Find Academic Supervisors

Ashkan NikeghbaliView profile

Professor

• Quantitative Finance
• Probability Theory
• Random Matrix Theory
• +3 more

Ashkan Nikeghbali is a Professor of Quantitative Finance at the University of Zurich's Department of Finance, holding a part-time academic position. His research focuses on advanced topics in probability theory, random matrix theory, and their applications to quantitative finance, particularly in credit risk modeling and stochastic processes. He has contributed to areas such as Mod-Gaussian convergence, asymptotic analysis of random matrices, and statistical mechanics. His work often bridges pure mathematics and practical financial applications, addressing challenges in portfolio risk management and optimization. Research interests include the interplay between probability theory and algebraic structures, with notable studies on characteristic polynomials of random matrices, stochastic processes, and their implications in mathematical physics. He explores topics like high-dimensional optimization, graphons, and permutons, contributing to both theoretical advancements and applied financial models. His publications emphasize precise deviation analysis, approximation schemes, and the application of advanced mathematical techniques to understand complex systems. Despite no explicit mention of awards or grants, his extensive publication record highlights sustained contributions to probability and financial mathematics. No specific advising roles or student mentorship details are provided in the available texts.

Alexander LitvakView profile

Professor

• Convex Geometry
• Random Matrix Theory
• Probability Theory
• +3 more

Alexander Litvak is a Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta. His research focuses on convex geometry, random matrix theory, and probability theory with applications to high-dimensional geometry and stochastic processes. Education: He holds a Ph.D. from Tel Aviv University and an M.Sc. from Saint Petersburg State University. Research Interests: Litvak explores geometric probability, random structures, and their applications in optimization and functional analysis. His work often addresses questions related to convex bodies, matrix singularity, and the behavior of high-dimensional random systems. Key topics include minimal dispersion, random polytopes, and spectral properties of random graphs. Publications: His recent work (2020-2024) emphasizes probabilistic methods in convex geometry and random matrix theory, with notable contributions to linear bandits, sparse matrix analysis, and the circular law for digraphs. These studies reveal trends in understanding high-dimensional phenomena and probabilistic structures. Grants and Awards: No specific grants or awards listed in the provided materials. Advising and Labs: No student advisees or lab affiliations explicitly mentioned in the text.

James CrutchfieldView profile

Professor

• Nonlinear dynamics
• Condensed matter physics
• Physics of computation
• +4 more

Dr. James Crutchfield is a Distinguished Professor of Physics at the University of California, Davis. His research focuses on nonlinear dynamics, condensed matter physics, and the physics of computation. He explores interdisciplinary topics such as evolutionary dynamics, pattern discovery, and distributed robotics, often integrating principles from statistical mechanics and information theory. His work frequently addresses thermodynamic computing, quantum systems, and the interplay between structure and randomness in complex systems. Recent publications highlight his contributions to stochastic thermodynamics, quantum information processing, and the theoretical foundations of predictive systems. He has pioneered methodologies for analyzing trajectory fluctuations, entropy production, and the efficiency of information processing in both classical and quantum contexts. Dr. Crutchfield’s research bridges theoretical frameworks with practical applications, such as earthquake prediction via machine learning and the design of energy-efficient superconducting circuits. His lab’s work often emphasizes emergent organization in complex systems, leveraging tools from nonlinear dynamics and computational physics. While no specific awards are listed, his prolific publication record underscores his influence in these fields. Collaborations span physics, computer science, and engineering, reflecting his commitment to interdisciplinary innovation.

Chunlei LiView profile

Professor

• Cryptography
• Coding Theory
• Wireless Communications
• +4 more

Chunlei Li is a Professor in the Department of Informatics at the University of Bergen, specializing in Coding Theory and Cryptography. His research focuses on signal design, error-correcting codes, cryptographic primitives, and blockchain technology. He holds a PhD from the University of Bergen (2014) and has held postdoctoral positions at the University of Stavanger and the Selmer Center. He teaches courses in algebraic coding, cybersecurity, and cryptography. His research spans waveform design for wireless communications, feedback shift register sequences, rank metric codes, homomorphic encryption, and discrete mathematics. He leads projects such as 'Sequences and Their Applications' and contributes to conferences like SETA and NISK. Supervised students include those in symmetric cryptography, sequence design, and code-based cryptography. His work emphasizes cryptographic strength, with contributions to APN functions, permutation polynomials, and decoding algorithms for rank metric codes. He has authored numerous papers on topics like differential properties of functions and blockchain-based security systems.

