جست‌وجوی استاد و پژوهشگر

Armine Bagyanمشاهده پروفایل

عضو هیئت علمی

• Limit theorems
• Probability inequalities for random positive definite matrices
• Dimension reduction
• +۴ مورد دیگر

Armine Bagyan is an Associate Teaching Professor of Statistics at Pennsylvania State University's Department of Statistics. She holds a Ph.D. in Statistics from Penn State (2015) and an M.S. in Mathematics from Moscow State University. Her research focuses on limit theorems, probability inequalities for random positive definite matrices, and dimension reduction. She serves as the Department Coordinator for the Graduate Minor in Statistics and is involved in undergraduate advising and university committees. Education: Ph.D. in Statistics, Penn State University, 2015 M.S. in Mathematics, Moscow State University Her work bridges theoretical probability and high-dimensional statistical analysis, with applications in matrix distributions and stochastic processes. Recent publications explore asymptotic expansions in Bingham distributions and modeling disease spread via continuous-time Markov chains. Dr. Bagyan advises Statistics majors and Schreyer Honors College students, and teaches courses including Probability Theory, Mathematical Statistics, and Applied Regression Analysis.

Charles Bertucciمشاهده پروفایل

پژوهشگر

• Analysis PDEs
• Mean Field Games
• Game theory
• +۴ مورد دیگر

Charles Bertucci is a CNRS researcher in Mathematics at the Applied Mathematics department of École polytechnique in Palaiseau, France. He also serves as a part-time teacher at École polytechnique since 2020. Bertucci defended his thesis on December 11, 2018, and his Habilitation à Diriger les Recherches (HDR) in June 2022, granting him accreditation to supervise research. His educational background includes being a former student of École Polytechnique (class of 2012) and Paris-Sorbonne University. His doctoral studies were conducted at Paris-Dauphine University under the supervision of Pierre-Louis Lions. Bertucci's research focuses primarily on mean-field game theory , optimization , and the analysis of partial differential equations . He is particularly interested in identifying stability principles for equations posed in infinite dimensions. His work spans theoretical mathematics with applications in economics, finance, and real-world phenomena such as oil markets, cryptocurrency markets, and telecommunications. His interdisciplinary approach bridges pure mathematics with practical applications in various economic and technological domains. Analysis of his recent publications reveals a strong focus on mean field games theory, with extensions to applications in finance (particularly cryptocurrency markets), optimal transport theory, and connections to PDEs. His work often involves collaborations with leading mathematicians including Pierre-Louis Lions, Jean-Michel Lasry, and others. The research demonstrates both theoretical depth in mathematical analysis and practical relevance to economic modeling. His notable scientific achievements include: Recipient of the prestigious Peccot Course for 2022-2023 at Collège de France Bertucci has been actively involved in academic service, including organizing the workshop "Mean Field Games and Applications" in 2022 with Yves Achdou, Jean-Michel Lasry and Pierre-Louis Lions. His teaching activities include delivering the Peccot Course on "Mean-field games and stochastic control in Wasserstein space" in 2023 at Collège de France, consisting of four lectures between March 31 and April 21, 2023. His research is conducted within the vibrant mathematical community at École polytechnique and through collaborations with researchers at CNRS and other institutions, focusing on advancing the theoretical foundations of mean field games while exploring novel applications across various domains.

Karoński Michałمشاهده پروفایل

استاد

• Random discrete structures
• Probabilistic combinatorics
• Graph theory
• +۱ مورد دیگر

Michał Karoński is a Professor of Mathematics at the Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Poznań, Poland, and serves as head of the Department of Discrete Mathematics. He has held visiting professorships at Emory University, The Johns Hopkins University, Purdue University, and Southern Methodist University since 1975, with ongoing engagements at Emory University since 1992. Research Focus: Discrete mathematics, random discrete structures, graph theory, and theoretical computer science. Leadership Roles: Editor-in-Chief of Random Structures & Algorithms (since 1990), Chairman of the Council of National Science Centre (2010–2016), and organizer of 17 bi-annual conferences on random structures. His research group in random structures gained international recognition in the 1970s. He has authored 60 publications, delivered over 30 plenary lectures, and collaborated globally at institutions like Microsoft Research, Bellcore, and BRICS. Scientific Awards: 2016 Medal 'Homini Vere Academico' (AMU Rector) 2013 Polonia Restituta Officer Cross (President of Poland) 1990 Minister of Science and Higher Education Prize His work spans probabilistic combinatorics, algorithm theory, and graph irregularity, with influential publications on stochastic Kronecker graphs, random intersection graphs, and distributed complexity in matchings.

