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Professor Catherine Greenhill is a faculty member at the School of Mathematics and Statistics, UNSW Sydney , where she serves as Professor and head of the Combinatorics group. Her academic career spans institutions including the University of Queensland, University of Oxford, University of Leeds, University of Melbourne, and Australian National University. D.Phil., University of Oxford (1996) M.Sc. (Research) in Combinatorics (1992) B.Sc. (Hons) in Pure Mathematics (1991) Her research focuses on the intersection of discrete mathematics , theoretical computer science , and probability , particularly in asymptotic combinatorics , probabilistic methods , and analysis of algorithms . Her work includes asymptotic enumeration of combinatorial structures and design of randomized algorithms for graph sampling and counting. Her recent publications (2025–2021) center on random graphs and hypergraphs , with key contributions to switch Markov chains , degree sequence analysis , and chromatic number bounds . These works reflect her expertise in probabilistic combinatorics and algorithmic complexity . Scientific Awards: Fellow of the Australian Academy of Science (2022) Christopher Heyde Medal in Pure Mathematics (2015) June Griffith Fellowship (2013) Hall Medal (2010) Advising and Grants: She has supervised numerous PhD/Masters students and secured multiple ARC Discovery Grants (2019–2021, 2014–2016, 2012–2014). Her grants address topics like hypergraph modeling, random discrete structures, and network analysis in illicit drug trafficking.

• Combinatorics
• Graph Theory
• Applied Probability
• +6 more

Jinhyung Park is an Associate Professor in the Department of Mathematical Sciences at KAIST, Daejeon, Korea. He obtained his Ph.D. from KAIST in 2014 under Prof. Sijong Kwak and was mentored as a CMC Fellow at KIAS (2014–2019). His research focuses on Algebraic Geometry , particularly syzygies of algebraic varieties , secant varieties , and positivity of line bundles . Education: Ph.D., KAIST (2014); MS/BS, KAIST and University of Chicago (2002/2001). Research Interests: His work explores geometric properties of projective manifolds, singularities in algebraic geometry, and applications of Okounkov bodies to divisors and syzygies. Recent trends include Castelnuovo-Mumford regularity bounds (e.g., for threefolds with rational singularities) and subadditivity of Okounkov bodies in fiber spaces. Teaching: Courses include Matrix Groups, Algebraic Geometry, and Calculus. He previously taught at Sogang University and Purdue University. Professional Affiliations: Member of the Korean Mathematical Society, American Mathematical Society, and other international societies. Organized the 8th East Asia Number Theory Conference at KAIST (2019).

• Algebraic Geometry
• Syzygies of Algebraic Varieties
• Secant Varieties
• +6 more

Anoosheh Heidarzadeh is an Assistant Professor in the Department of Electrical and Computer Engineering at Santa Clara University's School of Engineering. He holds a Ph.D. in Electrical and Computer Engineering from Carleton University (2012) and previously served as a Visiting Assistant Professor at Texas A&M University (2018-2022) and Associate Research Scientist at the same institution (2015-2017). His postdoctoral research was conducted at the California Institute of Technology (2013-2014). His research focuses on: Information and coding theory : Fundamental limits of data transmission and storage systems Private and secure computing : Protocols for confidential data processing in networked environments Fault-tolerant distributed systems : Resilient computation frameworks for large-scale applications Distributed machine learning : Scalable algorithms for collaborative learning architectures Recent publications (2021-2022) demonstrate strong emphasis on privacy-preserving computation (covering 73% of articles) and distributed coding techniques (67% of articles), with innovations in private information retrieval, matrix operations, and group testing methodologies. Theoretical contributions dominate (87%), while 13% address applied challenges like COVID-19 screening.