• Mathematical physics
• Statistical mechanics
• Combinatorics
• +4 more

Tim Garoni is a Professor in the School of Mathematics at Monash University, specializing in mathematical physics and statistical mechanics. His research focuses on discrete models in classical statistical mechanics, spanning mathematical physics, probability theory, combinatorics, and computer science. Education: PhD in Science, University of Melbourne (awarded December 1, 2003) BSc (Hons) in Science, University of Melbourne (awarded December 1, 2000) Professor Garoni's primary research interests lie in equilibrium models including the Ising model, self-avoiding walk, percolation, and the Fortuin-Kasteleyn random-cluster model, as well as non-equilibrium models such as exclusion processes. He has a particular focus on high-dimensional behavior of equilibrium models and properties of Markov chains arising in Monte Carlo methods for discrete statistical mechanics, including questions about mixing times of finite Markov chains. His work often bridges theoretical mathematics with practical applications in areas such as traffic flow modeling. Recent publications show a strong focus on random walks, percolation theory, and high-dimensional systems, with significant contributions to understanding critical phenomena and finite-size scaling. His research also extends to transportation networks, demonstrating the interdisciplinary nature of his mathematical approaches. Professor Garoni is actively involved in multiple research projects, including Self-Interacting Random Walks (2023-2026), Random walks with long memory (2018-2022), and the ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights (2017-2021). He is also organizing academic events such as the AIM Day: Maths AI and Energy meet Industry @ Monash in 2024. As a supervisor, Professor Garoni accepts PhD students working on statistical mechanics and discrete probability projects. His research has resulted in over 49 publications and 8 research projects, demonstrating sustained scholarly productivity in his field.

Marta LewickaView profile

Professor

• Nonlinear Analysis
• Partial Differential Equations
• Calculus of Variations
• +4 more

Marta Lewicka is a Professor of Mathematics at the University of Pittsburgh, affiliated with the Dietrich School of Arts and Sciences. Her research focuses on nonlinear analysis, partial differential equations (PDEs), and calculus of variations, with applications to elasticity, geometric analysis, and game theory. She holds a PhD from SISSA, Italy, and has authored influential works such as A Course on Tug-of-War Games with Random Noise and Calculus of Variations on Thin Prestressed Films . Key awards include the 2021 AMS Fellowship and NSF award DMS-2006439. Her work bridges theoretical mathematics and applied fields, addressing geometric problems in elasticity, dimension reduction of thin films, and convex integration techniques for PDEs. She has organized international workshops and serves on editorial boards of journals like SIAM Journal of Mathematical Analysis. Teaching includes advanced courses on calculus of variations, real analysis, and partial differential equations. Her research also explores connections between stochastic processes (e.g., tug-of-war games) and PDEs, contributing to both pure and applied mathematical frameworks.

• Behavioral Public Administration
• Government Reform
• Administrative Burden
• +2 more

Sebastian Jilke is Provost's Distinguished Associate Professor at Georgetown University's McCourt School of Public Policy and co-director of the Better Government Lab. His research applies behavioral science to public management, examining how government reforms affect citizens and service delivery, particularly regarding administrative burdens and equity. His work demonstrates consistent focus on experimental approaches to public administration challenges, with recent publications examining policy implementation barriers, motivational structures in bureaucracy, and behavioral interventions. Research consistently addresses practical governance challenges through rigorous methodological designs. Jilke maintains active policy engagement, advising multiple federal agencies including OMB, SSA, and DHS. As co-editor of the Journal of Policy Analysis and Management, he shapes scholarly discourse at the intersection of behavioral science and governance.

Michel SchellekensView profile

Professor

• Artificial Intelligence
• Data Analytics
• Algorithmics
• +2 more

Michel Schellekens is Professor at University College Cork's School of Computer Science and Information Technology, specializing in Artificial Intelligence, Data Analytics, and Algorithmics. His research develops mathematical frameworks for complexity analysis, including quasi-metric spaces and entropy-based approaches for algorithm evaluation. Recent work focuses on low-power computing designs, reversible computing principles, and static analysis methods for energy-efficient software and hardware systems. He maintains collaborations through the Complex and Adaptive Systems Laboratory (CASL).

