Christino Tamon is a Professor of Computer Science at Clarkson University's Coulter School of Engineering & Applied Sciences. He holds a Ph.D. from the University of Calgary (1993-1996), an M.S. from the University of Toronto (1990-1992), and a B.Sc. in Computer Science and Applied Mathematics from the University of Calgary (1986-1990). His research focuses on theoretical computer science, quantum computing, graph theory, and machine learning, with notable contributions to quantum state transfer and quantum walks on graphs. Recipient of the Clarkson University Distinguished Teaching Award (2009) and New Teacher Award (2000). Principal Investigator on multiple NSF grants, including quantum computing and REU mathematics programs. Visiting appointments at institutions like the Institut Henri Poincaré and the University of Waterloo. Research interests include quantum algorithms, graph spectral theory, and the application of algebraic methods to discrete systems. His work on quantum walks explores perfect state transfer, fractional revival, and spatial search optimization. Recent grants support quantum advantage in algorithm design and interdisciplinary research in quantum dynamics. Advised numerous graduate students and mentors undergraduate research through REU programs. Active in professional service, including organizing workshops on quantum mathematics and algebraic graph theory.
Associate Professor Oded Yacobi is affiliated with the University of Sydney's Faculty of Science. His research focuses on advanced algebraic structures, including representation theory, categorification, and geometric methods in quantum groups. He holds a Ph.D. from the University of California, San Diego (2009), followed by postdoctoral roles at the University of Toronto and Tel Aviv University. Yacobi is actively involved in grants exploring dualities in representation theory and braid group dynamics. His work bridges algebraic geometry and combinatorics, with recent articles addressing Weyl groups, braid group actions, and affine Grassmannians. He leads a vibrant research program with collaborations spanning North America and Australia. Education: Ph.D. in Mathematics, University of California, San Diego (2009) Postdoctoral Fellowships: University of Toronto, Tel Aviv University Research Interests: Representation theory of algebraic groups and quantum groups Categorification techniques and their applications Geometric methods in Lie theory and combinatorics Braid groups and their algebraic structures Key Grants: 2023: ARC DP Grant (Braid groups via representation theory and machine learning) 2018: ARC DP Grant (New Dualities in Modular Representation Theory) Professional Activities: Maintains an active research group and collaborates internationally. His work has been published in top journals like Mathematische Zeitschrift and Advances in Mathematics. He is also engaged in teaching advanced algebra courses at the University of Sydney.
Ian Wanless is a Research Professor at the School of Mathematics, Monash University. He specializes in combinatorics, with a focus on Latin squares, graph theory, and matrix permanents. His work bridges theoretical mathematics and applications in information technology, such as coding and experimental design. Wanless leads collaborative projects funded by the Australian Research Council, including studies on combinatorial structures and hypergraph matchings. He has authored over 120 peer-reviewed articles, with recent work addressing quantum states, Latin square properties, and quasigroup isomorphisms. Key Awards: Australian Mathematical Society 2009 Medal Collaborations: Global partnerships with institutions in the US, Europe, and Asia His research emphasizes universal solutions to combinatorial puzzles, such as Sudoku and the four-color theorem, while prioritizing theoretical rigor over direct applications.
Ecaterina Sava-Huss is a Full Professor in Mathematics at the University of Innsbruck, Austria, affiliated with the Department of Mathematics within the Faculty of Mathematics, Computer Science and Physics. She holds a PhD from Graz University of Technology (2010) and a Habilitation in Mathematics (2019). Previously, she served as an associate professor and tenure-track assistant professor at the University of Innsbruck, and as an assistant professor and visiting scholar at institutions including TU Graz and Cornell University. Her research focuses on stochastic processes, particularly random walks and rotor walks on graphs, fractals, and aggregation models. Key interests include the interplay between structural properties of infinite state spaces and stochastic processes. She has organized conferences such as the Austrian Stochastics Days and is the outreach coordinator for the Institute of Mathematics, engaging in public science initiatives like the MIP Day and Girls' Day. Her funding includes an FWF Grant P34129 (2021–2025) on growth models and quasi-random walks, and a prior Erwin Schrödinger Fellowship (2015–2016). She has supervised numerous PhD and Master’s students, with research topics ranging from branching processes to quantum probability. Her work has been published in journals such as Advances in Applied Probability , Bernoulli , and Journal of Fractal Geometry .
