جست‌وجوی استاد و پژوهشگر

Elmar Teuflمشاهده پروفایل

مدرس ارشد

• Random Walks on Graphs
• Combinatorics
• Probability Theory
• +۳ مورد دیگر

Elmar Teufl is a Senior Lecturer in the Department of Mathematics at Eberhard Karls Universität Tübingen. He holds a Doctorate (2002) and a Habilitation (2015) from Graz University of Technology and Tübingen University, respectively. His research focuses on random walks on graphs and groups, combinatorial problems on self-similar structures, asymptotic methods, and fractal geometry. His work bridges probability theory, combinatorics, and graph theory with applications to fractal networks and recursive systems. Teufl has held academic positions across Europe, including visiting professorships at the University of Stuttgart (2012–2013) and a Marie Curie Fellowship at Bielefeld University (2005–2006). His research has been supported by the Austrian Science Fund (FWF) and the EU. Key achievements include contributions to spanning tree enumeration on Sierpinski graphs and resistance scaling in self-similar lattices. His publications span topics like asymptotic enumeration, determinant identities for Laplacian matrices, and structural properties of nilpotent groups. He received the Austrian Mathematical Society's Studienpreis (2003) for his thesis on self-similar graphs and fractals. Teaching responsibilities include advanced courses in combinatorics and probability, with a full teaching record documented in alma.

• Mathematical Physics
• Analysis
• Probability Theory
• +۴ مورد دیگر

Prof. Dr. Peter Müller is a Professor at the Mathematical Institute of Ludwig Maximilian University of Munich (LMU), where he also serves as Dean of the Faculty of Mathematics, Informatics and Statistics. His research group focuses on Analysis, Mathematical Physics, and Numerics. Office: Room 439, Block B, Theresienstr. 39, 80333 Munich. Education: Habilitation in Mathematics, University of Göttingen (2006) Habilitation in Physics, University of Göttingen (2002) Ph.D. in Physics, University of Erlangen-Nürnberg (1996) Diploma in Physics, University of Erlangen-Nürnberg (1991) Research Interests: Müller's work spans mathematical physics, analysis, and probability theory, with emphasis on: Random Schrödinger operators and spectral theory Delocalization phenomena in disordered systems Quasiperiodic structures and ergodic properties Entanglement entropy in quantum systems His research bridges rigorous mathematical analysis with applications in quantum mechanics and statistical physics. Publication Trends: Recent articles (2013–2025) predominantly explore spectral theory in disordered quantum systems. Key themes include localization/delocalization transitions, asymptotic analysis of entanglement entropy, and spectral properties of random operators. Methodologically, his work combines functional analysis, stochastic processes, and operator theory to address fundamental questions in mathematical physics. Student Advising: Extensive mentorship of graduate students: 8 PhD students (e.g., Jakob Stern, Ruth Schulte) 17 Master's students (e.g., Leonard Wetzel, Julian Widl) Research Team: Leads the working group "Analysis, Mathematical Physics and Numerical Analysis" with postdoctoral researchers (e.g., Constanza Rojas-Molina) and PhD candidates. Regularly organizes international conferences on mathematical physics and disordered systems.

Gernot Akemannمشاهده پروفایل

استاد

• Random Matrix Theory
• Quantum Chromodynamics (QCD)
• Statistical Mechanics
• +۳ مورد دیگر

Gernot Akemann is a Professor at the Faculty of Physics, University of Bielefeld, with a focus on Random Matrix Theory and its applications in high energy physics and statistical mechanics . His work spans topics such as QCD Dirac spectra, effective field theory, orthogonal polynomials, asymptotic analysis, and universality. He has held leadership roles in projects like SFB 1283 and IGK 2235, emphasizing singular and random systems. 2025 : Subproject manager in SFB 1283 2024 : Leverhulme Trust Visiting Professorship at University of Bristol 2019 : Visiting Professor at KTH Stockholm His research includes random matrix theory for applications in quantum chromodynamics, statistical mechanics, and mathematical physics. Recent articles explore complex eigenvalue statistics, Ginibre ensembles, and their connections to Coulomb gases and territorial behavior in ecology. He has contributed to understanding universality in spectral statistics and non-Hermitian systems. Notable scientific awards include the Leverhulme Trust Visiting Professorship , Knut and Alice Wallenberg Foundation support, and DFG Research Grants . His work has been funded through projects like SFB 1283 and RTG 2235.

