جست‌وجوی استاد و پژوهشگر

Gerold Alsmeyerمشاهده پروفایل

استاد

• Theory of stochastic processes
• Stochastic fixed-point equations
• Iterated function systems
• +۷ مورد دیگر

Prof. Dr. Gerold Alsmeyer is a faculty member at the Institute of Mathematical Stochastics, Department of Mathematics and Computer Science, University of Münster. He is an active researcher with a focus on stochastic processes, particularly stochastic fixed-point equations and iterated function systems. His work is supported by his role as an Investigator in Mathematics Münster in the project EXC 2044 - C1: Evolution and asymptotics. His primary research interests include the theory of stochastic processes, branching processes, Markov random walks, renewal theory, and the asymptotic analysis of random structures such as random trees and polytopes. He has made significant contributions to the understanding of fluctuation theory, perpetuities, and the smoothing transform. His recent publications (2017–2023) reveal a sustained focus on theoretical probability, with recurring themes in random difference equations, iterated function systems, and limit theorems for stochastic processes. The work spans pure mathematical theory and applications in mathematical biology and combinatorics, indicating a broad yet deep research profile. Prof. Alsmeyer has supervised numerous doctoral and master’s students, including Viet Hung Hoang, Christopher Eick, Philipp Godland, and Fabian Buckmann, whose dissertations cover topics in branching processes, random walks, and stochastic fixed-point equations. He has no listed scientific awards in the provided texts. He teaches courses in probability theory, mathematical statistics, branching processes, and stochastic recursion equations, demonstrating a strong commitment to academic mentoring and education.

• Low-dimensional Topology
• Geometric Group Theory
• Mapping Class Groups
• +۲ مورد دیگر

Sebastian Hensel is a Professor of Pure Mathematics at the Mathematical Institute of Ludwig Maximilian University of Munich (LMU), where he also serves as the Dean of Studies. His research focuses on the intersection of low-dimensional topology and geometric group theory, with emphasis on mapping class groups, handlebody groups, and diffeomorphism groups of surfaces. He leads the Geometry and Topology Working Group and is actively involved in teaching advanced seminars. Hensel received his PhD from the University of Bonn in 2011 under Ursula Hamenstädt. Before joining LMU, he held positions as a Dickson Instructor at the University of Chicago and as a temporary academic councilor in Bonn. His research employs geometric methods to study algebraic structures in topological spaces, particularly surfaces and 3-manifolds. Scientific Awards: Dickson Instructor Fellowship, University of Chicago Teaching & Advising: Hensel regularly teaches courses on Riemannian geometry, geometric group theory, and manifold topology. He currently advises bachelor and master's theses in geometry/topology and organizes block seminars. As Dean of Studies, he oversees academic programs at the Mathematical Institute. Affiliations: Member of the Geometry and Topology Group at LMU, with collaborations spanning multiple institutions including TUM and international partners.

• Combinatorics
• Algebraic Combinatorics
• Log-Concave Polynomials
• +۱۳ مورد دیگر

Jonathan Leake is an Assistant Professor in the Department of Combinatorics and Optimization at the University of Waterloo. His research lies at the intersection of combinatorics, optimization, and theoretical computer science, with a focus on log-concave and Lorentzian polynomials and their applications in discrete and continuous settings. Assistant Professor, University of Waterloo (2022–present) Dirichlet Postdoctoral Fellow, TU Berlin (2020–2022) Postdoctoral Fellow, Institut Mittag-Leffler, Stockholm (Spring 2020) Postdoctoral Fellow, KTH, Stockholm (Fall 2019) James H. Simons Fellow, Simons Institute, UC Berkeley (Spring 2019) His research explores the deep connections between algebraic structures and combinatorial phenomena, particularly through polynomial capacity and Lorentzian polynomials. He applies these tools to problems in optimization, sampling, and representation theory. His work often involves developing new algebraic and analytic techniques to tackle longstanding conjectures and algorithmic challenges. The recent publications highlight a consistent focus on Lorentzian polynomials, capacity bounds, and their applications in combinatorics, optimization, and theoretical computer science. Key themes include matroid theory, log-concavity, sampling algorithms, volume approximation, and connections to Lie theory and representation theory. The research spans both theoretical developments and algorithmic applications, often in collaboration with leading researchers in the field. Dirichlet Postdoctoral Fellowship, TU Berlin Postdoc Fellowship in Algebraic and Enumerative Combinatorics, Institut Mittag-Leffler James H. Simons Fellowship, Simons Institute, UC Berkeley Jonathan Leake has advised or collaborated with several researchers, though formal advisees are not listed in the provided text. His work has been supported by prestigious fellowships and collaborations with institutions such as the Simons Institute and TU Berlin. He has taught courses including CO 250: Introduction to Optimization, MATH 239: Introduction to Combinatorics, and CO 739: Lorentzian Polynomials at the University of Waterloo and TU Berlin. While specific lab or research group names are not mentioned, Leake's collaborative work with researchers like Petter Brändén, Nisheeth Vishnoi, and Leonid Gurvits suggests active participation in research teams focused on algebraic combinatorics, optimization, and theoretical computer science. His publicly shared code for sampling from HCIZ densities and verifying positivity in Lie-theoretic contexts indicates an active computational research component.

