Find Academic Supervisors

• Finite Free Probability
• Non-commutative Probability
• Random Matrices
• +6 more

Dr. Daniel Perales Anaya is a Visiting Assistant Professor in the Department of Mathematics at Texas A&M University, affiliated with the College of Arts & Sciences. He completed his Ph.D. in 2022 at the University of Waterloo under the supervision of Alexandru Nica. His research focuses on Finite Free Probability, a field at the intersection of free probability, random matrices, combinatorics, and non-commutative probability. He also investigates infinitesimal freeness, hypergeometric polynomials, and cumulant theory. He organizes the Free Probability and Operators Seminar at Texas A&M University and maintains an active research profile with contributions to journals like Transactions of the American Mathematical Society and Constructive Approximation . His work bridges classical analysis, operator algebras, and combinatorial structures, often leveraging finite free convolutions and non-crossing partitions. Publications span topics including infinitesimal distributions, hypergeometric polynomial zeros, and S-transforms in finite free probability. His research has been supported by institutions such as the Simons Foundation and Birkhäuser.

Jason R. GreenView profile

Professor

• Theoretical chemical physics
• Nonequilibrium statistical mechanics
• Data science
• +4 more

Jason R. Green is a Professor in the Department of Chemistry at the University of Massachusetts Boston. With a PhD from Purdue University (2007) and postdoctoral experience at the Universities of Chicago, Cambridge, and Northwestern University, his research bridges theoretical chemistry, physics, and data science to explore nonequilibrium systems. His work focuses on transforming chemical energy into dynamically functional materials through interdisciplinary approaches. Education: B.S., Case Western Reserve University (cum laude, 2002) Ph.D., Purdue University (2007) with NASA Graduate Fellowship NSF Postdoctoral Fellow at University of Chicago and University of Cambridge Research Interests: Theoretical chemical physics Nonequilibrium statistical mechanics Data science applications in chemical systems His recent publications analyze electrochemical material dynamics (ACS Nano 2024), chemically driven self-assembly (Chemical Science 2024), and thermodynamic speed limits across disciplines (Nature Physics 2020, Physical Review X 2022). He has received prestigious fellowships including NASA's Graduate Student Researchers Program and NSF Postdoctoral Fellowship. The Green Research Group at UMB applies theory, computation, and data science to understand energy transformation in synthetic and biological materials.

• Stochastic Analysis
• Constructive Quantum Field Theory
• Statistical Mechanics of Multiscale Systems
• +9 more

Professor Massimiliano Gubinelli is the Wallis Professor of Mathematics at the University of Oxford and a Professorial Fellow at St. Anne's College. He leads the Stochastic Analysis Group within the Mathematical Institute, where his research focuses on stochastic analysis, constructive quantum field theory, and the intersection of probability theory with partial differential equations (PDEs) and renormalization group methods. His work spans statistical mechanics of multiscale systems, analysis of PDEs with random terms, homogenisation theory, mathematical quantum mechanics, path-integral formalisms, and non-commutative probability/geometry. He has pioneered paracontrolled distribution techniques to study singular stochastic PDEs and explored rough paths in ramification and transport equations. Recent publications highlight advancements in the sine-Gordon model via stochastic quantization, nonlinear PDEs with modulated dispersion, and ρ-irregularity in stochastic systems. His research bridges stochastic analysis, quantum field theory, and PDEs, emphasizing pathwise behavior and renormalization. Scientific Awards Junior member of the Institut Universitaire de France (2013–2018) Invited session speaker at the 2018 International Congress of Mathematicians (ICM) in Rio He contributes to scientific software development as a lead developer of TeXmacs , an open-source platform for technical documents, and teaches courses such as C8.1 Stochastic Differential Equations (MT22). No formal student advisement or grant details are provided.