Mark A Iwenمشاهده پروفایل

دانشیار

• Computational Harmonic Analysis
• Mathematical Data Science
• Signal Processing
• +۴ مورد دیگر

Mark A Iwen is an Associate Professor at Michigan State University, holding dual appointments in the Department of Mathematics and the Department of Computational Mathematics, Science and Engineering (CMSE) . His research focuses on computational harmonic analysis, mathematical data science, signal processing, and algorithms for analyzing high-dimensional datasets. He has contributed to advancements in sparse Fourier transforms, compressive sensing, and sublinear-time algorithms for large-scale data. Key research themes include: Efficient algorithms for high-dimensional PDEs and spectral methods Phase retrieval and inverse problems in imaging Optimization of tensor decompositions and dimensionality reduction techniques Development of sparse approximation methods with theoretical guarantees His recent work emphasizes applications in: Sublinear-time algorithms for function approximation Terminal embeddings for manifold data Fast JL embeddings with bi-Lipschitz properties Tensor completion and low-rank approximations Notable contributions include: Development of Sparse Harmonic Transforms for functions of many variables Advancements in distributed SVD algorithms for large networks Empirical and theoretical analysis of phase retrieval techniques Efficient sparse FFT implementations (e.g., DMSFT, GFFT) Iwen collaborates on open-source code projects, including sparse FFT libraries and phase retrieval tools. His work bridges mathematical theory with practical applications in engineering and computational science.

Thomas Schlumprechtمشاهده پروفایل

استاد

• Functional Analysis
• Banach Spaces
• Probability Theory
• +۳ مورد دیگر

Thomas Schlumprecht is a Professor at the Department of Mathematics, Texas A&M University (College of Arts & Sciences), holding a concurrent adjunct position at the Czech Technical University, Prague. He earned his Ph.D. (1988) and Diplom (1982) from Ludwig-Maximilians-Universität, München. His research focuses on Functional Analysis, Banach spaces, Probability Theory, Convex Geometry, and Mathematics in Finance. He has held various roles at Texas A&M since 1992, including Associate Head for Graduate Studies (2001–2005) and Professor since 1999. Schlumprecht’s work includes editorial roles for the Journal of Functional Analysis and Banach Journal of Mathematical Analysis . His teaching contributions span courses like Functional Analysis and Infinite Combinatorics. Recent research emphasizes metric embeddings, operator theory, and geometric functional analysis. Education: Ph.D. in Mathematics, Ludwig-Maximilians-Universität, München (1988) Diplom (M.Sc.), Mathematics, Ludwig-Maximilians-Universität, München (1982) Research Highlights: Advances in Banach space geometry and asymptotic properties Studies on metric embeddings and coarse rigidity Investigations into operator ideals and closed ideals in Banach algebras His recent publications explore topics such as greedy algorithms, transportation cost spaces, and stochastic embeddings, reflecting a deep engagement with both theoretical and applied aspects of functional analysis.

• Functional Analysis
• Metric Geometry
• Banach Space Geometry
• +۴ مورد دیگر

Florent Baudier is an Assistant Professor at Texas A&M University's Department of Mathematics, part of the College of Arts & Sciences. His research focuses on Functional Analysis, Metric Geometry, Banach Space Geometry, and Geometric Group Theory. He is actively involved in workshops such as the Banach and Metric Space Geometry Research Seminar and the STEaLTH Workshops. His work explores embeddings of metric spaces, Ribe Program, Kalton Program, and the geometry of graphs and Banach spaces. Key research interests include the study of metric embeddings, stability of metric spaces, and the interplay between nonlinear geometry and Banach space theory. He has organized conferences and participated in programs such as the Workshop in Analysis and Probability at Texas A&M. His teaching spans courses like Real Variables, Foundations of Mathematics, and Differential Equations. Recent research trends in his articles emphasize metric distortion, coarse geometry, and embeddings into Banach spaces, with contributions to understanding expander graphs, Wasserstein metrics, and operator algebras. His work bridges abstract mathematical structures with applications in theoretical computer science and geometric analysis.