Zakhar Kabluchkoمشاهده پروفایل

استاد

• Stochastic Processes
• Convex and Integral Geometry
• Random Trees and Branching Processes
• +۵ مورد دیگر

Prof. Zakhar Kabluchko is a faculty member at the University of Münster, affiliated with the Institut für Mathematische Stochastik and the Mathematics Münster cluster of excellence. His research focuses on stochastic processes, convex and integral geometry, and probabilistic number theory. He holds a professorship and has contributed to high-impact publications in areas like random polytopes, stochastic geometry, and extreme value theory. His research interests include the study of random analytic functions, stochastic processes in high dimensions, and geometric probability. Notably, he has explored beta-star polytopes, Poisson zero cells, and the interplay between convex hulls and random walks. Kabluchko has also investigated applications of stochastic geometry in statistical mechanics and number theory. Recent work includes studies on high-dimensional limit theorems, propagation of chaos in spin systems, and the geometry of random simplices. He collaborates actively with researchers like Christoph Thäle and Vladimir Vysotsky, contributing to advancements in geometric probability and stochastic analysis.

Christoph Thäleمشاهده پروفایل

استاد

• Stochastic Geometry
• Geometric Probability
• Limit Theorems
• +۴ مورد دیگر

Professor Christoph Thäle is a faculty member in the Faculty of Mathematics at Ruhr-Universität Bochum . His research focuses on stochastic geometry, geometric probability, limit theorems for random structures, and applications of Malliavin calculus and Stein's method. He has supervised numerous PhD and master's students, including Tristan Schiller, Nils Heerten, and Kathrin Meier. His work bridges theoretical probability with geometric analysis, particularly in high-dimensional spaces. Research Interests: Stochastic Geometry, Convex Geometry, Limit Theorems, Random Structures in High Dimensions Team Members: Postdocs (Panagiotis Spanos, Ercan Sönmez), PhD students (Philipp Tuchel, Bahareh Yousefi), and collaborators like Anna Gusakova and Zakhar Kabluchko. Key contributions include studies on random polytopes, Poisson hyperplane tessellations, and geometric analysis in hyperbolic spaces. His recent publications (2023–2025) explore intersection probabilities, radial spanning trees, and large deviations in high-dimensional settings. Thäle's research has been supported by collaborations with institutions like the University of Duisburg-Essen and the University of Osnabrück.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Bo Wang represents multiple academic researchers across various institutions worldwide, with prominent affiliations at Tsinghua University, Michigan State University, University of York, and Hamad Bin Khalifa University. The collective profile shows active research contributions across computer science, engineering, and applied mathematics disciplines. These researchers hold faculty positions primarily as Professors or Associate Professors in departments including Computer Science, Electrical Engineering, and Applied Mathematics. Research interests span artificial intelligence, machine learning, biomedical engineering, wireless communications, and computational mathematics. The collective publication record demonstrates significant contributions to federated learning, medical image analysis, control systems, and biomolecular modeling. Recent work shows particular strength in developing novel AI architectures for scientific computing and healthcare applications. Publication trends reveal increasing interdisciplinary collaboration, with substantial output in top-tier journals and conferences from 2020-2025. Key research areas include deep learning for medical imaging, optimization algorithms for engineering systems, and computational methods for biological data analysis. The collective work shows strong methodological innovation combined with practical applications. No specific scientific awards were identified in the disambiguation page, though the high publication volume in reputable venues suggests recognition within respective fields. The collective research demonstrates strong connections between theoretical advances and practical implementations across multiple domains. While specific student information isn't provided in the disambiguation page, the extensive publication record suggests active supervision of graduate students. Research appears well-funded through various institutional and potentially national funding mechanisms, supporting the diverse range of projects spanning theoretical and applied domains.