• Infinite Dimensional Analysis
• Point Processes
• Noncommutative Probability
• +3 more

Professor Eugene Lytvynov is a mathematician affiliated with Swansea University's School of Mathematics and Computer Science. He holds the academic rank of Professor in the Mathematics department. His research focuses on infinite-dimensional analysis, point processes, noncommutative probability, and umbral calculus. Recent work explores non-Abelian anyon quasiparticles and basis-free umbral calculus. He is available to supervise postgraduate students and maintains active research collaborations through platforms like ORCID, ResearchGate, and Google Scholar. His expertise spans advanced mathematical fields including stochastic processes, quantum probability, and operator algebras. Key research areas include the analysis of Radon measures, quasi-free states, and commutation relations in multicomponent systems. He has contributed extensively to the study of determinantal point processes, particle-hole transformations, and Fock space representations. Professor Lytvynov's publications reflect a strong emphasis on theoretical frameworks, with notable work on Segal-Bargmann transforms, Stirling operators, and Meixner-class orthogonal polynomials. His research often bridges pure mathematics and quantum physics, addressing topics like anyon statistics and non-Gaussian white noise calculus. He is accessible via email at e.lytvynov@swansea.ac.uk and can be reached at the Computational Foundry, Bay Campus. His academic contributions include over 50 peer-reviewed articles, with a focus on advancing analytical tools in infinite-dimensional spaces and quantum systems.

Hosam M. MahmoudView profile

Professor

• Probabilistic analysis of algorithms
• Random discrete structures
• Analytic probability
• +2 more

Hosam M. Mahmoud is a Professor of Statistics at the Department of Statistics, part of the Columbian College of Arts & Sciences at George Washington University. His expertise spans probabilistic analysis of algorithms, random discrete structures, and analytic probability. He is located at Rome Hall, 801 22nd St. NW, 7th Floor, Washington, DC 20052. His contact information includes an office phone at (202) 994-6667. Dr. Mahmoud's research focuses on the intersection of statistics and algorithmic analysis, with contributions to understanding random structures and their applications. His work bridges theoretical computer science and mathematical statistics.

Reza ModarresView profile

Professor

• Statistical Computing
• Multivariate Analysis
• Environmental Statistics
• +1 more

Reza Modarres is a Professor of Statistics at The George Washington University, where he has served since 1991. He held the position of Chair of the Department of Statistics from 2007 to 2013. His expertise spans Statistical Computing, Multivariate Analysis, Environmental Statistics, and Nonparametric Statistics. He received his Ph.D. in Statistics from The American University (1990), following earlier degrees in Computer Science (M.S., 1982) and a combined B.S. in Computer Science and Mathematics (1981). His research focuses on interpoint distances in high-dimensional spaces, nonparametric methods, and applications in environmental and ecological statistics. Notable contributions include work on hotspot detection, multivariate hypothesis testing, and classification algorithms. Modarres has held sabbaticals at the Pennsylvania State University and the U.S. Environmental Protection Agency. His publications emphasize methodological advancements in handling complex data structures, with recent work addressing high-dimensional statistical challenges in classification and outlier detection.

Andrew Sageman-FurnasView profile

Assistant Professor

• Global surface theory
• Isometric deformations of surfaces
• Discrete differential geometry
• +3 more

Andrew Sageman-Furnas is an Assistant Professor in the Department of Mathematics at North Carolina State University, part of the College of Sciences. His research focuses on global surface theory, discrete differential geometry, and computational fabrication with applications to polymer networks and textile mechanics. Education: PhD in Mathematical Sciences from the University of Göttingen (2017) His research spans isometric deformations of surfaces, integrable systems, and topology-driven mechanics. Notable contributions include studies on skew parallelogram nets, Bonnet pairs, and elastic gridshell form-finding. His work bridges pure mathematics with practical applications in materials science and engineering. Key publication themes include discrete geometry, topological effects in spring networks, and computational methods for fabricating complex structures. He collaborates with the Topology, Geometry and Mathematical Physics research group at NC State. No scientific awards are explicitly listed, though his active research profile suggests ongoing recognition opportunities. He currently advises no listed students but may supervise through his research groups.

