Wojciech Samotij is an Associate Professor at the School of Mathematical Sciences, Tel Aviv University. His research focuses on extremal and probabilistic combinatorics, Ramsey theory, large deviation theory, and additive number theory. He has held positions including Junior Research Fellow at Trinity College, University of Cambridge (2010–2014), and Post-doctoral researcher at Tel Aviv University (2010–2011, 2012–2013). PhD in Mathematics (2010), University of Illinois at Urbana-Champaign, supervised by Jozsi Balogh M.Sc. in Mathematics and Computer Science (2007), University of Wrocław His recent work explores large deviation principles in random graphs, hypergraph containers, and extremal problems in probabilistic settings. Publications span journals like Annals of Probability , Duke Mathematical Journal , and Transactions of the American Mathematical Society , with key contributions to Ramsey-type theorems and entropy-based combinatorial analysis. He has supervised graduate students in topics ranging from additive combinatorics to random graph theory, and taught courses including Probabilistic Methods in Combinatorics, Graph Theory, and Discrete Mathematics. His email contact is samotij@tauex.tau.ac.il and samotij@post.tau.ac.il .
Dr. Mahya Ghandehari is an Associate Professor in the Department of Mathematical Sciences at the University of Delaware . Her work bridges Noncommutative Harmonic Analysis , Graph Limit Theory , and Data Science , with a focus on mathematical frameworks for network analysis and signal processing on graphs. PhD in Mathematics, University of Waterloo Her research addresses challenges in seriation and graph signal processing (GSP) , particularly through graphon-based models. Recent work explores spectral methods, Fourier bases for stochastic block model graphs, and wavelet characterizations of network structures. Dr. Ghandehari’s research is supported by active NSF grants (DMS-2408008, CCF-2427965) and Simons Travel Support . She supervises PhD student Caroline McCrorey and has mentored several PhD graduates now holding academic positions at institutions like Tufts University and SUNY Oswego. Scientific honors include the Fields Postdoctoral Fellowship . She organizes seminars such as the Analysis Seminar at Delaware and the Northeastern Analysis Meeting (NEAM 2025) .
Quirin Thomas Simon Vogel is a Senior Lecturer at the University of Klagenfurt , located within the Department of Statistics . Before joining Klagenfurt, he held post-doctoral positions at the Technical University of Munich and New York University Shanghai , and served as Interim Professor at Ludwig-Maximilians University of Munich . His research lies at the intersection of probability theory and statistical mechanics . Specifically, he investigates random walks , random algorithms , and loop-based models arising from physical systems. Key themes include: Loop percolation and interacting Bose gases Large deviations and critical phenomena Randomised algorithms for communication networks Mathematical models of cancer dynamics and immune response Across his 2020-2025 publications, Vogel consistently applies probabilistic techniques to high-dimensional statistical-physics models, neural-network theory, and wireless-protocol design, evidencing a broad yet cohesive research portfolio. Contact details: Email: quirin.vogel@aau.at Office: N.0.01, Main Building, North Wing West, Level 0 Phone: +43 463 2700 3156
Khanh Duy Trinh is a Professor (non-tenure-track) at Waseda University's Global Center for Science and Engineering, specializing in probability theory and its applications to random matrix theory and stochastic topology. He holds a PhD from Osaka University (2012) and has held academic positions at Tohoku University and Kyushu University. Current affiliation: Waseda University (2025-present) Past roles: Associate Professor at Waseda (2019-2025), Tohoku University, Kyushu University Research areas: Beta ensembles, Random topology, Spectral measures, Stochastic geometry His work demonstrates universal behavior in random matrix models through spectral analysis and topological persistence. Key contributions include central limit theorems for eigenvalue statistics, Poisson approximations in high-temperature regimes, and geometric interpretations of persistence diagrams. His recent papers focus on generalized beta processes and higher-dimensional complex structures. Current projects include: JSPS Grant 2024-2029: Universal approaches in random matrix theory Past JSPS Grant 2019-2023: Multi-aspects of beta ensembles Teaching activities at Waseda include: Introduction to Probability and Statistics Advanced Probability and Statistics Master's Thesis advising in Pure and Applied Mathematics