• Stochastic Hybrid Systems
• Formal Verification
• Monte-Carlo Methods
• +۳ مورد دیگر

Jonas Stübbe is a PhD Student and Research Associate at the University of Münster, affiliated with the Safety-critical Systems Group led by Prof. Dr. Anne Remke. His research focuses on stochastic hybrid systems, formal verification, and Monte-Carlo methods, with notable contributions including the RealySt tool for optimizing reachability probabilities. He holds a position in Room 201a at Einsteinstr. 62, Münster, and can be contacted at jonas.stuebbe@uni-muenster.de. Teaching responsibilities include leading the 'Discrete Structures' lecture and its exercise sessions since 2023, as well as contributing to courses like 'Modeling and Analysis of Dynamic Systems' and 'Computer Networks and Their Performance'. His work bridges theoretical computer science with practical tool development, emphasizing safety-critical system analysis. Key contributions include publications in Performance Evaluation Methodologies and Tools (Springer LNCS series) and ongoing research in stochastic system modeling. Collaborations with peers like Joanna Delicaris and Stefan Schupp highlight his active participation in interdisciplinary projects.

Martin Huesmannمشاهده پروفایل

استاد

• Stochastic analysis
• Optimal transport
• Random measures
• +۱۰ مورد دیگر

Prof. Dr. Martin Huesmann is a full Professor at the Institute for Mathematical Stochastics, Department of Mathematics and Computer Science, University of Münster, and a key investigator in the Excellence Cluster Mathematics Münster. He leads an active research group focusing on stochastic analysis, optimal transport, random measures, and robust finance. Research Interests: Stochastic analysis Optimal transport (classical, martingale, causal) Random measures and point processes Skorokhod embedding and its geometric variants Matching and allocation problems Robust and model-independent finance Gradient flows and asymptotic analysis of random structures His recent publications reveal a strong trend in probabilistic approaches to optimal transport, particularly in martingale and multi-marginal settings, with deep connections to financial mathematics and geometric analysis of stochastic processes. His work often involves collaboration with leading researchers such as Mathias Beiglböck, Alex Cox, and Felix Otto. Scientific Contributions: Investigator in EXC 2044 - C1: Evolution and asymptotics, developing gradient flow descriptions for diffusion-reaction systems. Research on asymptotics of random polytopes and random trees. Development of transport distances for stationary random measures. He actively advises PhD and master’s students, including Bastian Müller, Jonas Jalowy, and Hanna Stange. He teaches advanced courses such as Optimal Transport , Stochastic Analysis , and Probability Theory , and supervises numerous master’s and bachelor’s theses. His research group includes current members Bastian Müller, Hanna Stange, and Jonas Jalowy, and former members Francesco Mattesini and Martin Brückerhoff, reflecting sustained research activity and mentorship.

Anna Gusakovaمشاهده پروفایل

عضو هیئت علمی

• Stochastic Geometry
• Probability Theory
• Random Polytopes
• +۷ مورد دیگر

Anna Gusakova is a Junior Professor at the Institute for Mathematical Stochastics, University of Münster, Germany. Her research lies at the intersection of stochastic geometry , probability theory , and high-dimensional analysis , with a focus on random polytopes, tessellations, and concentration phenomena. Education: She completed her Ph.D. under the supervision of Prof. Dr. Friedrich Götze, with a thesis titled Application of Probability Methods in Number Theory and Integral Geometry . Research Interests: Her work spans a broad range of topics including: Stochastic geometry of random polytopes and tessellations High-dimensional probability and concentration inequalities Poisson processes and their geometric applications Convex and integral geometry Number-theoretic aspects of random structures Publications Overview: Her recent publications demonstrate a deep engagement with theoretical foundations and asymptotic analysis in stochastic geometry. Notable contributions include studies on the β-Delaunay tessellation , spherical convex hulls , and concentration inequalities for Poisson functionals . These works often involve advanced tools from integral geometry, functional analysis, and probabilistic limit theory. Teaching and Mentorship: She teaches a variety of courses including master's seminars on stochastic geometry, probability theory, and high-dimensional probability. Her teaching emphasizes both theoretical depth and practical applications in modern probability and geometry. Collaborations and Grants: While specific grant details are not provided, her extensive collaboration network includes researchers like Christoph Thäle, Zakhar Kabluchko, and Florian Besau, indicating active participation in international research projects. Laboratory and Team: She is associated with the working group in Mathematical Stochastics at the University of Münster, contributing to a vibrant research environment in probability and geometry.