• Information and coding theory
• Private and secure computing
• Fault-tolerant distributed computing
• +3 more

Afonso S. Bandeira is a Professor in the Department of Mathematics (D-MATH) at ETH Zurich, where he conducts research at the intersection of mathematics, statistics, and computer science. He maintains strong affiliations with several interdisciplinary research centers including the Institute For Operations Research (IFOR), the Max Planck ETH Center for Learning Systems, the ETH Foundations of Data Science, and the ETH AI Center, with a courtesy appointment at D-ITET. Bandeira actively teaches courses including Mathematics of Signals, Networks, and Learning, and Mathematics of Data Science. His research focuses on High Dimensional Probability, Random Matrices, Mathematical Statistics, Theoretical Computer Science, Combinatorics, and Mathematical Optimization. Bandeira's work often explores the theoretical foundations of data science, examining phase transitions in statistical problems, computational barriers, and the geometry of high-dimensional spaces. He maintains a research group blog called Randomstrasse101 that emphasizes open problems in his field. Analysis of his recent publications reveals a strong focus on matrix and tensor concentration inequalities, synchronization problems, nonconvex optimization landscapes, and computational-statistical tradeoffs in high-dimensional inference. His work bridges theoretical mathematics with practical applications in machine learning and data analysis, particularly examining where computational limitations arise in statistical problems. Bandeira actively mentors students and researchers, currently supervising several doctoral candidates including Daniil Dmitriev, Konstantin Donhauser, Anastasia Kireeva, Kevin Lucca, Chiara Meroni, Gil Kur, Petar Nizic-Nikolac, and Almut Roedder. He emphasizes that students working with him should participate in the DACO seminar and group meetings, and encourages prospective students to have completed his Mathematics of Signals, Networks, and Learning or Mathematics of Data Science courses. He leads a research group focused on the mathematics of data science, with regular group meetings and seminars. Bandeira has developed comprehensive lecture notes including 'A Tour Through the Mathematics of Signals, Learning, and Networks' (2025) and 'Mathematics of Machine Learning' (2021), and previously authored 'Ten Lectures and Forty-Two Open Problems in the Mathematics of Data Science' (2015).

• High Dimensional Probability
• Random Matrices
• Mathematical Statistics
• +3 more

Maria Chudnovsky is a Professor of Mathematics at Princeton University and a former Professor of IEOR and Mathematics at Columbia University (2006-2014). Her research focuses on graph theory and combinatorics, with significant contributions to structural graph theory, perfect graphs, and algorithmic applications. Education: B.A. Summa Cum Laude (1996) and M.Sc. (1999) from Technion, Ph.D. (2003) from Princeton University Her work addresses fundamental problems in graph coloring, forbidden induced subgraphs, and combinatorial optimization, including the proof of the Strong Perfect Graph Theorem and development of algorithms for detecting graph structures. Notable awards include the MacArthur Foundation Fellowship (2013-2017), D.R. Fulkerson Prize (2009), and Henry Burchard Fine Professor of Mathematics (2022). She has held prestigious fellowships such as the Clay Mathematics Institute Research Fellowship (2003-2008). Grants: NSF DMS-EPSRC Grant DMS-2120644 (2021-2024), US Army Research Office Grant W911NF-16-1-0404 (2016-2020), and multiple NSF grants She has advised numerous PhD/MSc students and postdocs, including Sophie Spirkl, Mingxian Zhong, and Tara Abrishami. Her outreach includes popular science communication on YouTube's Numberphile and participation in initiatives promoting women in STEM.

• Graph Theory
• Combinatorics
• Discrete Mathematics
• +3 more

Brett Kolesnik is a Research Fellow in the Department of Statistics at the University of Warwick. His research focuses on probability theory, random structures, bootstrap percolation, and interactions with combinatorics. He has held postdoctoral fellowships at UC Berkeley, San Diego, and the University of Oxford, and was a Senior Demy at Magdalen College. His work includes organizing workshops on bootstrap percolation and collaborating with leading researchers in probability and combinatorics. Education: PhD in Mathematics from the University of British Columbia (advised by Omer Angel). Notable awards include the NSERC Postdoctoral Fellowship and the Florence Nightingale Bicentennial Fellowship in Statistics. Research interests span bootstrap percolation models, random graph dynamics, and stochastic processes. Recent work includes studies on Brownian map geometry, tournament score sequences, and Coxeter group structures. Selected articles explore topics such as critical beta-splitting processes, Catalan percolation, and random walks on algebraic structures. His publications appear in top journals like Electronic Journal of Probability and Annals of Applied Probability . Awards include the Florence Nightingale Fellowship and NSERC Postdoctoral Fellowship. Professional involvement includes organizing the 2024 BIRS workshop on Bootstrap Percolation and contributing to interdisciplinary collaborations in probability and combinatorics.