• Mobile Health (mHealth)
• Chronic Disease Management
• Gamification in Healthcare
• +۳ مورد دیگر

Dr. Hoang D. Nguyen is an Assistant Professor at the School of Computing Science, University of Glasgow. His research focuses on mobile health (mHealth), chronic disease management, and design science research. He has contributed to developing nurse-led self-management programs for diabetes and heart failure patients, leveraging gamification and AI technologies. His work emphasizes evidence-based interventions and patient-centered care, with a strong emphasis on digital health innovation. Key research areas include mHealth intervention design, AI-driven conversational agents, and privacy-preserving visual content tagging. Nguyen has collaborated on studies evaluating smartphone-based programs for heart disease prevention and diabetes care. His methodologies often involve randomized controlled trials and in-situ simulations to assess complex design artifacts. Recent publications highlight innovations in gamified mobile health for older adults' mental well-being, blockchain applications in healthcare ecosystems, and social behavior analysis through deep learning. Nguyen’s interdisciplinary approach bridges computer science, healthcare, and design science to address global health challenges.

• Combinatorics
• Combinatorial Design
• Latin Squares
• +۵ مورد دیگر

Ian Wanless is a Research Professor at the School of Mathematics, Monash University. He specializes in combinatorics, with a focus on Latin squares, graph theory, and matrix permanents. His work bridges theoretical mathematics and applications in information technology, such as coding and experimental design. Wanless leads collaborative projects funded by the Australian Research Council, including studies on combinatorial structures and hypergraph matchings. He has authored over 120 peer-reviewed articles, with recent work addressing quantum states, Latin square properties, and quasigroup isomorphisms. Key Awards: Australian Mathematical Society 2009 Medal Collaborations: Global partnerships with institutions in the US, Europe, and Asia His research emphasizes universal solutions to combinatorial puzzles, such as Sudoku and the four-color theorem, while prioritizing theoretical rigor over direct applications.

Wenqing Huمشاهده پروفایل

دانشیار

• Probability
• Data Sciences/Machine Learning/Optimization
• Operations Research
• +۲ مورد دیگر

Roles & Affiliations: Wenqing Hu is an Associate Professor of Mathematics at the Department of Mathematics and Statistics, Missouri University of Science and Technology (formerly University of Missouri, Rolla). He holds memberships in professional societies including The Bachelier Finance Society, INFORMS, SIAM, and the Society of Actuaries. Education: Ph.D. in Mathematics, University of Maryland at College Park (2013) B.S. in Mathematics, Peking University (2008) Research Interests: His work spans Probability (stochastic analysis, multiscale problems), Machine Learning (optimization algorithms, neural networks), Operations Research (smart grid systems), Math Biology (Ao's potential function), and Cryptology (zero-knowledge proofs in blockchain). Recent breakthroughs include contributions to zero-knowledge virtual machines and high-dimensional data analysis . Publications Overview: His 15 most recent works (2025-2012) span topics like cryptology (e.g., zkEVM), stochastic differential equations, and reinforcement learning applications in manufacturing. Key themes include stochastic processes, nonlinear optimization, and interdisciplinary applications in energy systems and biology. Awards & Grants: Miner Alumni Teaching Award (2018) Simons Foundation Collaboration Grant (2020-2025) NSF-funded travel support for the 2018 ICM Labs & Collaborations: Active in cross-disciplinary projects such as subspace indexing on Grassmann manifolds and nonlinear optimization in ML .