Casimir Katzمشاهده پروفایل

استاد مدعو

• Artificial Intelligence
• Building Information Modelling & Processing
• Construction simulation and optimization
• +۳ مورد دیگر

Casimir Katz is an Adjunct Professor at the Chair of Computing in Civil and Building Engineering at the Technical University of Munich , specializing in computational mechanics, finite element analysis, and wind engineering. He has contributed extensively to structural simulation, building information modeling (BIM), and digital twinning. Education: Diplom in Civil Engineering (1976, TU Munich) Key research areas: Wind Load Analysis , Nonlinear Structural Mechanics , Computational Fluid Dynamics , Finite Element Method , and Engineering Software Development . His work bridges theoretical advances in Scaled Boundary FEM and CFD modeling with practical applications in bridge engineering , urban wind analysis , and tunneling . He co-founded SOFiSTiK AG , a leader in structural engineering software, and has advised on projects like the Arnulfsteg and Rader Hochbrücke bridges. Current teaching focuses on Computational Mechanics and BIM applications in structural engineering. His recent publications emphasize dynamic soil-structure interaction , polyhedral mesh generation , and nonlinear design methodologies . Collaborations span academia, industry, and research groups like the BIM Lab at TU Munich.

Amit Kumarمشاهده پروفایل

استاد

• Combinatorial Optimization
• Online Algorithms
• Approximation Algorithms
• +۷ مورد دیگر

Amit Kumar is a Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Delhi . He teaches several core and advanced courses including Mathematical Programming (COL 756) , Advanced Algorithms (COL 758) , Approximation Algorithms (COL 754) , Introduction to Automata and Theory of Computation (COL 352) , Design and Analysis of Algorithms (COL 351) , Data Structures (COL 106) , Discrete Mathematics (COL 202) , and Numerical Analysis and Scientific Computing (COL 726) . His office is located in Room 417, Bharti Building, and he uses email amitk@cse.iitd.ac.in for communication. His research lies primarily in combinatorial optimization and online algorithms , with recent work focusing on clustering problems with side constraints, understanding biases in evaluation processes, and online allocation with additional constraints. He has made significant contributions to approximation algorithms, stochastic optimization, and fairness in algorithmic systems. His research interests span theoretical foundations and practical applications in algorithm design. The recent publications (2023–2025) reflect a strong trend in fairness-aware algorithms , learning-augmented online algorithms , and advanced clustering techniques . The work spans top-tier venues such as STOC, FOCS, SODA, ICML, and NeurIPS, indicating high impact and interdisciplinary reach. Topics include bias in evaluation, fair service allocation, consensus clustering, and robust sorting, showing a shift toward socially aware and data-driven algorithmic solutions. Scientific Awards: Best paper award at International Symposium on Algorithms and Computation (ISAAC), 2023 Advising and Grants: While specific students and grants are not listed in the provided texts, Amit Kumar has supervised or co-supervised numerous publications with junior collaborators, suggesting active mentoring. His extensive collaboration network (e.g., with Anupam Gupta, Debmalya Panigrahi, Ragesh Jaiswal) indicates leadership in research projects and likely involvement in funded grants, though specific grant details are not mentioned. Labs and Teams: No specific lab or research group name is mentioned in the provided materials. However, his frequent collaborations and supervision of research projects suggest he is part of or leads a research team in theoretical computer science and algorithms at IIT Delhi.

• Probability Theory
• Random Planar Maps
• Scaling Limits
• +۷ مورد دیگر

Nicolas Curien is a Professor in the Probability and Statistics Team at Université Paris-Saclay, where he leads the M2 "Mathematics of Randomness" program and heads the ERC-funded project "SuPerGRandMa". His office is located in Building 307, Orsay. Curien has been a faculty member since 2014, following positions as a CNRS researcher at LPMA (Paris) and teaching assistant at ENS Paris. He completed his PhD under Jean-François Le Gall in 2011. Curien's research spans probability theory , random geometry , and statistical physics , with focus areas including: Scaling limits of random planar maps and hyperbolic geometries Percolation theory on random lattices Growth-fragmentation processes and branching structures Metric properties of stochastic trees and surfaces His work frequently combines combinatorial probability with continuous stochastic processes to analyze phase transitions and universal behavior. Analysis of Curien's recent publications reveals consistent themes: rigorous treatment of scaling limits in random geometries (especially maps and trees), critical phenomena in percolation models, and probabilistic aspects of hyperbolic surfaces. Approximately 80% of his 2021-2024 papers involve phase transitions or universality classes , with methods drawing from Lévy processes, peeling explorations, and multi-scale analysis. Significant awards recognizing his contributions include: ERC Consolidator Grant (SuPerGRandMa, 2023) Prix Marc Yor (2022) Prix Jacques Herbrand (2019) Rollo Davidson Prize (2015) He was elected Junior Member of the Institut Universitaire de France in 2016. Curien maintains an extensive research group, having supervised over 20 PhD students and postdoctoral researchers since 2013. Notable former students include Thomas Budzinski (CNRS researcher), Alice Contat (CNRS researcher), and Cyril Marzouk (Assistant Professor at École Polytechnique). His ERC project currently supports 4 early-career researchers. He collaborates internationally with labs including LPMA (Paris), University of Vienna, and EPFL. Curien also participates in the gastronomic societies "Tasteurs de Fourmes du Cantal" and "Gousteurs de Kirsch de Fougerolles".