Masudul Haqueمشاهده پروفایل

استاد

• Theoretical Physics
• Quantum Mechanics
• Many-Body Systems
• +۷ مورد دیگر

Dr. Masudul Haque is a Professor at the Institut für Theoretische Physik (Department of Theoretical Physics) at Technische Universität Dresden. His research focuses on quantum many-body systems, non-equilibrium dynamics, and the interplay between quantum mechanics and statistical mechanics. He investigates topics such as eigenstate thermalization hypothesis, quantum chaos, integrability, and topological phases. His work spans theoretical frameworks including random matrix theory, entanglement entropy, and lattice models like the Bose-Hubbard and Heisenberg chains. Key research areas include: Quantum dynamics in open systems and thermalization phenomena Spectral properties of non-Hermitian Hamiltonians Entanglement structures in many-body systems Phase transitions and critical behavior in quantum spin chains Statistical mechanics of classical and quantum stochastic processes His recent publications (2023-2025) explore cutting-edge topics such as anti-thermalization effects, coalescence of eigenstates in non-Hermitian systems, and quantum noise-induced symmetry breaking. His work often bridges abstract theoretical concepts with potential applications in quantum technologies and condensed matter physics. No scientific awards or grants are explicitly mentioned in the provided text. His advising record remains unspecified based on current data.

Richard A. Davisمشاهده پروفایل

استاد

• Applied Probability
• Time Series Analysis
• Stochastic Processes
• +۴ مورد دیگر

Richard A. Davis is a Professor of Statistics at Columbia University and a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study (TUM-IAS). He holds the Howard Levene Professorship in Statistics. His research focuses on applied probability, time series analysis, stochastic processes, and extreme value theory. Davis has contributed to nonlinear time series models, spatial modeling, and financial econometrics. He has held academic positions at Colorado State University and MIT, and has been recognized with awards including the Koopmans Prize, IBM Faculty Award, and fellowships from the Institute of Mathematical Statistics and American Statistical Association. His education includes a B.A. and Ph.D. in Mathematics from the University of California, San Diego. He co-authored influential textbooks like Time Series: Theory and Methods and has advised numerous papers on topics ranging from count time series to spatial extremes. Current research explores machine learning applications in time series and environmental risk modeling through collaborations like the STARMAP program.

Peter Sollichمشاهده پروفایل

استاد

• Non-equilibrium statistical physics
• Soft matter rheology
• Active matter
• +۷ مورد دیگر

Prof. Dr. Peter Sollich is a Professor of Theoretical Physics at Georg-August-Universität Göttingen, affiliated with the Institute for Theoretical Physics. His research spans non-equilibrium statistical physics with applications to soft matter, active systems, and complex networks. He maintains a small part-time appointment at King's College London. His primary research interests focus on non-equilibrium statistical physics , particularly soft and active matter rheology, jamming transitions, glassy dynamics, dynamical phase transitions, and inference from dynamical data. His work bridges theoretical physics with applications in materials science and network theory, emphasizing both fundamental mechanisms and quantitative modeling approaches. Analysis of his recent publications reveals strong thematic consistency in studying glassy dynamics and active matter systems , with increasing integration of machine learning techniques for network analysis. Key methodological threads include coarse-grained modeling, spectral analysis of complex systems, and non-equilibrium thermodynamics frameworks. His 2023-2025 work shows growing emphasis on nonreciprocal interactions in active mixtures and physics-inspired machine learning applications. Prof. Sollich actively supervises Bachelor's, Master's, and PhD students, welcoming thesis inquiries in theoretical physics. His group develops analytical and computational approaches to complex dynamical systems, with recent grants likely supporting work on network dynamics and active matter modeling (specific grants not detailed in source text). His research group operates within the Institute for Theoretical Physics at Göttingen, focusing on computational and analytical modeling of disordered systems. Current projects involve elastoplastic modeling of amorphous solids, spectral analysis of heterogeneous networks, and theoretical frameworks for active matter phase separation.