Magdalena E. MusatView profile

Professor

• Functional Analysis
• Operator Algebras
• Noncommutative Probability Theory
• +3 more

Magdalena E. Musat is a Professor at the Department of Mathematical Sciences, University of Copenhagen, within the Faculty of Science. She holds a Ph.D. from the University of Illinois at Urbana-Champaign (2002) and has extensive teaching experience across institutions including the University of Copenhagen, University of Southern Denmark, and UC San Diego. Her research focuses on Functional Analysis, Operator Algebras, and their intersections with noncommutative probability, quantum information theory, and group theory. She has organized major conferences like the Harald Bohr Lectures and the ICM Satellite conference on Operator Algebras. Her academic contributions include over 15 publications in top journals such as Inventiones Mathematicae and Communications in Mathematical Physics. She has supervised numerous Ph.D. and Master’s students, including current advisee Rasmus Kløvgaard Stavenuiter. Her work explores topics like quantum channel factorization, Connes embedding problem, and non-commutative L_p-spaces. Musat serves as Head of Studies for the Master’s Program in Mathematics and co-organizes the Department Colloquium. Her teaching spans advanced courses on Functional Analysis, Operator Algebras, and Measure Theory. Professional activities include organizing masterclasses on Sofic Groups and Approximation Properties for Operator Algebras.

Nathaniel EldredgeView profile

Professor

• Probability theory
• Stochastic processes
• Functional analysis
• +6 more

Nathaniel Eldredge is a Professor and PhD Program Coordinator in the Department of Mathematical Sciences at the University of Northern Colorado (UNC), part of the College of Natural and Health Sciences. His research focuses on probability theory, stochastic processes, and geometric analysis, with specializations in sub-Riemannian manifolds, Lie groups, and partial differential equations. Eldredge holds a Ph.D. in Mathematics from the University of California, San Diego (2009), an M.A. (2005), and a B.S. from Harvey Mudd College (2003). Education: Ph.D. Mathematics, UC San Diego, 2009 M.A. Mathematics, UC San Diego, 2005 B.S. Mathematics, Harvey Mudd College, 2003 His research interests bridge probability and analysis, particularly in stochastic processes on geometric structures like Lie groups and sub-Riemannian manifolds. Recent work includes studies on hypoelliptic heat kernels, functional inequalities, and transportation inequalities in complex geometric settings. Publications span topics such as hypercontractivity, logarithmic Sobolev inequalities, and heat kernel analysis on stratified Lie groups. His work often intersects functional analysis and geometric analysis, with applications to stochastic modeling and mathematical physics. While no formal awards are listed, his extensive publication record reflects sustained contributions to stochastic and geometric analysis. Eldredge has advised the PhD program at UNC since 2018, following roles as Associate Professor (2018–present) and Assistant Professor (2013–2018). He previously held postdoctoral positions at Cornell University (2009–2013) and UC San Diego (2003–2009).

• Infinite-Dimensional Analysis
• Non-Commutative Probability
• Mathematical Finance
• +3 more

Dr. Irina Rodionova is a Senior Lecturer in Mathematics at Swansea University, affiliated with the School of Mathematics and Computer Science within the Faculty of Science and Engineering. She specializes in infinite-dimensional analysis and non-commutative probability. As the Undergraduate Admissions Tutor for the Department of Mathematics, she oversees student recruitment and academic support. Her research focuses on orthogonal polynomials, quantum probability, and stochastic processes, with notable contributions to non-commutative structures and Fock space extensions. Dr. Rodionova holds a fellowship from the Higher Education Academy, recognizing her teaching excellence. She is available for postgraduate supervision and teaches modules on mechanics, financial mathematics, and Lie theory. Her publications span topics like non-commutative Lévy noises and anyon Fock spaces, appearing in journals such as Infinite Dimensional Analysis, Quantum Probability and Related Topics and Russian Mathematical Surveys . She contributes to both undergraduate and postgraduate education, integrating actuarial science syllabi into her courses on financial mathematics.

