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Christian BargetzView profile

Professor

• Nonlinear Functional Analysis
• Banach Spaces
• Locally Convex Spaces
• +4 more

Christian Bargetz is a Professor of Functional Analysis at the University of Innsbruck, Austria, affiliated with the Faculty of Mathematics, Computer Science, and Physics (MIP). His primary research focuses on nonlinear functional analysis, Banach space theory, and distribution theory. He teaches advanced courses such as Optimization, Distribution Theory, and Functional Analysis, demonstrating his expertise in both theoretical and applied aspects of his field. Education: Completed his PhD in 2012 at the University of Innsbruck under the supervision of Norbert Ortner. His diploma thesis (2008) explored differential behaviors with Ulrich Oberst. Bargetz has held continuous academic positions since 2008, including roles as a lecturer and researcher. Research Interests: Specializes in iterative projection methods, generic properties of nonexpansive mappings, Fréchet spaces, and vector-valued distributions. His work bridges functional analysis with geometric measure theory and optimization, with applications in metric geometry and topological tensor products. Publications: Over 30 peer-reviewed articles in prestigious journals such as Canadian Journal of Mathematics , Journal of Mathematical Analysis and Applications , and Proceedings of the American Mathematical Society . Recent work includes studies on extremal nonexpansive mappings and Lipschitz function spaces. Grants & Projects: Principal investigator in FWF-funded projects on nonexpansive mappings and Banach spaces. Collaborates internationally, including with institutions in Israel, Poland, and Serbia. Teaching: Leads advanced courses in functional analysis, optimization, and distribution theory. Supervises bachelor's theses and master's projects on topics like extension operators for Lipschitz functions. Affiliations: Active member of the Functional Analysis working group and regularly participates in international conferences such as the Banach Afternoon, Winter School in Abstract Analysis, and DMV-ÖMG Annual Conferences.

Sean HoweView profile

Assistant Professor

• arithmetic geometry
• algebraic geometry
• representation theory
• +2 more

Sean Howe is an Assistant Professor in the Department of Mathematics at the University of Utah, where he has been employed since July 2019. His research is supported by NSF grants DMS-2201112 and DMS-2501816. In the academic year 2023-2024, he was a Friends of the Institute for Advanced Study Member at the special year on p-adic arithmetic geometry at the Institute for Advanced Study. Dr. Howe received his PhD from the University of Chicago in 2017 under the supervision of Matt Emerton. Prior to his position at Utah, he was an NSF Postdoctoral Scholar at Stanford University from September 2017 to June 2019. He earned a joint master's degree from Leiden University and Universite Paris-Sud 11 through the ALGANT program in 2012 and completed his undergraduate studies at the University of Arizona. Dr. Howe's research spans arithmetic and algebraic geometry, representation theory, and number theory, with a particular focus on p-adic aspects. His work often explores the connections between geometry and number theory through the lens of p-adic methods, including p-adic Hodge theory, perfectoid spaces, and the Langlands program. He has made significant contributions to understanding cohomological structures in mixed characteristic settings, the geometry of moduli spaces, and the statistical properties of L-functions. His extensive publication record demonstrates a strong trajectory in advancing p-adic geometry and its applications. Recent work shows increasing focus on cohomological smoothness in mixed characteristic, p-adic periods, and the interplay between random matrix theory and arithmetic statistics. His research often bridges abstract theoretical frameworks with concrete computational approaches. NSF Postdoctoral Scholar NSF grants DMS-2201112 and DMS-2501816 Dr. Howe is an active mentor, currently advising five PhD students: Minhua Cheng, Madison Delmoe, Shea Engle, Abhay Goel, and Suo Jun Tan. He has successfully graduated two PhD students: Matthew Bertucci (2025) and Hanlin Cai (2024). He also regularly mentors undergraduate researchers, with notable projects including Emil Geisler's work on stable multiplicities in configuration space cohomology and Daniel Koizumi's software for computing braid monodromy of cubic surfaces. His teaching portfolio includes advanced courses in algebraic topology, number theory, and algebra, reflecting his broad expertise across pure mathematics. He has taught courses such as Math 6950 (Topics in Algebraic Topology), Math 4400 (Introduction to Number Theory), and Math 6320 (Modern Algebra II).