• Probability Theory
• Branching Processes
• Products of Random Matrices
• +۷ مورد دیگر

Prof. Dr. Sebastian Mentemeier is a permanent Professor (W2) in the Department of Mathematics 2 at the Institute for Mathematics, Mathematics Education and Computer Science Education, University of Hildesheim, Germany, a position he has held since October 2019. He also holds significant administrative roles as Vice Dean and Dean of Studies in Faculty 4 (Mathematics, Natural Sciences, Economics & Computer Science), and is a member of the Institute's Board and the Central Commission for Studies and Teaching. His research is centered on advanced probability theory, with a focus on branching processes, products of random matrices, and extreme value theory for time series. His research interests include: Non-Gaussian limit theorems Branching processes, particularly Multitype Branching Random Walks Products of random matrices Extreme value theory for time series Heavy-tailed random variables Conditional limit theorems His recent publications, spanning from 2012 to 2022, demonstrate a consistent and high-impact research trajectory in theoretical probability. The articles reveal a strong trend in analyzing the asymptotic behavior of complex stochastic systems, particularly those defined by recursive equations and random matrix products. His work frequently intersects with statistical mechanics and time series analysis, often investigating the tail behavior and limit laws of solutions to stochastic fixed-point equations, with a particular emphasis on heavy-tailed and multivariate settings. Prof. Mentemeier has been a Principal Investigator on two major DFG projects: 'Nonlinear stochastic fixed-point equations with applications in statistical mechanics' (2017-2023) and 'Products of Random Matrices, Noncommutative Branching Random Walks, and Multitype Branching Random Walks in Random Environments' (since 2021). He is an active member of the academic community, serving as a referee for journals such as Stochastic Processes and their Applications and Journal of Theoretical Probability , and has co-organized international conferences on recursive stochastic processes and branching models. He supervises PhD and Master's students, although specific names are not listed on his profile. He has led a research group within the Department of Mathematics 2 and is a key member of the Institute's academic board. His work is conducted within the broader context of the Faculty of Mathematics, Natural Sciences, Economics & Computer Science at the University of Hildesheim.

André Uschmajewمشاهده پروفایل

استاد

• Numerical Analysis
• Tensor Methods
• Low-Rank Approximation
• +۷ مورد دیگر

Prof. Dr. André Uschmajew is a full professor and holds the Chair of Mathematical Data Science at the Institute of Mathematics, Faculty of Mathematics, Natural Sciences, and Materials Engineering, University of Augsburg, Germany. He has held prominent research and academic positions at institutions including the Max Planck Institute for Mathematics in the Sciences (Leipzig), University of Bonn, and EPF Lausanne. 2022–present: Chair of Mathematical Data Science, University of Augsburg 2017–2022: Research Group Leader, Max Planck Institute MiS Leipzig 2014–2017: Bonn Junior Fellow Professorship, University of Bonn 2013: Ph.D. in Mathematics, TU Berlin His research centers on the theoretical and computational aspects of low-rank tensor and matrix approximations, with deep connections to Riemannian optimization, functional analysis, and high-dimensional scientific computing. He investigates the geometry of low-rank varieties, convergence of alternating algorithms, and applications in data science and dynamical systems. His work combines rigorous mathematical analysis with algorithmic innovation. The recent publications (2023–2025) reflect a strong focus on optimization methods for low-rank structures, dynamical low-rank approximation for PDEs like the Vlasov-Poisson equation, randomized SVD, Sinkhorn-type algorithms with overrelaxation, and Kronecker product operator approximation. Key themes include convergence analysis, algorithmic acceleration, and applications in scientific computing and signal processing. Although no specific awards are listed, his publication record in top-tier journals such as Numerische Mathematik , SIAM Journal on Optimization , and Foundations of Computational Mathematics indicates significant recognition in applied mathematics and numerical analysis. He advises students and researchers in mathematical data science and numerical analysis, though specific advisees are not named. He teaches courses such as Kernel Methods and Linear Algebra II. He has collaborated with leading researchers including Bart Vandereycken, Daniel Kressner, and Wolfgang Hackbusch. His work is supported through institutional affiliations and likely research grants, though specific grants are not listed. He is actively involved in the development of numerical methods for high-dimensional problems, particularly using tensor networks and manifold optimization. He is affiliated with research teams at the University of Augsburg and previously led a group at the Max Planck Institute MiS Leipzig, focusing on mathematical aspects of data science and tensor methods.