Arie LevitView profile

Senior Lecturer

• Discrete Groups
• Geometric Group Theory
• Analytic Group Theory
• +6 more

Dr. Arie Levit is a Senior Lecturer (tenure track) in the Department of Theoretical Mathematics at Tel Aviv University's School of Mathematics, a position he has held since 2021. Previously, he served as a Gibbs Assistant Professor at Yale University from 2017. His academic career centers on pure mathematics with emphasis on structural properties of discrete groups and dynamical systems. His educational background includes: B.A in Mathematics from the Hebrew University of Jerusalem (2004) M.A in Mathematics from the Hebrew University of Jerusalem (2012) Ph.D. in Mathematics from the Weizmann Institute of Science (2017) under Prof. Tsachik Gelander Levit's research spans discrete groups, geometric and analytic group theory, and ergodic theory, with significant contributions to lattice theory, invariant random subgroups, character rigidity, and group stability. His work integrates algebraic, geometric, and probabilistic frameworks to solve fundamental problems in classification and rigidity of group actions, particularly in non-Archimedean and hyperbolic settings. Analysis of his 14 publications (2014-2024) reveals evolving focus from foundational lattice theory toward contemporary stability phenomena and character theory, with 60% of recent work (2022-2024) addressing permutation stability, Hilbert-Schmidt representations, and ergodic properties of group actions. Key methodological threads include the application of ergodic theory to group-theoretic classification and the development of analytical tools for stability problems. His scholarly recognition includes: Klein Prize (2017) ISF-BSF research grant (2020) As principal investigator of the ISF-BSF grant, Levit leads research on group stability and ergodic theory. His extensive collaborations with Gelander, Lubotzky, and Lazarovich demonstrate active mentorship within the global mathematics community. His work is conducted within Tel Aviv University's Theoretical Mathematics department, which maintains strong international partnerships in geometric group theory and dynamics.

Ping ZhongView profile

Associate Professor

• Free Probability
• Random Matrix Theory
• Operator Algebras
• +2 more

Ping Zhong is an Associate Professor in the Department of Mathematics at the University of Houston. He holds a Ph.D. from Indiana University Bloomington and joined UH in 2024 after serving as Assistant Professor at the University of Wyoming (2018-2024) and completing postdoctoral work at the University of Waterloo. His research explores free probability theory, operator algebras, and applications of random matrix theory to high-dimensional statistics. Educational background includes: Ph.D. Mathematics, Indiana University (2014) M.S. Mathematics, Peking University (2008) B.S. Applied Mathematics, Huazhong University of Science and Technology (2005) Research focuses on fundamental mathematical structures in probability with emerging applications in quantum physics and statistical learning. Current investigations bridge theoretical frameworks with computational approaches for high-dimensional data analysis. Recent publications demonstrate consistent contributions to spectral analysis of random operators and convergence properties in non-commutative probability spaces. Works frequently appear in premier mathematics journals including Transactions of the AMS and Journal of the European Mathematical Society.

Madhur TulsianiView profile

Professor

• Theoretical Computer Science
• Complexity Theory
• Algorithm Design
• +3 more

Madhur Tulsiani is a Professor at the University of Chicago's Department of Computer Science and a researcher at the Toyota Technological Institute at Chicago (TTIC). His research focuses on theoretical computer science, particularly complexity theory and algorithm design, with applications in coding theory and information theory. He has been supported by NSF grants 1254044, 1816372, and 2326685. Education: Bachelor’s in Computer Science, IIT Kanpur (2001-2005) Ph.D. in Computer Science, UC Berkeley (2005-2009), advised by Luca Trevisan Postdoctoral fellowships at the Institute for Advanced Study (IAS) and Princeton University Research Interests: Mathematical foundations of computation Complexity theory and algorithm design Coding theory and error-correcting codes Sum-of-Squares hierarchies and approximation algorithms Recent Contributions: Pioneering work on list decodable codes and expander-based constructions Advances in approximation algorithms for high-dimensional expanders Lower bounds for Sum-of-Squares algorithms using high-dimensional expanders Teaching: Information and Coding Theory Mathematical Toolkit (linear algebra/probability) Summer REU programs in theoretical computer science Students: Advised PhD students including Fernando Granha Jeronimo, Goutham Rajendran, and Shashank Srivastava Co-advised students with Sasha Razborov, Janos Simon, and others Labs/Groups: Member of the Theoretical Computer Science Group at TTIC and UChicago, contributing to cross-disciplinary research in algorithms and complexity.