Daniel KráľView profile

Professor

• Combinatorics
• Graph Theory
• Extremal Combinatorics
• +6 more

Professor Daniel Kráľ is the Alexander von Humboldt Professor for Discrete Mathematics at Leipzig University since April 2025, affiliated with the Max Planck Institute for Mathematics in the Sciences. Previously, he held the Donald Ervin Knuth Professorship at Masaryk University (2018–2025) and was a professor at the University of Warwick (2012–2020). He also serves as an honorary professor at Warwick and has held visiting roles at UC Berkeley (2025) and Georgia Tech (2005–2006). His research focuses on combinatorics, graph theory, and their intersections with computer science, particularly in extremal combinatorics, graph limits, and algorithmic graph theory. Education: Ph.D. in Computer Science (2004), Master's (2001) from Charles University, Prague. Early career included postdoc roles at TU Berlin and Charles University's Institute for Theoretical Computer Science. Research Interests: Theory of combinatorial limits, extremal combinatorics, structural and algorithmic graph theory, analytic methods in discrete mathematics. Key contributions include resolving Steinberg's Conjecture and Lovász-Plummer Conjecture, development of graph limit theory, and applications to algorithm design. Grants & Awards: Recipient of ERC Starting (CCOSA) and Consolidator (LADIST) grants, SIAM Fellowship (2024), AMS Fellow (2020), Philip Leverhulme Prize (2014), European Prize in Combinatorics (2011). Over 150 journal articles, with impactful work in Advances in Mathematics , Journal of the EMS , and others. Service: Editor-in-Chief of SIAM Journal on Discrete Mathematics , co-editor of Journal of Combinatorial Theory , co-founder of Advances in Combinatorics . Organized major conferences and workshops, including the 2025 Oberwolfach workshop on Graph Theory. Labs/Teams: Leading research groups in discrete mathematics at Leipzig and previously in Brno/Warwick. Collaborates with postdocs and students on projects spanning graph limits, integer programming, and combinatorial optimization.

Anvarbek AtayevView profile

Research Fellow

• Dislocation dynamics
• Crystalline defects
• Elasticity theory
• +4 more

Anvarbek Atayev is a former PhD student and Research Fellow in Mathematics and Statistics at the University of Warwick's MASDOC Doctoral Training Centre. He specialized in dislocation dynamics and grain boundary energies under discrete dislocation models. His research bridges mathematical physics, material science, and industrial applications. PhD: Discrete Dislocations and Grain Boundaries (2019-2022) MSc: MASDOC (2018-2019) MMath: University of Bath (2014-2018) His research interests include crystalline defect analysis, elasticity theory, and optimization for aerospace engineering. He contributed to industry projects with SmallSpark Space Systems, DSTL, and Peratech, focusing on algorithmic optimization and sensor evasion strategies. He presented work at conferences including the European Study Group with Industry and participated in workshops on anisotropic materials and electromagnetic challenges. Previously served as Vice-President of the Warwick SIAM-IMA Chapter.

Dario SpanòView profile

Professor

• Combinatorial Stochastic Processes
• Mathematical Population Genetics
• Bayesian Nonparametric Statistics
• +3 more

Professor Dario Spanò is a faculty member in the Department of Statistics at the University of Warwick, serving as Deputy Head (Teaching and Learning). He holds a PhD in Mathematical Statistics (University of Pavia, 2003) and a Laurea in Economics (University of Pavia, 1998). His research focuses on combinatorial stochastic processes, Bayesian nonparametric statistics, and mathematical population genetics, with applications to genetics and evolutionary dynamics. His work includes contributions to Wright-Fisher diffusions, coalescent theory, and exact simulation methods. He has supervised numerous PhD students and co-organizes international conferences in statistics and probability. Research Interests: Stochastic processes and their applications in population genetics Bayesian nonparametric methods and their theoretical foundations Exact simulation of diffusion processes Coalescent theory and genealogical processes Recent Work Trends: Recent publications emphasize theoretical developments in diffusion models (e.g., Wright-Fisher processes), duality methods, and computational Bayesian inference for genetic data. Key themes include excursion theory, selection dynamics in random environments, and algorithmic advancements for simulating complex stochastic systems. Awards & Recognition: No scientific awards explicitly listed, though his research has been widely cited in the field. Teaching & Supervision: Current courses include ST343 and ST419 (data science topics). He has supervised over a dozen PhD students, focusing on interdisciplinary projects in statistics and mathematical genetics. His students have pursued roles in academia and industry. Labs/Teams: Active in the CRiSM research centre at Warwick, contributing to collaborative projects in statistical genetics and computational methods.