• Probability Theory
• Random Structures
• Bootstrap Percolation
• +4 more

Joseph Eremondi is an Assistant Professor in the Department of Computer Science at the University of Regina, Faculty of Science, Canada. He began his tenure in 2024 after serving as a Royal Society Newton International Fellow at the University of Edinburgh, where he conducted postdoctoral research with Ohad Kammar in the Laboratory for Foundations of Computer Science. He earned his PhD from the University of British Columbia (UBC) under the supervision of Ron Garcia at the UBC Software Practices Laboratory. His research is centered on programming languages theory, with a strong focus on type systems that enhance software reliability and usability. He is particularly known for his work in dependent types, gradual typing, and the integration of both paradigms. His research interests include: Dependent pattern matching and its semantic foundations Gradual dependent types and approximate normalization Error message generation and usability in dependently typed languages Static analysis using set constraints and SMT solvers Theoretical properties of reversal-bounded counter automata and shuffle operations His recent publications, appearing in premier venues like POPL, ICFP, and CPP, reflect a consistent trajectory toward making advanced type systems more accessible and practical. Key themes include coverage semantics for dependent pattern matching, formal models of gradual dependent typing, and improving the developer experience through better tooling and error diagnostics. Notable scientific recognitions include the NSERC Discovery Grant (awarded in 2025) and the prestigious Royal Society Newton International Fellowship. These awards underscore the impact and promise of his research program on the usability of dependently typed programming languages. Joseph is actively mentoring and recruiting graduate students, particularly in areas such as dependently typed programming (Lean, Agda, Idris, Coq), gradual typing, live programming environments, and static analysis. He emphasizes close collaboration within a small, focused research group. He has also served on program committees, including for TyDe and POPL Artifact Evaluation, demonstrating active engagement in the programming languages community. His work bridges theoretical rigor with practical implementation, evident in his artifact releases on GitHub and integration with tools like Ott and DrRacket. He maintains a personal website and open-source repositories that support reproducibility and community involvement.

• Programming Languages
• Type Theory
• Dependent Types
• +12 more

Brandon Seward is an Associate Professor of Mathematics at the University of California San Diego (UC San Diego), where they conduct research and teach in the Department of Mathematics. They use the pronouns they/them or he/him . Education Ph.D. in Mathematics, University of Michigan , 2015 Research Interests Their work lies at the intersection of ergodic theory, topological dynamics, descriptive set theory, and group theory . They investigate geometric, combinatorial, and entropic properties of actions of countable groups, with special emphasis on the divide between amenable and non-amenable groups. Publications & Research Impact Across 27 refereed papers (2014-2024), Seward has advanced entropy theory for non-amenable groups, Borel combinatorics of group actions, and structure theorems for measure-preserving actions. Their work has appeared in top journals such as Inventiones Mathematicae , Journal of the American Mathematical Society , and Duke Mathematical Journal . Scientific Awards Michael Brin Dynamical Systems Prize for Young Mathematicians (2018) – awarded for outstanding contributions to dynamical systems. Teaching & Mentorship Seward regularly teaches core undergraduate courses (e.g., Math 142A Introduction to Analysis) and organizes the UC San Diego Group Actions Seminar , a weekly research forum featuring international speakers. They serve as a faculty mentor and are actively involved in graduate student supervision and seminar coordination. Contact & Office Email: bseward@ucsd.edu Office: AP&M 5739, 9500 Gilman Drive, La Jolla, CA 92093-0112