Kenneth RossView profile

Professor

• Database Systems
• Query Processing
• Query Language Design
• +7 more

Kenneth Ross is a Professor in the Computer Science Department at Columbia University in New York City. His primary appointment is within the Department of Computer Science, with affiliations including the Foundations of Data Science Committee. His work bridges theoretical database research and practical system implementation. His research focuses on database systems with particular expertise in query processing, query language design, data warehousing, and architecture-sensitive database system design. Additional research spans computational biology, especially analysis of large genomic data sets. Current projects include Linear Algebra Operators in Databases for machine learning workloads and Repeats and Somatic Mutation analysis in genomics. His work consistently addresses the intersection of hardware capabilities and database system design. Ross leads the Database Research Lab at Columbia, which has produced significant work on query optimization, GPU database processing, and hardware-conscious database systems. His recent publications demonstrate strong focus on adapting database systems to modern hardware including GPUs, SIMD processors, and persistent memory. His scientific recognition includes: Packard Foundation Fellowship Sloan Foundation Fellowship NSF Young Investigator Award Distinguished Faculty Teaching Award (2008) Ross actively advises undergraduate engineering students (juniors with last names P-Z) and has taught foundational courses including Introduction to Databases and Programming and Problem Solving for over two decades. His teaching portfolio shows consistent engagement with both theoretical concepts and practical implementation challenges in computer science education.

Torsten GrustView profile

Professor

• Database Systems
• Programming Languages
• Query Optimization
• +6 more

Torsten Grust is a Professor of Computer Science at the University of Tübingen, leading the Database Systems research group since 2008. Previously, he held professorships at TU München and TU Clausthal. He earned his M.Sc. (Diploma) and Ph.D. in Computer Science from Universität Konstanz in 1994 and 1999, respectively. His research focuses on database languages, query and programming language technology, and scalable processing of non-relational queries. He bridges database and programming language research, emphasizing mutual benefits between the fields. **Education:** Ph.D. in Computer Science, University of Konstanz (1999) M.Sc. (Diploma), Computer Science, University of Konstanz (1994) Visiting Scientist, IBM Silicon Valley Laboratories (2000) **Research Interests:** Design and optimization of database languages Query compilation and execution engines Integration of functional programming with SQL Query provenance and debugging **Awards and Honors:** ACM SIGMOD Reproducibility Award (2021) University of Tübingen Teaching Award (2021/22) Winner of Dyalog 2019 APL Program Solving Competition Member of the VLDB Endowment Board of Trustees (2022–2027) **Advising & Grants:** Guided numerous students, including alumni such as Alexander Ulrich, Benjamin Dietrich, and Christian Duta Recipient of grants supporting research in query compilation, provenance analysis, and database language design **Labs & Teams:** Leads the Database Systems research group at University of Tübingen Collaborates with the National Institute of Informatics (Tokyo) on query and programming languages

Jeremy GibbonsView profile

Professor

• Functional Programming
• Programming Languages
• Software Engineering
• +3 more

Jeremy Gibbons is a Professor of Computing at the University of Oxford, affiliated with the Department of Computer Science within the Faculty of Computer Science. He serves as Director of the Professional Programmes, overseeing part-time postgraduate degrees in Software Engineering. His roles include Chair of the Faculty of Computer Science (2012–2016), Director of the Software Engineering Programme, and Fellow of Kellogg College. Gibbons' research focuses on programming methodologies, particularly functional and object-oriented languages, with an emphasis on program calculation, design patterns, and bidirectional transformations. He leads the Algebra of Programming research group and is Editor-in-Chief of the Journal of Functional Programming and The Art, Science, and Engineering of Programming . Education includes a D.Phil. from Oxford University. His work spans formal methods, domain-specific modeling for clinical trials (e.g., CancerGrid project), and semantic frameworks for software systems. He has advised numerous students and contributed to open-access initiatives in publishing. Key collaborations include roles in ACM SIGPLAN and IFIP Working Groups 2.1 and 2.11. Research interests emphasize foundational aspects like profunctor optics, categorical programming, and algorithm design. Notable projects include datatype-generic programming and metadata-driven engineering for clinical trials. His work bridges theoretical computer science with practical applications in software architecture and system design.