Dr. Tim Seppelt is a postdoctoral researcher at the IT University of Copenhagen , working under the mentorship of Prof. Radu Curticapean. Previously, he earned his PhD from RWTH Aachen University with supervisors Prof. Martin Grohe and Prof. Michael Schaub. His research focuses on theoretical computer science, specifically homomorphism indistinguishability , a framework connecting graph isomorphism, quantum information, and logical equivalences. Current Role: Postdoc in Theoretical Computer Science, ITU Education: PhD in Computer Science, RWTH Aachen University Tim's work addresses algorithmic meta-theorems for homomorphism indistinguishability over minor-closed and treewidth-bounded graph classes. He has extended Lovász-type results to CMSO2 logic, resolved complexity conjectures for the Lasserre hierarchy, and classified quantum group-induced indistinguishability relations. His research spans quantum computing , graph algorithms , and descriptive complexity , often intersecting with applications in machine learning and finite model theory. Recent publications include a 2025 paper on quantum group-driven homomorphism indistinguishability and a 2024 journal article on logical equivalences and forbidden minors. He presented at workshops like the Graph Learning Meets TCS (Simons Institute, 2025) and delivered tutorials on finite model theory at Finite and Algorithmic Model Theory 2025 (Les Houches, France).
Heiko Dietrich is a Professor in the School of Mathematics at Monash University and serves as the Associate Dean Graduate Education in the Faculty of Science. His roles include overseeing graduate education, research leadership, and editorial board memberships. He holds a doctoral degree from the University of Braunschweig (2009) and has held positions at institutions including the University of Trento and University of Auckland. Research Interests His research focuses on computational group theory , computational algebra , finite groups , and Lie algebras . He applies computational methods to problems in algebra and has contributed to areas such as Hadamard matrices and classification of quantum states. Recent Research Trends Recent work includes studies on maximal subgroups of the Monster group, coclass theory, and algorithmic approaches to group isomorphism. His publications span theoretical advances and applications in quantum information and combinatorics. Awards: Australian Research Council Discovery Early Career Researcher Award (2013) Cheryl E. Praeger Visiting Research Fellowship (2022) 2019 Victorian Tall Poppy Award Advising & Grants He has supervised over 20 students, including HDR candidates and Master’s researchers. Notable projects include investigations into finite p-groups, computational group theory, and combinatorial identities. He led research initiatives funded by ARC and international collaborations, such as the Computing with Lie groups and algebras project (2019–2023). Labs & Affiliations Editorial roles include Associate Editorships at Mathematische Nachrichten , Journal of Computational Algebra , and Beiträge zur Algebra und Geometrie . He contributes to STEM education through CSIRO’s STEM Professionals in Schools program.
Dr. Alexey Bochkarev is a researcher in the Optimization Department at the Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU), affiliated with the Felix Klein Center. His work focuses on discrete optimization, quantum computing applications, and network security. Current affiliation: RPTU, Optimization Department Contact: Building 31, Room 455, Paul Ehrlich Street, 67663 Kaiserslautern | a.bochkarev@math.rptu.de Research Interests Quantum computing for combinatorial optimization Monte Carlo tree search in adversarial network scenarios BDD-based representations for facility location problems Dynamic optimization under uncertainty Recent Publications His 2024 publications highlight quantum computing advancements and Monte Carlo methods for interdiction problems, while earlier works explore BDD alignment in network optimization. Key trends include hybrid quantum-classical algorithms and stochastic search frameworks for infrastructure protection.
Jin-Yi Cai is a distinguished Professor of Computer Science and Steenbock Professor of Mathematical Sciences at the University of Wisconsin at Madison, where he has been a faculty member since 2000. Previously, he held academic positions at State University of New York at Buffalo (Professor 1996-2000, Associate Professor 1993-1996), Princeton University (Assistant Professor 1989-1993), and Yale University (Assistant Professor 1986-1989). He has also been a Radcliffe Institute Fellow at Harvard University (2007-2008) and a Guggenheim Fellow and Visiting Professor at the University of Toronto (1999-2000). Dr. Cai earned his Ph.D. in Computer Science from Cornell University in 1986, an M.A. in Mathematics from Temple University in 1983, and a Certificate in Mathematics from Fudan University in 1981. His academic journey spans prestigious institutions across the United States and demonstrates a consistent trajectory of scholarly excellence. Professor Cai's research focuses on theoretical computer science, particularly computational complexity theory, with significant contributions to holographic algorithms, counting constraint satisfaction problems, and graph homomorphisms. His work bridges computer science and mathematics, developing sophisticated algorithms and proving fundamental complexity results. His research has evolved from foundational work in structural complexity and oracle separations to specialized work in holographic algorithms and counting problems, demonstrating both depth and breadth in theoretical computer science. His publication record shows a consistent output of high-impact research, with major contributions spanning over three decades. His work on holographic algorithms represents a particularly innovative strand of research that has opened new avenues in computational complexity. The progression of his research demonstrates increasing specialization in counting problems while maintaining connections to broader theoretical frameworks in computer science and mathematics. 2022 Simons Fellowship 2022 CCF Award for Overseas Outstanding Contribution 2022 Fellow, American Mathematical Society (AMS) 2021 Fulkerson Prize in Discrete Mathematics 2021 Gödel Prize in Theoretical Computer Science 2014 Steenbock Professorship, UW Madison 2001 ACM Fellow 1998 John Simon Guggenheim Fellowship 1994 Sloan Fellowship Professor Cai has served as Editor of the Journal of Computer and System Sciences and Associate Editor of the Journal of Computational Complexity. His work has been recognized with numerous prestigious fellowships including the Guggenheim Fellowship, Sloan Fellowship, and Humboldt Research Award. His research has had significant impact in theoretical computer science, earning him the Gödel Prize and Fulkerson Prize, two of the most prestigious awards in theoretical computer science and discrete mathematics respectively.