• Ergodic theory
• Topological dynamics
• Descriptive set theory
• +1 more

Raphael Hauser is an Associate Professor in Numerical Mathematics at the University of Oxford's Mathematical Institute, Director of Graduate Studies - Teaching, and Tanaka Fellow in Applied Mathematics at Pembroke College. His affiliations include membership in the Data Science, Numerical Analysis, and Mathematical and Computational Finance research groups, as well as a fellowship at the Alan Turing Institute. Education: PhD in Operations Research, Cornell University, Ithaca, USA Dipl. Math. ETH, Swiss Federal Institute of Technology (ETH Zurich), Switzerland Research interests span data science, numerical optimisation, medical imaging, distributed computing, and applied probability/statistics. His work integrates mathematical rigor with practical applications, particularly in optimization algorithms, machine learning theory, and medical imaging technology. Publications focus on optimization theory, stochastic processes, medical imaging systems, and computational finance, with recurring themes in non-convex optimization guarantees, PCA variants, and X-ray tomography innovations. Awards: Oxford University Teaching Award (2007) SIAM Optimization Prize (2005) SIAM Student Paper Prize (2000) Advising includes 15+ DPhil students and 40+ MSc students, with projects in optimization, finance, imaging, and machine learning. Current postdocs and students are affiliated with the Alan Turing Institute and industrial partners like Siemens and Macquarie Group. He leads teams in the Mathematical Institute's research groups and collaborates with the Alan Turing Institute on large-scale data science initiatives.

• Data Science
• Numerical Optimisation
• Medical Imaging
• +3 more

Yulan Qing is an Assistant Professor in the Department of Mathematics at the University of Tennessee, Knoxville (UTK), part of the College of Arts and Sciences. She holds a Ph.D. in Mathematics from Tufts University. Her research focuses on low-dimensional topology, geometric group theory, asymptotic properties of groups, and big mapping class groups. Notable projects include studies on Gromov boundaries, genericity in groups, and curve graphs. She has published extensively in journals like Geometry & Topology and the Journal of the London Mathematical Society. Dr. Qing has organized conferences such as the 53rd Barrett Memorial Lectures and the GGTea Webinar, fostering collaboration in geometric group theory. She has taught courses like Honors Topology at UTK and supervised graduate students including Sagnik Jana and Alex Squires. Her work bridges theoretical foundations with applications in topology and geometry. Recent invited talks include presentations at the University of Virginia, Caltech, and the 2nd China-Russia Conference on Topology. She actively mentors undergraduate and graduate students, contributing to initiatives like the Math Circle programs at Tufts and MIT's RSI Summer Program.

• Low-Dimensional Topology
• Geometric Group Theory
• Asymptotic Properties of Groups
• +4 more

Ben Green is the Waynflete Professor of Pure Mathematics at the University of Oxford and a Fellow of Magdalen College. His work spans additive combinatorics, analytic number theory, harmonic analysis, ergodic theory, discrete geometry, and group theory, with a focus on interdisciplinary approaches. Research Interests: Additive combinatorics and its applications to primes Analytic number theory (prime distribution, L-functions) Harmonic analysis (Fourier methods, spectral theory) Ergodic theory and its combinatorial applications Discrete geometry (ordinary lines, convex structures) Group theory (approximate groups, expansion) Article Trends: His recent work emphasizes multiplicative functions, Ramsey-type problems in number theory, expansion in finite groups, and extremal set theory. Themes include prime gaps, arithmetic progressions, and interactions between analysis and algebra. Scientific Awards: Clay Research Award (2004) Ostrowski Prize (2005) Whitehead Prize (2005) Leverhulme Prize (2007) European Mathematical Society Prize (2008) Royal Society Fellow (2010) Sylvester Medal (2014) Senior Whitehead Prize (2019) Advising: Ben has supervised numerous D.Phil students across additive combinatorics, analytic number theory, and related fields. Past students hold postdoctoral and academic positions globally.

• Additive Combinatorics
• Analytic Number Theory
• Harmonic Analysis
• +3 more

Alan Hammond is a Professor in the Department of Statistics at the University of California, Berkeley. His research focuses on rigorous mathematical probability techniques applied to problems in statistical mechanics, including percolation theory, polymer models, and random growth processes. He has contributed to understanding critical phenomena, phase transitions, and universality classes in stochastic systems. Hammond's work spans topics such as KPZ universality, Brownian motion, and the geometry of random media. He has investigated models like last passage percolation, self-avoiding walks, and tug-of-war games, often uncovering deep connections between stochastic processes and nonlinear PDEs. His teaching includes courses on stochastic processes and statistical theory at both graduate and undergraduate levels. Notable research highlights include studies on fractal properties of Airy processes, stability in dynamical last passage percolation, and the behavior of geodesics in random environments. His contributions bridge probability theory with applications in physics and combinatorics.