Siegfried Beckusمشاهده پروفایل

مدرس ارشد

• Spectral Theory
• Dynamical Systems
• Operator Algebras
• +۶ مورد دیگر

Siegfried Beckus is a Senior Lecturer and Researcher at the Institute of Mathematics , University of Potsdam, Germany, since 2020. His work focuses on spectral theory of Schrödinger operators on graphs with aperiodic ordered potentials, dynamical systems , and operator algebras . He has also contributed to the study of Delone sets , graph limits , and aperiodic tilings . Education : PhD in Mathematics (2016) and Diploma (2012) from Friedrich Schiller University Jena, Germany. Research Interests : Spectral theory of quantum systems, aperiodic order, groupoids, C*-algebras, and applications to quasicrystals. His recent publications address operator families defined by dynamical systems , Sturmian Hamiltonians , and symbolic substitution systems on non-abelian groups. These works establish spectral continuity , Lipschitz/Hölder estimates , and periodic approximation techniques . Scientific Awards include Postdoctoral Fellowships at Technion (Haifa) and Research in Pairs scholarships at Oberwolfach. He has supervised several theses on topics like non-Euclidean estimates , Delone dynamical systems , and primitive substitutions .

Andrei Bulatovمشاهده پروفایل

استاد

• Constraint problems
• Computational complexity
• Combinatorics
• +۳ مورد دیگر

Andrei Bulatov is a Professor of Computing Science at Simon Fraser University (SFU), affiliated with the School of Computing Science within the Faculty of Applied Sciences. His research focuses on computational complexity, constraint satisfaction problems (CSP), combinatorics, and universal algebra. Bulatov earned his Ph.D. and M.Sc. in Mathematics from Ural State University, Russia, in 1995 and 1991, respectively. His work bridges theoretical computer science and algebra, with notable contributions to the complexity classification of CSPs. He has received a Best Paper Award at FOCS 2002 for his dichotomy theorem on three-element set constraints. Bulatov’s research also explores counting CSPs, algorithms for satisfiability, and applications of algebraic methods in discrete mathematics. He is part of the Algorithms & Theory Group and the Computational Logic Laboratory at SFU. Bulatov’s publications span journals like Journal of Computer and System Sciences, Theoretical Computer Science, and SIAM Journal on Computing, addressing topics from graph theory to randomized algorithms. His academic service includes roles in professional organizations and editorial work. Bulatov’s teaching includes courses such as Discrete Mathematics (MACM 101) and Directed Reading (CMPT 894).

Bastien Malleinمشاهده پروفایل

استاد

• Probability Theory
• Stochastic Processes
• Branching Processes
• +۳ مورد دیگر

Bastien Mallein is a Professor of Mathematics at the University of Toulouse III Paul Sabatier, where he is affiliated with the Institut de Mathématique de Toulouse (IMT). His research focuses on probability theory, particularly branching processes, random walks, and their applications in statistical mechanics and mathematical physics. Education: PhD in Mathematics (2012–2015), Université Pierre et Marie Curie, supervised by Zhan Shi Agrégé-préparateur (2013–2016), École Normale Supérieure Postdoctoral Researcher (2016–2017), Universität Zürich under Jean Bertoin Research Interests: Mallein studies branching processes, including branching random walks, branching Brownian motion, and Lévy processes. His work explores extreme value theory, phase transitions, and the behavior of stochastic systems over time. He has contributed to understanding critical phenomena in random trees, percolation models, and population dynamics. Recent Publications: His recent work addresses reinforced Galton-Watson processes, extremal point processes, and applications to evolutionary models. Key topics include phase transitions, large deviations, and stochastic stability. Students: He advises PhD students such as Simon Delalande (2024–) and Lianghui Luo (2023–), focusing on branching processes and extreme value analysis. Notable co-advised students include Elie Cerf (2020–2024) and Mohamed Ali Belloum (2018–2021). Labs/Teams: Active member of the IMT Probability group. Collaborates internationally on projects involving stochastic processes and mathematical physics.