Renaud Raquépas is a Phillip Griffiths Assistant Research Professor in the Department of Mathematics at Duke University, where he has been working since 2025 under the mentorship of Professor Jonathan C. Mattingly. Prior to his position at Duke, he was a Courant Instructor in the Mathematics Department of the Courant Institute at New York University (2022-2025), hosted by Professor Lai-Sang Young, and a postdoctoral researcher at CY Cergy Paris Université (2021-2022), working with Professor Armen Shirikyan. His educational background includes a PhD in Mathematics from McGill University and Université Grenoble Alpes (2017-2020), where he was jointly supervised by Professors Vojkan Jakšić and Alain Joye. His doctoral thesis focused on "Tools and results in the study of entropy production." He also earned an MSc in Mathematics and Statistics from McGill University (2016-2017) under the supervision of Professor Vojkan Jakšić, with a thesis on "Heat full statistics and regularity of perturbations in quantum statistical mechanics." His undergraduate studies were completed at McGill University, where he also earned his Master's degree over a period of approximately five years. Raquépas's research primarily focuses on mathematical physics, with particular emphasis on time-dependent aspects of statistical mechanics and entropy production in both quantum and classical systems. His work bridges several mathematical disciplines including probability theory (particularly large deviations and stochastic differential equations), dynamical systems and ergodic theory (covering recurrence, mixing, theory of C*-algebras, and random dynamical systems), and operator theory (focusing on spectra, resolvents, perturbation theory, and one-parameter semigroups). His research addresses fundamental questions about nonequilibrium statistical mechanics, quantum information, and the mathematical foundations of thermodynamics. The most recent publications by Raquépas demonstrate a consistent focus on entropy production, large deviation principles, and the mathematical structure of statistical mechanical systems. His work spans both classical and quantum domains, with particular attention to the connections between information theory, probability, and physics. A significant portion of his research examines return times, waiting times, and their relationship to entropy estimators, while other papers explore quantum measurement processes, fermionic systems, and diffusions with various types of noise. His publications appear in prestigious journals including Communications in Mathematical Physics, Annales Henri Poincaré, and Journal of Mathematical Physics. Raquépas has presented his research at numerous international conferences and seminars, including the IEEE International Symposium on Information Theory, the International Congress of Mathematical Physics, and various departmental seminars at institutions worldwide. His work has been featured at specialized workshops on entropy, dynamical systems, and mathematical physics. As an educator, Raquépas has taught a variety of undergraduate mathematics courses at multiple institutions. At Duke University, he is scheduled to teach Probability in the Fall 2025 semester. Previously at NYU, he taught courses including Ordinary Differential Equations, Introduction to Mathematical Modeling, Linear Algebra, and Applied Complex Variables. He has also taught mathematics courses in French at CY Cergy Paris Université and Université Grenoble Alpes, demonstrating his bilingual capabilities (French is his first language, with fluency in English). Raquépas was born in the 1990s in the Province of Québec and has been involved in mathematical outreach activities, including service on the committee of the Seminars in Undergraduate Mathematics in Montréal and work on the website of the French-language mathematics magazine Accromath.
Evgeny Igorevich Prokopenko is a Senior Research Fellow at the Faculty of Computer Science, National Research University Higher School of Economics (HSE), specifically within the Institute of Artificial Intelligence and Digital Sciences and the Laboratory of Theoretical Foundations of Artificial Intelligence Models. He joined HSE in 2024 and concurrently serves as a Senior Researcher at the Sobolev Institute of Mathematics, Siberian Branch of the Russian Academy of Sciences since January 2019. His educational background includes: 2018: Candidate of Physical and Mathematical Sciences 2014: Master's degree in Mathematics from Novosibirsk National Research State University Prokopenko specializes in probability theory and random processes, with particular focus on large deviations. His research bridges theoretical mathematics with applications in artificial intelligence and complex systems. His work demonstrates a strong foundation in mathematical theory while addressing contemporary challenges in data science and stochastic modeling. His scientific contributions primarily focus on limit theorems, branching processes, and large deviation principles. His publications reveal a consistent research trajectory in probability theory with applications to various domains including polymer physics and random environments. The temporal pattern of his publications shows ongoing productivity with recent work published in top probability journals. His notable achievements include: Multiple publications in high-impact journals including Probability Theory and Its Applications, Extremes, Statistics and Probability Letters, and Problems of Information Transmission Collaborations with prominent researchers in probability theory across international institutions Prokopenko maintains active research affiliations with both HSE University in Moscow and the Sobolev Institute of Mathematics in Novosibirsk, reflecting a strong connection between Russia's leading mathematical centers. His current position at HSE's Faculty of Computer Science suggests an integration of his theoretical expertise with modern computational approaches.