Tom LeinsterView profile

Professor

• Category Theory
• Metric Geometry
• Algebra
• +3 more

Tom Leinster is a mathematician at the University of Edinburgh, specializing in category theory, metric geometry, and their applications to areas such as algebra, topology, and mathematical biology. His research focuses on the concept of magnitude, a measure for metric spaces and enriched categories, as well as entropy and diversity. He has authored influential books including *Basic Category Theory* and *Entropy and Diversity: The Axiomatic Approach*. Leinster's work bridges foundational mathematics with interdisciplinary applications, emphasizing the interplay between abstract structures and concrete problems. His research interests span category theory, metric geometry, algebraic topology, and mathematical biology. Key contributions include foundational work on magnitude and its connections to geometric measure theory, entropy characterization, and categorical frameworks for diversity measurement. Leinster also engages in mathematical education and ethics, advocating for responsible research practices. Notable publications include recent advancements in magnitude homology of Euclidean sets, extremal magnitude in metric spaces, and entropy modulo primes. His work often highlights interdisciplinary applications, such as biodiversity quantification and information-theoretic foundations.

Richard GarnerView profile

Lecturer

• Category Theory
• Algebraic Structures
• Homotopy Type Theory
• +3 more

Richard Garner is a lecturer at Macquarie University's School of Mathematical and Physical Sciences, Faculty of Science and Engineering. He specializes in teaching mathematics to engineering and computing students in units like MATH2055 and MATH1007, focusing on problem-solving and real-world applications. His teaching philosophy emphasizes authentic mathematical experiences, blending abstract concepts with practical examples, such as connecting multivariable calculus to AI technologies. School: School of Mathematical and Physical Sciences University: Macquarie University Teaching Areas: Mathematics for engineering and computing, convolution, multivariable calculus Richard won a Student Nominated Award in the 2023 Vice Chancellor’s Learning and Teaching Awards, reflecting his commitment to student-centered education. He prioritizes clarity in course design, using visual tools and accessible materials to enhance learning, and fosters a supportive environment where students feel comfortable asking questions. Key Teaching Strategies Organized iLearn layouts following Macquarie University's standards Multiple formats for lecture materials (diagrams, color-coded slides) Weekly task clarity and real-world problem framing Live worked examples and transparent success criteria His research spans category theory, computational effects, and homotopy theory, with publications on topics like comodels, monoidal bicategories, and enriched categories. Richard's work bridges abstract mathematics with applications in computer science and logic. Scientific Awards 2023 Vice Chancellor’s Learning and Teaching Award (Student Nominated) Students praise his ability to make complex concepts intuitive, his enthusiasm for mathematics, and his dedication to explaining the 'why' behind the subject. His teaching design, including time-sensitive banners and structured weekly content, has been highlighted as exemplary.

Sebastian RudolphView profile

Professor

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Description Logics
• +7 more

Prof. Sebastian Rudolph is a Professor of Computational Logic at the Institute for Artificial Intelligence , Faculty of Computer Science , TU Dresden. Since 2021, he has been an Affiliate Member of the Faculty of Mathematics. His research spans theoretical and applied artificial intelligence, focusing on Knowledge Representation and Reasoning through formalisms like Description Logics, Existential Rules, and Formal Concept Analysis, with applications in Semantic Technologies. 2017 : ERC Consolidator Grant for decidability principles in logic-based knowledge representation 2006-2013 : Postdoctoral researcher, project leader, and Privatdozent at KIT's Institute AIFB 2011 : Habilitation at KIT Earlier : PhD in Algebra and teaching qualification in mathematics, physics, and computer science at TU Dresden His recent publications address decidability of logical reasoning, non-monotonic extensions in formal concept analysis, standpoint logics, and multiagent systems. He supervises the DeciGUT and KIMEDS projects, and is involved in the SECAI and ScaDS.AI centers. Teaching activities include courses on Theoretical Computer Science, Existential Rules, and Formal Concept Analysis.