Joseph Sawada is a Professor at the School of Computer Science , University of Guelph , specializing in combinatorial algorithms , graph theory , and universal cycles . His research aims to efficiently list non-isomorphic combinatorial objects like necklaces, Lyndon words, and de Bruijn sequences with constant-change Gray codes. Key projects : COS++ (combinatorial object server), debruijnsequence.org Software entrepreneurship : Co-founder of FreshBooks (accounting software) and Brown and Beatty (AI-powered labor dispute resolution). Research keywords : Combinatorial algorithms, de Bruijn sequences, universal cycles, Gray codes, graph theory, combinatorial generation. Selected publications include work on de Bruijn sequences (Discrete Mathematics 2015), successor rules for pancake flipping (Theoretical Computer Science 2015), and k-critical P5-free graphs (Discrete Applied Mathematics 2015). His algorithms have applications in data compression, quantum error correction, and constraint satisfaction problems.
Prof. Dr. Erich Grädel is a full professor in the Mathematical Foundations of Informatik group at RWTH Aachen University, where he conducts research at the intersection of logic, computer science, and mathematics. His work lies in the Department of Mathematics, Computer Science and Natural Sciences, focusing on logic and theoretical computer science. Institution: RWTH Aachen University Department: Mathematical Foundations of Informatik Research Focus: Logic in Computer Science, Algorithmic Model Theory, Semiring Semantics, Dependence Logic His primary research interests include logic and games, algorithmic model theory, fixed-point logics, and semiring semantics for provenance analysis. He has pioneered work in logics of dependence and independence, extending classical logical frameworks to model information flow and uncertainty. His recent publications emphasize semiring-based provenance in first-order and fixed-point logic, Büchi games, and team semantics, often in collaboration with Val Tannen and Matthias Naaf. The trend in his recent articles (2021–2025) reveals a deep and sustained investigation into the algebraic and semantic foundations of logic, particularly through semiring semantics. His work applies logical methods to database theory, verification, and game theory, focusing on how information and strategies can be tracked and analyzed via algebraic structures. Topics include provenance in infinite structures, locality theorems, zero-one laws, and logical characterizations of computational phenomena. Erich Grädel has held significant editorial responsibilities in the logic community: Editor, Logical Methods in Computer Science (since 2004) Editor, Mathematical Logic Quarterly (since 2012) Editorial Board Member (Corner Editor for Logic and Games), Journal of Logic and Computation (since 2007) Editor, Journal of Symbolic Logic (2008–2013) He chaired the European GAMES Research-Training Network (2002–2013) and has co-edited five books, including Lectures in Game Theory for Computer Scientists (Cambridge University Press, 2011). He has advised numerous PhD students, including Faried Abu Zaid, Łukasz Kaiser, and Wied Pakusa. His research group has included long-term collaborators and former members such as Dietmar Berwanger, Martin Otto, and Richard Wilke. He has received no explicitly listed scientific awards in the provided text, but his sustained editorial roles and leadership in major research networks indicate high recognition in the field. His research group, associated with the Mathematical Foundations of Informatik, has been active for decades, with current members including Sophie Brinke and former members forming a substantial list of researchers in logic and theoretical computer science. The group has contributed significantly to algorithmic model theory, automata, and logic games.