• Statistical Mechanics
• Mathematical Probability
• Probability Theory
• +5 more

Chan Song Heng is an Associate Professor in the Division of Mathematical Sciences at the School of Physical and Mathematical Sciences, Nanyang Technological University (NTU), Singapore. He has been affiliated with NTU since 2007. His academic journey includes a B.Sc. (Hons) in Mathematics from the National University of Singapore (2001) and a Ph.D. in Mathematics from the University of Illinois at Urbana-Champaign (2005). His research focuses on advanced mathematical topics such as partition theory, q-series, mock theta functions, and number theory. Recent work includes studies on identities analogous to Jacobi, Fermat-Wilson theorems, and applications of Rogers-Fine identities. His publications explore combinatorial, analytic, and algebraic aspects of these fields, with notable contributions to modular forms, theta functions, and partition congruences. Dr. Chan’s articles often intersect with classical problems in mathematics, blending historical insights with modern analytical techniques. Notable themes include exploring identities through modular forms, analyzing partition statistics (ranks/cranks), and studying mock theta functions. Despite his prolific output, no specific scientific awards or student advisees are listed in the provided materials.

• Mathematics
• Number Theory
• Combinatorics
• +3 more

Gábor Somlai is a mathematics researcher at Eötvös Loránd University's Faculty of Science, affiliated with the Department of Algebra and Number Theory since 2006. He is a core member of the HUN-REN-ELTE Geometric and Algebraic Combinatorics Research Group (previously MTA-ELTE until 2023) and participates in the Asymptotic Group Theory ERC project. His institutional roles include contributions to the Mathematics Doctoral School and the Institute of Mathematics. His research spans Algebra , Combinatorics , and Number Theory , with emphasis on spectral sets, tiling problems, group theory, and finite geometry. Recent work explores cyclotomic polynomials, the generalized trifference problem, and connections between tiling and spectral properties in finite abelian groups. His publications reveal a strong focus on combinatorial number theory and algebraic methods in discrete geometry. Somlai's publication trends show sustained contributions to theoretical foundations of tiling and spectral sets (testing Fuglede's conjecture in cyclic groups) Cayley graph properties and CI-group classifications polynomial methods in finite geometry and direction problems His work bridges pure algebra with combinatorial applications, often resolving long-standing conjectures in specialized domains. As part of the HUN-REN-ELTE research group, he collaborates on geometric and algebraic combinatorics projects, leveraging ERC funding for asymptotic group theory investigations. His research infrastructure includes access to the Alfréd Rényi Institute of Mathematics (http://www.renyi.hu) resources.

• Algebra
• Combinatorics
• Number Theory
• +3 more

Jean-Pierre Fouque is a Professor in the Department of Statistics and Applied Probability (PSTAT) at the University of California, Santa Barbara. His research focuses on stochastic processes, financial mathematics, systemic risk, and reinforcement learning, with a particular emphasis on mean field games and multi-scale stochastic models. He explores applications in portfolio optimization, risk management, and algorithmic finance. His work combines theoretical advancements in stochastic analysis with practical applications in economics and finance. Notable contributions include developing models for systemic risk in financial networks, analyzing reinforcement learning algorithms in mean-field frameworks, and studying stochastic volatility effects in derivatives pricing. Recent research trends include integrating deep learning techniques for systemic risk quantification, advancing multi-scale asymptotic methods for portfolio optimization, and investigating strategic interactions in financial systems using game-theoretic approaches. His publications frequently address topics such as stochastic volatility calibration, optimal investment strategies under uncertainty, and the dynamics of financial markets under stress scenarios. Dr. Fouque has contributed to foundational textbooks and edited volumes on systemic risk and mean field games. His interdisciplinary work bridges probability theory, mathematical finance, and computational methods, impacting both academic research and practical risk management practices.

• Stochastic Processes
• Financial Mathematics
• Systemic Risk
• +6 more