• Probability
• Mathematical Physics
• Combinatorics
• +2 more

Alexey Bufetov is a Professor at Leipzig University, holding an ERC Starting Grant for his research in Integrable Probability (2022-2027). Previously, he served as a W2-Professor ("Bonn Junior Fellow") at the Hausdorff Center for Mathematics (2018-2021) and as a CLE Moore Instructor at Massachusetts Institute of Technology (2015-2018). His research centers on Probability Theory , with deep connections to Mathematical Physics and Combinatorics . Key areas include integrable probability, stochastic particle systems (ASEP/TASEP), random tilings, Schur generating functions, and representation-theoretic aspects of probability. His work often bridges abstract mathematical structures with physical models from statistical mechanics. Bufetov's recent publications reveal a strong focus on integrable systems and asymptotic analysis , particularly exploring connections between Mallows measures, vertex models, and random matrix theory. His 2025 work on Aztec diamond domino tilings exemplifies his signature approach combining combinatorial structures with probabilistic methods. His primary recognition is the ERC Starting Grant "Integrable Probability" (2022-2027), supporting his cutting-edge research program. Bufetov has maintained a prolific collaborative network, frequently publishing with leading researchers including Alexei Borodin, Vadim Gorin, Leonid Petrov, and Kailun Chen. His work appears in top journals such as Advances in Mathematics , Duke Mathematical Journal , and Communications in Mathematical Physics .

Josef DickView profile

Professor

• Numerical Integration
• Quasi-Monte Carlo Rules
• Number Theory
• +5 more

Professor Josef Dick serves as a Professor and Deputy Head in the School of Mathematics & Statistics at the University of New South Wales (UNSW). With a distinguished career in computational mathematics, he has established himself as a leading researcher in numerical integration methods and quasi-Monte Carlo theory. His work bridges theoretical mathematics with practical computational applications across various scientific domains. Dr. Dick earned his PhD in Mathematics from UNSW in 2004 and his MSc in Mathematics from the University of Salzburg in 2001. His academic journey reflects a strong foundation in both theoretical and applied mathematics, which has informed his subsequent research contributions. Professor Dick's research primarily focuses on numerical integration and quasi-Monte Carlo rules , employing techniques from number theory , abstract algebra (particularly finite fields), discrepancy theory , wavelet theory , and statistics . His work provides rigorous analysis of practical algorithms for computational problems, with implementations often provided in Matlab to bridge theory and application. His research has successfully addressed point distributions on the unit cube for numerical integration, completely uniformly distributed sequences for Markov chain quasi-Monte Carlo algorithms, and explicit constructions of uniformly distributed points on the sphere. Analysis of his recent publications (2022-2025) reveals a consistent focus on advancing quasi-Monte Carlo methods, with increasing integration of machine learning techniques and applications to complex computational problems. His work demonstrates strong interdisciplinary connections between pure mathematics, computational science, and practical engineering applications, particularly in uncertainty quantification and high-dimensional numerical integration. Discovery project from Australian Research Council (2012-2014): "Mathematics in the round - the challenge of computational analysis on spheres" Queen Elizabeth II Fellowship from Australian Research Council (2010-2014): "Algebraic methods for Markov Chain Monte Carlo and quasi-Monte Carlo" UNSW Vice Chancellor Fellowship (2006-2009) Professor Dick has supervised numerous PhD and Honours students working on topics including Quasi-Monte Carlo methods, Discrepancy Theory, Markov chain Monte Carlo, and Uncertainty Quantification. His research has been supported by significant grants from the Australian Research Council, including serving as Chief Investigator on multiple projects. Beyond his research, he serves as an Editor for the Journal of Complexity and Journal of Approximation Theory, demonstrating his leadership in the mathematical community. He teaches courses in Algebra and Mathematical Computing for Finance at UNSW.