Mikael de la SalleView profile

Professor

• Functional Analysis
• Group Theory
• Operator Algebras
• +3 more

Mikael de la Salle is a CNRS Senior Researcher (Directeur de recherche) at the Institut Camille Jordan, Université Claude Bernard Lyon 1. He received his PhD from Université Paris 6 in 2009 and his Habilitation from ENS de Lyon in 2016. Previously, he held positions at Institut de Mathématiques de Jussieu, DMA, Laboratoire de Mathématiques de Besançon, and École Normale Supérieure de Lyon. During 2023-2024, he was a member at the Institute for Advanced Study in Princeton. His research focuses on interactions between functional analysis and group theory, including operator algebras, harmonic analysis, ergodic theory, and geometric group theory. His publications demonstrate expertise in non-commutative functional analysis, group representations, and geometric properties of discrete groups. He has received the Prix Charles-Louis de Saulce de Freycinet (2021) and was an invited speaker at the International Congress of Mathematicians (2022). He advises or has advised several students including Ignacio Vergara, Emilie Mai Elkiaer, Guillaume Dumas, and Martin Gilabert Vio. He organizes academic events such as the Entropies School/Workshop (2018) and serves on editorial boards for Confluentes Mathematici, Mathematische Zeitschrift, and Proceedings of the London Mathematical Society.

• Probability Theory
• Mathematical Physics
• Stochastic Analysis
• +3 more

Pierre PERRUCHAUD is a Postdoctoral researcher at the Department of Mathematics within the Faculty of Science, Technology and Medicine (FSTM) at the University of Luxembourg. His research focuses on advanced topics in stochastic analysis, mathematical physics, and functional analysis. He is affiliated with the Maison du Nombre research unit located in Esch-sur-Alzette. His work explores complex systems such as hypoelliptic operators, stochastic processes in geometric settings, and homogenization theory. Key contributions include studies on non-de Finetti theorems, loop soup representations, and kinetic Dyson Brownian motion. His research bridges probability theory with applications in quantum field theory and statistical mechanics. Pierre's publications reflect a deep engagement with both theoretical and applied aspects of stochastic analysis, often involving interdisciplinary approaches combining geometry and probability. His current projects likely continue to advance understanding in anisotropic kinetic systems and asymptotic expansions for hypoelliptic equations. No scientific awards or grants are explicitly mentioned in the provided information. His advising record remains unspecified, though his postdoctoral role suggests active participation in academic mentorship.

Augusto GerolinView profile

Assistant Professor

• Optimal Transport Theory
• Mathematical Physics
• Theoretical and Computational Chemistry
• +4 more

Augusto Gerolin is an Assistant Professor jointly appointed in the Departments of Mathematics and Statistics and Chemistry and Biomolecular Sciences at the University of Ottawa. He holds a Tier II Canada Research Chair in Artificial Intelligence at the Interface of Chemistry and Mathematics. His research focuses on Optimal Transport Theory, Mathematical Physics, Theoretical and Computational Chemistry, and Machine Learning. Gerolin’s work bridges quantum chemistry, mathematical analysis, and computational methods, with applications in Density Functional Theory and quantum information science. He obtained his PhD from the University of Pisa and was a Marie Skłodowska-Curie fellow at Vrije Universiteit Amsterdam. He is a member of the European Laboratory for Learning and Intelligent Systems (ELLIS) and leads a research group exploring AI-driven solutions in chemistry and mathematics. His current projects include developing optimal transport frameworks for quantum systems, advancing machine learning algorithms in scientific computing, and fostering collaborations across disciplines through initiatives like the OQMG Network. Gerolin’s research has led to advancements in multi-marginal optimal transport, entropy-regularized methods, and the strong-interaction limit of density functional theory. His group actively collaborates with institutions worldwide, including the Fields Institute, IPAM, and the University of Genoa. He has supervised numerous PhD, Master’s, and undergraduate students, many of whom have contributed to cutting-edge studies in computational chemistry, quantum algorithms, and mathematical analysis. Key awards include the Canada Research Chair designation, and his work has been supported by grants from NSERC, MITACS, and the University of Ottawa. Gerolin is also committed to diversity in science, endorsing principles such as the Diversity Axioms, and advocates for academic solidarity with researchers affected by global conflicts.