Anthony Danalisمشاهده پروفایل

عضو هیئت علمی

• High-Performance Computing (HPC)
• Performance Analysis and Optimization
• System Benchmarking
• +۴ مورد دیگر

Anthony Danalis is a Research Assistant Professor at the University of Tennessee's Innovative Computing Laboratory (ICL), affiliated with the Department of Electrical Engineering and Computer Science. His research focuses on high-performance computing (HPC), including performance analysis, system benchmarking, compilers, MPI, and accelerators. He holds a Ph.D. and two M.S. degrees in Computer Science from the University of Delaware and the University of Crete, along with a B.S. in Physics from the University of Crete. Education: Ph.D. in Computer Science, University of Delaware M.S. in Computer Science, University of Delaware M.S. in Computer Science, University of Crete B.S. in Physics, University of Crete Research Interests: High-Performance Computing (HPC) Performance Analysis and Optimization System Benchmarking Compilers and Runtime Systems Parallel Programming Models (e.g., MPI) Accelerator Technologies Publications Highlight Trends in: Advancements in the PAPI library for exascale computing Dataflow-based execution for scientific applications Hardware performance counter analysis Compiler-driven optimizations Scientific Awards: Best Research Poster Finalist at SC 2017 Advising and Grants: No formal advisees listed Contributions to ICL's leadership and collaborative projects Labs and Teams: Innovative Computing Laboratory (ICL) Participation in projects like DAGuE, DPLASMA, and SHOC

• Quantum chaos
• Quantum information theory
• Mathematical physics
• +۶ مورد دیگر

Marek Kuś is a Full Professor at the Center for Theoretical Physics, Polish Academy of Sciences (PAS) in Warsaw, where he has held this position since 1995. He previously served as Full Professor at Cardinal Stefan Wyszyński University (2001-2012) and Director of the Center for Theoretical Physics, PAS (2003-2006). His international collaborations include visiting professorships in Germany, France, and the USA. Education: M.Sc. in Physics, Warsaw University (1979) Ph.D. in Physics, Warsaw University (1983) D.Sc. (Habilitation), Warsaw University (1988) Professor title conferred in 1995 His research spans quantum chaos, quantum information theory, and mathematical physics, with specialized interests in nonlinear phenomena, geometric methods, and quantum entanglement. Recent publications (2011-2015) focus on quantum correlations, entanglement detection frameworks, and symplectic geometry applications to quantum systems, reflecting sustained work in foundational quantum theory and complex systems. Scientific Awards and Leadership: Humboldt Fellowship (1987) President, Polish Society for Advancement of Arts and Sciences (2003-2005) Chairman, Scientific Council of National Center for Quantum Information (since 2008) Member, ERC Advanced Grants evaluation panel (2014) Editorial board member for International Journal of Quantum Information

• Machine Learning
• Econometrics
• Financial Econometrics
• +۷ مورد دیگر

Anastasija Tetereva is an Assistant Professor in the Department of Econometrics at the Erasmus School of Economics, Erasmus University Rotterdam. Her research lies at the intersection of machine learning and econometrics, with applications in financial markets, real estate pricing, and risk modeling. Her research interests include Machine Learning , Econometrics , Volatility Forecasting , Hedonic Pricing , Financial Sentiment Analysis , and Granger Causality . She applies advanced computational methods to economic and financial data to improve forecasting and decision-making. The recent articles reflect a strong trend in combining machine learning techniques—particularly random forests and hybrid models—with traditional econometric frameworks to analyze volatility, real estate valuations, and financial news causality. Her work demonstrates a consistent focus on improving predictive accuracy in financial and housing markets through data-driven modeling. A Forest Full of Risk Forecasts for Managing Volatility (2022) How much is the view from the window worth? Machine learning-driven hedonic pricing model of the real estate market (2022) Forecasting realized correlations: a MIDAS approach (2019) Sentiment spillover effects for US and European companies (2019) Application of Multivariate Hawkes Graphs to Uncover Granger Causality of Financial News (2018) Anastasija Tetereva has actively contributed to the academic community, including co-organizing the event Financial Econometrics meets Machine Learning (FinEML) in 2023, indicating strong engagement in interdisciplinary research networks. While no direct mention of student advising or grant funding is made in the text, her publication record and collaborative work suggest involvement in research teams and potential supervision of junior researchers. She is affiliated with the research network in financial econometrics and machine learning, contributing to a growing interdisciplinary community that bridges computer science and economic modeling. Her work is disseminated through working papers, peer-reviewed journals, and conference presentations, reflecting a robust and current research agenda.