Christine VespaView profile

Professor

• Algebra
• Algebraic Topology
• Category Theory
• +3 more

Christine Vespa is a Professor at Aix-Marseille Université affiliated with the Institute of Mathematics (I2M) in Marseille. Her research lies at the intersection of Algebra , Algebraic Topology , and Category Theory , focusing on polynomial functors , functor homology , and stable homology of group families. Education Habilitation à diriger des recherches (HDR), Université de Strasbourg, 2013. Thesis: Foncteurs polynomiaux et homologie stable à coefficients polynomiaux . Jury: William Dwyer, Vincent Franjou, Hans-Werner Henn, Nick Kuhn, Birgit Richter, Lionel Schwartz. Doctorat en Mathématiques, Université Paris 13, 2005. Thesis: La catégorie F_quad des foncteurs de Mackey généralisés pour les formes quadratiques sur F2 . Director: Lionel Schwartz. Research Interests Her work explores structural properties of polynomial functors and their applications in homology stability. She connects abstract category-theoretic frameworks with concrete algebraic and topological problems, such as stable homology for automorphism groups of free groups and orthogonal groups. Recent preprints address PROP structures , analytic exponential functors , and Jacobi diagrams , highlighting her engagement with algebraic topology and category theory. Article Trends Christine Vespa's publications and preprints emphasize algebraic topology and category theory . Recent trends include analyzing partition PROPs , exponential functors , and Jacobi diagrams in the context of stable homology. Earlier works delve into Hochschild homology , automorphism groups , and generalized Mackey functors , showcasing her contributions to homological algebra and representation theory. Advising Antoine Feltz (2020–2024): Foncteurs polynomiaux sur les catégories FI_d . Arthur Soulié (2015–2018): Foncteurs de Long-Moody et homologie stable des groupes de difféotopie . Andrea Cesaro (2012–2016): Pre-Lie algebras and operads in positive characteristic , co-supervised with Benoit Fresse. Labs & Teams She is a member of the Analyse, Géométrie, Topologie research group at I2M. She has organized academic events, including the 2014 Strasbourg workshop on Mac Lane's cubic construction and the 2015 Strasbourg Masterclass on Topological K-theory.

• Algebraic Geometry
• Tropical Geometry
• Combinatorics
• +3 more

Kristin Shaw is a Professor in the Department of Mathematics at the University of Oslo, specializing in Algebra, Geometry and Topology. She leads the research group on Algebraic and Topological Cycles in Tropical and Complex Geometries, funded by the BFS. Her office is located in room 1114 of Niels Henrik Abels hus, with contact information including email krisshaw@math.uio.no and phone +47 22855940. Shaw's research focuses on the connections between combinatorics and algebraic geometry over the real and complex numbers, with particular emphasis on tropical geometry. Her work bridges abstract mathematical theory with concrete geometric structures, exploring how combinatorial methods can illuminate deep properties of algebraic varieties. She has made significant contributions to understanding matroids, real algebraic curves, and the topology of hypersurfaces through tropical techniques. Her research demonstrates how combinatorial structures can reveal fundamental insights about algebraic varieties and their topological properties. Analysis of Professor Shaw's recent publications reveals a consistent focus on tropical geometry and its applications to classical algebraic geometry problems. Her work frequently examines the interplay between real and complex geometries, with particular attention to combinatorial structures underlying algebraic varieties. Key themes include matroid theory, enumerative geometry, and the topology of algebraic varieties, demonstrating how tropical methods can provide new insights into longstanding problems in algebraic geometry. Her research shows remarkable depth across multiple subfields while maintaining a coherent theoretical framework that connects combinatorial and geometric approaches. Professor Shaw leads the research group on Algebraic and Topological Cycles in Tropical and Complex Geometries, which is funded by the BFS. Prior to her position at the University of Oslo, she held postdoctoral positions at the Max Planck Institute Leipzig, the Technical University of Berlin, the University of Toronto, and participated in the Fields' Institute semester in Combinatorial Algebraic Geometry. Her collaborative work spans multiple international institutions, reflecting her active engagement in the global mathematical research community.

Timothy RileyView profile

Professor

• Geometric Group Theory
• Geometric Topology
• Algorithmic Complexity
• +3 more

Timothy Riley is a Professor in the Department of Mathematics at Cornell University, affiliated with the College of Arts and Sciences. His research focuses on geometric group theory, studying infinite discrete groups through geometric lenses such as Riemannian manifolds, graphs, and cell complexes. Key interests include curvature, geometric features of group presentations, and algorithmic complexity. He holds a D.Phil. from Oxford University (2002). Research spans geometric aspects of the word problem, hyperbolic groups, Dehn functions, and applications to cryptography and topology. His work integrates algebraic, topological, and computational perspectives. Notable collaborations include studies on hydra groups, Cayley graphs, and asymptotic cones. Publications emphasize geometric topology and group theory, with contributions to understanding filling invariants and geometric algorithmic properties. His office is 403 Malott Hall, and he maintains an active personal web page. No explicit awards are listed in the provided text, though he was part of news items related to teaching honors in 2024.