• Quantum Cognition
• Cognitive Psychology
• Decision Making
• +7 more

Emmanuel M. Pothos is a Professor in the Department of Psychology at City, University of London, within the School of Arts and Social Sciences. He has held prior academic positions as Senior Lecturer at City, Reader at Swansea University, and Lecturer at both the University of Edinburgh and Bangor University, reflecting a sustained and progressive academic career in cognitive psychology. PhD in Psychology, University of Oxford (1995–1998) BSc in Physics, Imperial College London (1992–1995) His research primarily focuses on quantum cognition, where he applies the mathematical formalism of quantum theory to model cognitive phenomena such as decision-making, judgment, and similarity perception. He investigates violations of classical probability in human cognition, context effects, and the role of ambiguity and conflict in choices. His interdisciplinary work draws from psychology, physics, and computational modeling. The recent trend in his publications reveals a strong emphasis on formal modeling of cognitive processes using quantum probability, with applications extending into behavioral health, financial systems, and foundational questions in decision theory. His work frequently appears in high-impact journals across psychology, physics, and interdisciplinary sciences, indicating a broad scholarly impact. While no formal awards are listed in the provided data, his extensive publication record in top-tier journals and frequent peer-review activities for leading outlets such as Nature , Psychological Review , and PNAS reflect significant academic recognition and service. Dr. Pothos actively collaborates with researchers internationally and has contributed to theoretical advances in understanding how quantum-like structures can explain human cognitive biases and complexities. Although no direct mention of student supervision is made, his role as a professor and prolific researcher implies involvement in mentoring graduate students and leading research initiatives. He has not indicated any lab or research group name, but his work clearly involves collaborative projects in cognitive modeling and decision science.

• Theory of Computation
• Discrete Algorithms
• Theoretical Computer Science
• +5 more

Michael Saks is a Distinguished Professor of Mathematics at Rutgers, The State University of New Jersey . He is affiliated with both the Department of Mathematics and the Computer Science Department as a graduate faculty member. His research focuses on theory of computation and discrete algorithms , with applications in computational complexity, combinatorics, and algorithmic analysis. His recent publications include work on edit distance approximations , randomized algorithms , discrepancy of random matrices , and Boolean function analysis , reflecting a strong emphasis on theoretical foundations. He has contributed to journals such as Combinatorica , Journal of Graph Theory , and Discrete Applied Mathematics , and served on editorial boards and conference program committees, including the 2014 IEEE Conference on Computational Complexity . Michael Saks maintains active research and teaching pages , including guidance for graduate applicants and links to seminars like the Discrete Mathematics/Theory of Computing Seminar . He also participates in initiatives such as the Center for Computational Intractability and DIMACS .

Tuomas OrponenView profile

Associate Professor

• Geometric Measure Theory
• Harmonic Analysis
• Fractal Geometry
• +4 more

Tuomas Orponen is an Associate Professor in the Department of Mathematics and Statistics at the University of Jyväskylä, Faculty of Mathematics and Science. His research focuses on geometric measure theory, harmonic analysis, and fractal geometry, with particular interests in incidence geometry, Fourier analysis, and metric geometry. Orponen is affiliated with the research groups for Nonlinear Partial Differential Equations and Geometric Measure Theory and Harmonic Analysis. His work explores topics such as projections of fractal sets, additive properties of fractal configurations, and geometric incidence problems. He leads projects in approximate incidence geometry, multi-scale incidence geometry, and incidences on fractals. His research trends include advancing understanding of geometric and analytic properties of fractals, exploring connections between incidence geometry and harmonic analysis, and studying the interplay between discrete and continuous geometric structures. Recent articles highlight investigations into radial projections, Kakeya-type sets, and the discretised ABC sum-product problem. Orponen has no listed scientific awards but has contributed to significant collaborative projects, including studies on Heisenberg group geometries and singular integrals. He actively publishes in top journals such as Transactions of the American Mathematical Society and Geometric and Functional Analysis. His research is anchored in two core teams: the Nonlinear PDE group and the Geometric Measure Theory team, reflecting his dual focus on analytical and geometric methodologies.