Alexander Weißeمشاهده پروفایل

پژوهشگر

• Condensed Matter Physics
• Mathematical Physics
• Integrable Systems
• +۴ مورد دیگر

Alexander Weiße is a tenured researcher at the Max Planck Institute for Mathematics in Bonn, Germany, where he also serves as Head of IT. Previously, he was a junior professor for computational physics at the University of Greifswald (until 2009). He holds a PhD in physics from the University of Bayreuth (2002) and completed postdoctoral research at the Max Planck Institute for the Physics of Complex Systems, University of New South Wales (Sydney), and University of Greifswald. Research Interests : His work spans condensed matter physics, mathematical physics, and integrable systems. Recent focuses include spin systems (e.g., XXZ Heisenberg chain), disorder/randomness in quantum systems, and computational methods (e.g., Chebyshev expansion, kernel polynomial method). He also contributes to high-performance computing and programming tools (C, Form, Julia). Teaching & Leadership : He has taught courses on computational physics, group theory, numerical many-particle physics, and computer algebra. Notable collaborations involve the Bergische Universität Wuppertal group on spin model correlation functions. He co-edited the textbook Computational Many-Particle Physics (Springer, 2008). IT Responsibilities : As Head of IT, he manages IT infrastructure security and strategy, with interests in cybersecurity and computational resource optimization.

Stephan Seifertمشاهده پروفایل

استاد

• Chemometrics
• Bioinformatics
• Food Profiling
• +۳ مورد دیگر

Professor Stephan Seifert leads research at the University of Hamburg's Department of Chemistry, focusing on chemometrics and bioinformatic methods for food profiling and manuscript analysis. His group develops analytical approaches using vibrational spectroscopy, machine learning, and data fusion techniques. Research spans: Chemometric method development (random forests, variable selection) Spectroscopic analysis (FTIR, Raman, NMR) Food authentication and quality control Manuscript material characterization Recent publications demonstrate increasing use of machine learning for metabolomics data interpretation and multi-technique data fusion. Research integrates analytical chemistry with computational approaches to solve problems in food science and cultural heritage. Current projects include the Cluster of Excellence 'Understanding Written Artefacts' and Palm-Leaf Manuscript Profiling Initiative. Leads the Seifert AG research group at the Institute of Food Chemistry.

Moritz Gerlachمشاهده پروفایل

پژوهشگر

• Operator Theory
• Ergodic Theory
• Markov Processes
• +۳ مورد دیگر

Dr. Moritz Gerlach is a researcher associated with the Institute of Mathematics at the University of Potsdam . His work focuses on operator theory, ergodic theory, and the asymptotic behavior of Markov processes. He collaborates on topics like kernel operators, positivity in Banach lattices, and spectral convergence in graph theory. PhD thesis: Semigroups of Kernel Operators (2014) Diploma thesis: The Asymptotic Behavior of Positive Semigroups (2010) Diploma thesis: Comparison of Time and Space Complexity (2008) Gerlach's research spans positive operator semigroups, their convergence properties, and applications to partial differential equations and stochastic processes. He has extended classical theorems by Doob, Lasota-Yorke, and Lévy, often eliminating restrictive continuity assumptions. His work on graph Laplacian convergence bridges machine learning and computational mathematics. His publications, including 10 peer-reviewed articles since 2012, emphasize abstract kernel operators, mixing properties, and lattice structures. While the website lists him as a freelancer, his university email ( gerlach@math.uni-potsdam.de ) suggests ongoing collaboration with the institute.

Robert Stelzerمشاهده پروفایل

استاد

• Financial Mathematics
• Stochastic Volatility Models
• Stochastic Processes
• +۵ مورد دیگر

Robert Stelzer is a Professor and Head of the Institute of Mathematical Finance at Ulm University. His research focuses on stochastic processes, financial mathematics, and statistical methodologies. He has supervised numerous PhD students and organized international scientific events. Key contributions include work on multivariate stochastic volatility models, Lévy processes, and time series analysis. Awards include the Förderpreis and Promotionspreis for his doctoral work. He holds editorial roles in leading journals and actively participates in academic service. Research interests span financial mathematics, stochastic volatility, and extreme value theory. His publications explore CARMA processes, supOU models, and geometric ergodicity. Teaching includes courses on financial mathematics, stochastic analysis, and econometrics. Supervised students have contributed to advancements in stochastic finance and statistical theory. Organized events include workshops on extreme value theory and financial mathematics. Editorships include Statistics and Risk Modeling, reflecting his leadership in statistical research. His work bridges theoretical probability and practical applications in finance and risk management.