Tom SchrijversView profile

Professor

• Programming Languages
• Functional Programming
• Type Systems
• +6 more

Tom Schrijvers is a Professor at the Department of Computer Science in the Faculty of Engineering Science at KU Leuven, Belgium. He leads the Programming Languages Group within the Declarative Languages and Artificial Intelligence (DTAI) research group. His research focuses on programming languages, particularly functional and logic programming, with special emphasis on Haskell, type systems, and algebraic effects. His research interests include: Functional Programming, especially Haskell Type Systems and Type Theory Algebraic Effects and Handlers Logic Programming, particularly Prolog Constraint Programming Domain-Specific Languages Programming Language Theory Prof. Schrijvers' recent research has focused on effect systems, staged programming, and language composition. His work on algebraic effect handlers has been particularly influential, providing new insights into how effects can be modularly composed and handled in functional languages. He has also made significant contributions to the understanding of type classes and their implementation in Haskell. His publications demonstrate a consistent focus on practical applications of programming language theory, with work spanning from foundational type theory to applied domain-specific languages for areas like fluorescence microscopy. His research often bridges the gap between theoretical programming language concepts and practical implementation concerns. Prof. Schrijvers has supervised numerous PhD students to completion, including Pieter Wuille, Benoit Desouter, George Karachalias, Steven Keuchel, Amr Saleh, Alexander Vandenbroucke, and Ruben Pieters. He currently supervises PhD students Klara Mardirosian, César Santos, Gert-Jan Bottu, Koen Pauwels, Birthe van den Berg, and Roger Bosman. His research group has received funding from various sources including EU projects like GRACeFUL. The Programming Languages Group at KU Leuven, which he leads, focuses on functional (Haskell) and logic (Prolog, Datalog, CLP) programming languages, as well as general programming language theory. The group has been active in numerous research projects and collaborations across Europe.

Piotr ZwiernikView profile

Associate Professor

• Statistical Computing
• Theoretical Statistics
• High-dimensional Statistics
• +7 more

Piotr Zwiernik is an Associate Professor in the Department of Statistical Sciences at the University of Toronto's Faculty of Arts and Science, with a cross-appointment in the Department of Mathematics. Currently on leave from the University of Toronto, he is based in Barcelona following his return in July 2025. His academic journey includes a PhD in Statistics from the University of Warwick (2011), research positions at prestigious institutions including Mittag Leffler Institute, IPAM, TU Eindhoven, UC Berkeley, and the University of Genoa, and an Assistant Professorship at Universitat Pompeu Fabra in Barcelona (2016-2021). His research spans the intersection of statistics, mathematics, and computational methods, with particular emphasis on graphical models, covariance matrix estimation, convex analysis, tensors, and algebraic and combinatorial methods in statistics. Zwiernik's work demonstrates a consistent focus on high-dimensional statistics, mathematical statistics, and elegant theoretical frameworks that bridge abstract mathematics with practical statistical applications. His recent publications reveal a deepening exploration of tensor analysis, algebraic statistics, and the geometric properties of statistical models. Zwiernik serves as an associate editor for leading journals including Biometrika, Scandinavian Journal of Statistics, and Algebraic Statistics. His research program includes the development of the GOLAZO R package for asymmetric regularization of log-likelihood in Gaussian graphical models. As an academic leader, he has served as Associate Chair for Research in his department and actively participates in numerous international conferences and workshops, reflecting his significant standing in the statistical community. His recent publications show a strong trend toward algebraic and geometric approaches to statistical problems, with increasing focus on tensor methods, positivity constraints in statistical models, and the theoretical foundations of graphical models. The work demonstrates remarkable continuity in exploring the mathematical structures underlying statistical models while adapting to emerging challenges in high-dimensional data analysis. Zwiernik is committed to mathematical accessibility and education, guided by Federico Ardila's four axioms which emphasize equitable distribution of mathematical potential, joyful mathematical experiences, mathematics as a malleable tool, and treating every student with dignity and respect. He actively seeks PhD students with strong mathematical backgrounds for research at UPF or the Institute of Mathematics of UPC.