłodowska-Curie project ALGACOM (Algorithms and Game Comonads), which bridges category theory with parameterized complexity through game comonads. Supervisor: Dušan Knop (CTU) Funding: EU Horizon Europe grant agreement No 101111373 Research Highlights: Jakl explores dualities between topology and algebra, leveraging category theory's compositional tools to analyze algorithmic efficiency and limitations in computational problems. His recent work includes applying game comonads to finite model theory and constraint satisfaction problems. Scientific Contributions: Jakl has published preprints on categorical approaches to PCSP and constraint satisfaction, and collaborated with researchers like Anna Laura Suarez, Max Hadek, and Jakub Opršal. His ALGACOM project integrates category theory into algorithm analysis and parameterized complexity. Awards & Activities: Marie Skłodowska-Curie Fellowship Lecturer at ESSLLI 2025 Submitted ERC Starting proposal and GACR grant Presented at Summer School on General Algebra and Ordered Sets Active in CTU's GGOAT seminar
Silvia Butti is a Senior Research Associate at the University of Oxford's Department of Computer Science and holds a Junior Research Fellowship at Lady Margaret Hall. Her research focuses on theoretical computer science, particularly constraint satisfaction problems (CSPs), algorithms, and complexity theory. She collaborates with Standa Živný on projects funded by the UKRI-ERC grant NAASP. She earned a PhD from Universitat Pompeu Fabra, an MSc in Mathematics and Foundations of Computer Science from Oxford, and a BSc from University College London. Her work bridges algebraic methods and computational complexity, exploring topics like promise CSPs, hierarchies (e.g., Sherali-Adams, Weisfeiler-Leman), and approximation algorithms. She has been awarded the INPhINIT fellowship and Marie Skłodowska-Curie COFUND funding. She has taught courses on Combinatorial Optimization, Computational Complexity, and Probability and Computing at Oxford, and Discrete Mathematics at UPF. Butti actively participates in academic outreach, including Maths Fest and Royal Institution Masterclasses, and has presented her research globally at venues like ICALP, LICS, and STACS. Her contributions span theoretical advancements and collaborative projects, with a focus on solving foundational challenges in computational complexity.
Demian Banakh is affiliated with the Department of Algorithmics at the Faculty of Mathematics and Computer Science, Jagiellonian University. His research focuses on quantum computing and computational complexity, as evidenced by his work on quantum CSP strategies and hardness conditions for promise constraint satisfaction problems (PCSPs). He completed a Master's thesis titled "Dichotomies for Boolean minions of weighted-sum functions with threshold." Banakh is part of the Algorithmics Research Group and collaborates with researchers like Marcin Kozik. His publications appear in prestigious conferences such as IEEE Symposium on Logic in Computer Science (LICS). He is involved in academic administration, contributing to technical infrastructure (e.g., university WiFi access management) and maintaining departmental resources. Contact details include room 3148 at the department, though an explicit email address is not provided in the text.
Patrick Wynne is a Lecturer in the Department of Mathematics at the University of Colorado Boulder. He defended his PhD in 2024 under Dr. Peter Mayr, with a dissertation titled 'Clonoids and Nilpotent Mal'cev Algebras.' His research focuses on clonoids, their structural roles in nilpotent Mal'cev algebras, and applications in equational theories and computational complexity. He has taught extensively since 2017, including courses on Calculus, Linear Algebra, and Mathematical Analysis in Business. Office: MATH 140 Email: patrick.wynne@colorado.edu, wynnepm@gmail.com Research emphasizes clonoids between abelian algebras, central extensions, and finiteness results in universal algebraic geometry. Recent work connects clonoids to nilpotent algebra structures, particularly 2-nilpotent Mal'cev algebras through abelian algebra clonoids. Presented at conferences including the Association for Symbolic Logic North America Meeting (2024), BLAST Conferences (2022-2024), and the Workshop on General Algebra (AAA 101-102). Teaching roles include course instructorships and assistant coordination of Calculus 2.