Andrea Torsello is a researcher at the University of York, specializing in 3D shape analysis, graph-based machine learning, and quantum computing applications in computer vision. His work bridges theoretical and applied domains, focusing on pattern recognition, network thermodynamics, and remote sensing. PhD from University of York (2004) Published extensively in journals like IEEE Transactions and Pattern Recognition Research interests include: Quantum-inspired graph analysis 3D reconstruction techniques Manifold learning for complex networks Thermodynamic modeling of time-evolving systems Key contributions involve: Quantum walk-based graph similarity measures k-Anonymity for graph data Physics-driven CNN models for ocean wave reconstruction Game-theoretic approaches to shape matching
Wolfgang Bock is an Associate Professor (Docent) in Stochastic Analysis at Linnaeus University, where he joined as a Senior Lecturer in August 2023 and was promoted to Associate Professor in December 2023. He serves as Program Director for the Master's Program in Mathematics and is a member of the Faculty Board. His academic career spans institutions in Germany, Portugal, and Sweden, with a strong focus on stochastic processes and their applications. His educational background includes: PhD in Stochastic Analysis (2013) from Technische Universität Kaiserslautern, Germany, supervised by Martin Grothaus Postdoctoral fellowship (2013-2014) at the Center of Mathematical Analysis and its Applications (CMAF) in Lisbon, Portugal Lecturer position (2014 onwards) at Technische Universität Kaiserslautern Permanent senior lecturer (Akademischer Rat) from 2015, responsible for Engineering Mathematics Bock's research centers on Stochastic Analysis, with particular expertise in White Noise Analysis, Non-Gaussian Analysis, and Mittag-Leffler Analysis. His work bridges theoretical mathematics with practical applications in epidemiology, especially in disease modeling for dengue and SARS-CoV-2. He has developed novel approaches to random time variation, non-linear Markov processes, and McKean-SDEs, contributing significantly to the understanding of complex stochastic systems. His recent publications demonstrate a consistent focus on extending classical Gaussian analysis to non-Gaussian settings, with increasing applications to real-world problems in epidemiology and physics. The research shows progression from theoretical foundations to practical applications, particularly in disease transmission modeling. Bock leads the Stochastic Analysis and Stochastic Processes research group and is also involved with the Computational Mathematics for Predictive Digital Twins (PreDiTwin) initiative. His research has attracted international collaborations across Europe, reflecting his commitment to enhancing Linnaeus University's international visibility in stochastic analysis.
Cristopher Moore is a Professor at the Santa Fe Institute, where he explores interdisciplinary research at the intersection of physics, computer science, and mathematics. His work focuses on phase transitions in computational problems, social network analysis, quantum algorithms, and algorithmic fairness in consequential decisions like criminal justice risk assessment. Organized decarbonization workshops for New Mexico's energy transition Developed topological classifications for n-body orbital dynamics Co-founded Journal of Weird-Ass Shit and Journal of Unpublished Results Research interests span from transparency in AI to quantum computing and social network theory . His recent work analyzes phase transitions in machine learning and the computational limits of pattern detection in noisy data. Key article trends include quantum computation ( Graph Isomorphism , Quantum Walks ), complex systems ( Sandpiles , Cellular Automata ), and algorithmic justice frameworks. All work emphasizes both theoretical barriers and practical policy implications.
Michael Bronstein is the DeepMind Professor of Artificial Intelligence at the University of Oxford and Founding Scientific Director at the Aithyra Institute. He holds affiliations with Imperial College London (previous) and institutions like Stanford, MIT, and Harvard. His research focuses on geometric deep learning, graph neural networks, protein design, and non-human species communication. Bronstein received his PhD from the Technion in 2007 and has been awarded multiple fellowships and grants, including ERC, Google, and Amazon awards. Education: PhD in Computer Science, Technion, 2007 Research Interests: His work spans geometric deep learning, graph neural networks, 3D shape analysis, and applications in protein design. Notable projects include protein interaction design using surface fingerprints and advancing graph neural network architectures. He also explores AI in non-human communication, combining machine learning with biological systems. Publications: Recent work emphasizes knowledge graph foundation models, graph homomorphism analysis, and generative models for discrete data. His research bridges theoretical foundations (e.g., graph expressivity) with practical applications in biomedicine and AI. Awards: EPSRC Turing AI Fellowship Royal Society Wolfson Research Merit Award Academia Europaea Membership IEEE/IAPR/ELLIS Fellowships Advising & Grants: Supervises students in AI and graph learning. Active in securing ERC, Google, and industry grants. His entrepreneurial ventures include founding companies like Fabula AI (acquired by Twitter). Labs/Teams: Leads Graph Learning Research at DeepMind and collaborates with interdisciplinary teams in AI, biology, and quantum systems.
William J. Martin is a Full Professor in the Department of Mathematical Sciences at Worcester Polytechnic Institute (WPI) , with affiliated appointments in Computer Science and Bioinformatics. He earned his BA, MA, and PhD from the State University of New York Potsdam and the University of Waterloo. Research Interests: Algebraic Combinatorics, Association Schemes, Quantum Information Theory, Cryptology, and K-12 Education Outreach His recent publications focus on quantum computing, association schemes, and cryptography. Articles span topics like quantum error correction, homomorphic encryption, and algebraic structures in discrete mathematics. Scientific Awards: Erskine Fellowship (2024) Grants include multiple NSF and National Security Agency awards for research in association schemes, quantum information, and cryptographic systems. He co-founded the Northeast Combinatorics Network and is active in educational outreach, including math clubs and curriculum development.