• Mathematical Optimization
• Algorithmic Game Theory
• Multi-Agent Systems
• +۳ مورد دیگر

Max Klimm is an Assistant Professor for Discrete Optimization at Technische Universität Berlin, affiliated with the Department of Mathematics within Faculty II – Mathematics and Natural Sciences. He holds a PhD in Mathematics from TU Berlin (2012) and previously served as an Assistant Professor for Operations Research at Humboldt-Universität zu Berlin (2014–2016) and led the Junior Research Group for Optimization under Uncertainty at the Einstein-Center for Mathematics (2014–2016). His research focuses on algorithmic game theory, mathematical optimization of multi-agent systems in traffic, telecommunications, and economics. Key areas include network flows, congestion games, mechanism design, and infrastructure networks. He actively contributes to academic activities as an associate editor for journals like International Journal of Game Theory and Operations Research Forum , and has served on program committees for conferences such as AAAI, EC, and WINE. Recent work includes studies on evolutionary road network reconstruction, robustness of potential-based flows, and algorithmic solutions for knapsack and assignment problems. His research bridges theoretical foundations with practical applications in transportation and resource allocation.

Anton Klimovskyمشاهده پروفایل

مدرس ارشد

• Probability Theory
• Stochastic Processes
• Statistical Mechanics of Disordered Systems
• +۷ مورد دیگر

Anton Klimovsky is a Senior Lecturer at the University of Würzburg since 2022, affiliated with the Applied Stochastics department. His career includes visiting professorships at the University of Stuttgart (2022) and the University of Bonn (2014), along with lecturing at the University of Duisburg-Essen (2013-2022). Education : Habilitation (2019), Ph.D. in Mathematics (2008, TU Berlin, advisor: Anton Bovier), M.Sc. in Applied Mathematics (2002, Kharkiv National University, advisor: Mariya Shcherbina). Klimovsky’s research focuses on stochastic models of complex systems , including statistical mechanics of disordered systems , range-free spin glasses , and stochastic processes on evolving networks . His work bridges high-level heuristic ideas from statistical physics (e.g., cavity method, renormalization group) with rigorous probabilistic techniques. The 15 most recent articles highlight his expertise in disordered systems , hierarchical structures , population genetics , and network dynamics . Key trends include analysis of phase transitions in branching Brownian motion, renormalization of Lambda-Cannings processes, and Gaussian fluctuation theory in random energy models. Scientific awards include the Marie Curie Intra-European Fellowship (2010-2012) DFG Ph.D. Fellowship (2003-2005) National Academy of Sciences of Ukraine Ph.D. Fellowship (2002-2003) He has held visiting positions at Leiden University , EURANDOM , and Technische Universität Berlin , and has taught courses on Stochastic Processes , Markov Chains , and Spin Glasses . His grants include DFG funding for stochastic processes on evolving networks (2019-2024) and collaborative projects on hierarchical self-organization (2020-2026).

Roland Speicherمشاهده پروفایل

استاد

• Free Probability Theory
• Random Matrices
• Operator Algebras
• +۳ مورد دیگر

Roland Speicher is a Professor at the Department of Mathematics, Saarland University. His research focuses on Free Probability Theory , Random Matrices , and Operator Algebras , with applications in quantum physics, machine learning, and statistical mechanics. University: Saarland University Department: Mathematics Academic Rank: Professor Email: speicher@math.uni-sb.de Roland Speicher's research explores the interplay between free probability and random matrices, particularly through the lens of quantum mechanics and computational mathematics. He has contributed to understanding the effects of non-linear transformations on random matrices and their eigenvalue distributions, extending free probability tools to problems in machine learning and quantum information theory. His recent publications address: Non-linear functions on orthogonally invariant matrices Fuglede-Kadison determinants in operator-valued free probability Structured random matrices and cyclic cumulants Free probability applications in quantum gravity and black hole entropy Connections to the replica trick and quantum de Finetti theorems Key scientific recognitions include the ERC Advanced Grant (2014-2019) for non-commutative distributions. He leads a research group at Saarland University, collaborating with Dr. Johannes Hoffmann, Dr. Tobias Mai, and M.Sc. Alexander Wendel. His teaching includes advanced courses on random matrices, with lecture notes published by EMS Press.