Pavan Aduri is a Professor and Interim Department Chair at Iowa State University's Department of Computer Science. His research focuses on theoretical computer science, computational complexity, algorithms, and machine learning. Key interests include statistical similarity estimation, submodular optimization, and probabilistic inference. He has contributed significantly to topics like #P-completeness, data stream processing, and fairness in optimization. His work spans algorithm design, computational hardness analysis, and applications in data science. Notable publications address total variation distance estimation, forgetting mechanisms in data streams, and monotone k-submodular maximization. He has explored connections between model counting and distinct element estimation in streams. Aduri's recent work (2023-2025) emphasizes geometric rounding techniques, Sperner's lemma variants, and algorithmic approaches to probabilistic inference. His research often bridges foundational theory with practical algorithmic challenges in machine learning and big data analysis. No scientific awards are explicitly listed, but his extensive publication record reflects sustained academic contributions.
Dr. Lorenzo Ciardo is a Research Fellow and Senior Research Associate in the Department of Computer Science, specializing in theoretical computer science and discrete mathematics. His research focuses on algorithms, complexity theory, constraint satisfaction problems, and spectral graph theory. He actively explores the algebraic approach to CSPs and their generalizations, with recent work involving quantum computing intersections and combinatorial machine learning applications. Research interests include the study of graph coloring problems, algebraic graph theory, and spectral parameters of graphs. His work bridges theoretical foundations with algorithmic innovations, particularly in constraint satisfaction and approximation methods. Notable recent contributions involve analyzing quantum advantage in CSP complexity and developing new algorithmic frameworks like CLAP for promise CSPs. His publications span topics from quantum chromatic gaps to Sherali-Adams hierarchies, reflecting expertise in both classical and quantum computational models. While no awards are listed here, his prolific output indicates significant contributions to the field. No advising or grant information is provided in the available data.
Libor Barto is a full professor at the Department of Algebra, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic. He is a leading researcher in universal algebra and computational complexity, with a strong focus on constraint satisfaction problems (CSPs) and their algebraic foundations. He leads the ERC Synergy Grant POCOCOP and previously led the ERC Consolidator Grant CoCoSym, and is deeply involved in advancing the algebraic theory of promise constraint satisfaction. Research Interests: His primary research areas include universal algebra, computational complexity, constraint satisfaction problems (CSP), promise constraint satisfaction problems (PCSP), clone theory, and the algebraic approach to logic and computation. He investigates the interplay between algebraic structures and computational tractability, particularly through polymorphisms, minions, and Taylor algebras. The recent articles reflect a strong trend in unifying algebraic approaches to CSP, exploring promise variants, approximation through plurimorphisms, symmetries in structures, and the role of Weisfeiler-Leman hierarchies. His work often appears in top-tier journals and conferences such as the Journal of the ACM, SIAM Journal on Computing, and LICS. Fellow of the Learned Society of the Czech Republic (since 2024) ERC Synergy Grant (POCOCOP, 2023–2029) ERC Consolidator Grant (CoCoSym, 2018–2023) Charles University Research Center (UNCE) Grant (PI, 2024–2029) Libor Barto advises PhD students and leads research teams under major grants like POCOCOP and CoCoSym. He has secured substantial funding from the European Research Council and the Czech Science Foundation (GACR). He is actively involved in the academic community as an editor of Algebra Universalis and Acta Scientiarum Mathematicarum , and has served on program committees for LICS, ICALP, and STACS. He has organized major workshops, including at the Fields Institute and multiple AAA and SSAOS conferences. He is involved in several research labs and collaborative teams, particularly through the Department of Algebra at Charles University, the POCOCOP project (with M. Bodirsky and M. Pinsker), and the CoCoSym ERC team. His work fosters international collaboration with researchers in France, Germany, Austria, Poland, Canada, and the USA.
Victor Dalmau is an Associate Professor at the Department of Information and Communication Technologies, Universitat Pompeu Fabra (UPF). He holds a Ph.D. and a degree in Computer Science from Universitat Politècnica de Catalunya. His career includes post-doctoral roles at institutions such as the University of Zaragoza and University of California, Santa Cruz, before joining UPF in 2000. He has held visiting positions at prestigious universities including Oxford, Cambridge, and Simon Fraser University. His research focuses on theoretical computer science, particularly constraint satisfaction problems (CSPs), exploring their complexity, combinatorial structures, and applications in areas like artificial intelligence and database theory. His work integrates concepts from universal algebra, logic, and computational learning theory. Notably, he investigates algorithmic techniques like Sherali-Adams hierarchies and Weisfeiler-Leman invariance for solving CSPs efficiently. Recent publications emphasize advancements in constraint satisfaction frameworks, homomorphism dualities, and the interplay between logic and database query optimization. His research bridges foundational theory with practical challenges in distributed computing and algorithm design. Victor Dalmau’s contributions span over 50 peer-reviewed articles, with a focus on computational complexity classifications, constraint programming, and the theoretical underpinnings of database systems. His work often addresses the boundaries between tractability and intractability in combinatorial problems.
Silvia Butti is a Senior Research Associate in the Department of Computer Science at the University of Oxford, where she also holds a Junior Research Fellowship at Lady Margaret Hall. She specializes in theoretical computer science, focusing on constraint satisfaction problems (CSPs), algebraic methods, approximation algorithms, and computational complexity. Her research bridges theoretical foundations with applications in distributed computing and combinatorial optimization. She earned her PhD from Universitat Pompeu Fabra (Barcelona, Spain) in 2022, supervised by Victor Dalmau, and holds an MSc in Mathematics and Foundations of Computer Science from the University of Oxford (2018) and a BSc in Mathematics from University College London (2017). Her academic journey is supported by prestigious fellowships, including the INPhINIT “la Caixa” and Marie Skłodowska-Curie Actions. Her research interests include the algebraic analysis of CSPs, inapproximability, and the interplay between hierarchies like Sherali-Adams and Weisfeiler-Leman invariants. She actively contributes to conferences such as LICS, MFCS, and CP, and has published extensively on topics ranging from promise problems to distributed algorithms. Dr. Butti teaches courses on computational complexity, combinatorial optimization, and probability and computing at the University of Oxford. She is committed to science communication, engaging with outreach initiatives like Maths Fest, the Royal Institution Masterclasses, and the UNIQ Summer School. Her work is funded by the UKRI-ERC grant NAASP, focusing on new approaches to approximability of satisfiable problems.
Dr. hab. Marcin Kozik is a Professor at the Department of Algorithmics within the Faculty of Mathematics and Computer Science at Jagiellonian University. His research focuses on Constraint Satisfaction Problems (CSP), Universal Algebra, and Computational Complexity. He has led multiple grants including 'Constraint Satisfaction Problems: Beyond the Finite Case' (2022–2026) and organized AAA 101 conference (2022). His work bridges algebraic methods with computational complexity, contributing to foundational theories in CSP dichotomy and robust algorithms. Research interests include algebraic approaches to CSP, complexity of finite algebras, and robust algorithms for near-unanimity CSPs. Recent publications emphasize quantum CSP strategies, unifying algebraic frameworks, and injective hardness conditions. He has received awards for his habilitation research (2011) and contributions in 2021. Grants Managed: Topological Correction Codes in Error-Resistant Quantum Computing (2022–2026) "Constraint Satisfaction Problems: Beyond the Finite Case" (Ministry of Science & Higher Education, 2022–2026) Key Contributions: Over 35 peer-reviewed articles, including foundational work on bounded width CSPs and absorption theory in universal algebra. Labs/Teams: Part of the Algorithmics Research Group, collaborating with Libor Barto, Andrei Bulatov, and others on CSP and algebraic complexity.