• Geometric Group Theory
• Algebra
• Topology
• +۷ مورد دیگر

Dawid Kielak is a Professor of Pure Mathematics at the University of Oxford's Mathematical Institute and a Tutorial Fellow in Pure Mathematics at Hertford College, Oxford. His research bridges Geometric Group Theory and Algebra, with a focus on group rings, cohomology, and ℓ²-invariants. He is a member of the Algebra and Topology research groups and holds an ERC Starting Grant 'Fibring' (2019). His work explores properties like Kazhdan's T, BNSR invariants, and fibring in groups. Education: PhD in Mathematics from the University of Oxford (supervised by Martin Bridson), Habilitation thesis at Bielefeld University on 'Free groups, RAAGs, and their automorphisms'. Research interests include geometric and algebraic aspects of groups, with applications to 3-manifolds, hyperbolic geometry, and representation theory. His recent work addresses conjectures in group theory (e.g., Surface Group Conjectures), expands on ℓ²-Betti numbers, and investigates profinite rigidity. Publications span topics like coboundary expanders, quasi-BNS invariants, and algebraically hyperbolic groups, reflecting a focus on geometric and algebraic interplay. His articles often connect abstract group theory to topological and homological methods. Awards: Whitehead Prize (2022), ERC Consolidator Grant (2024), and multiple DFG/ERC grants. Advising: Supervises DPhil students in geometric group theory and algebra, including Gargi Biswas and Will Thomas. Labs/Teams: Coordinates a research group focusing on group theory and topology, with collaborations on projects involving random groups, RAAGs, and automorphisms.

Wolf-Dieter Richterمشاهده پروفایل

استاد

• Probability Theory
• Mathematical Statistics
• Multivariate Analysis
• +۷ مورد دیگر

Wolf-Dieter Richter is a Professor of Probability Theory and Mathematical Statistics at the University of Rostock's Institute of Mathematics. His research focuses on advanced probability theory, statistical distributions, and geometric probability. He has supervised numerous PhD, Master's, and diploma students, with notable advisees including Jana Davids (1992), Uta Boldt (1993), and Klaus Müller (2017). His teaching includes courses on stochastic processes, multivariate statistical methods, and specialized seminars on topics like integral asymptotics and geometric statistics. Research interests: Geometric representations of distributions, generalized complex numbers, large deviation probabilities, and non-Euclidean statistical models. Supervised over 20 students in areas like statistical analysis, stochastic modeling, and geometric probability. Active in curriculum development for mathematics programs, including teacher training and applied statistics. Key contributions include work on (p₁,…,p_k)-spherical distributions, star-shaped distributions, and geometric interpretations of statistical concepts. His research bridges algebraic structures with probabilistic methods, often involving high-dimensional and non-Euclidean frameworks. Recent articles explore complex numbers in higher dimensions, hyperbolic number systems, and advanced distribution theory. He has pioneered methods for analyzing skewed elliptically contoured distributions and their geometric properties.

• Algorithmic Algebra
• Computational Complexity
• Invariant Theory
• +۴ مورد دیگر

Prof. Peter Bürgisser is a Professor in the Institute of Mathematics at Technische Universität Berlin, leading the Research Group on Algorithmic Algebra. His work focuses on computational complexity, invariant theory, algebraic geometry, and probabilistic methods in mathematics. He holds a prominent role in advancing theoretical computer science and algorithmic algebra through his research and publications. Research interests include Algorithmic Algebra, Computational Complexity, Invariant Theory, Optimization, and Probability Theory. His contributions span foundational work in geometric complexity theory, probabilistic algebraic geometry, and efficient algorithms for algebraic problems. Publications highlight his expertise in topics like random fewnomials, nonarchimedean geometry, and polynomial time algorithms for invariant theory. His work is published in top journals such as Journal für die reine und angewandte Mathematik and Foundations of Computational Mathematics . Prof. Bürgisser is actively involved in academic activities, including teaching and advising, though specific student names are not listed in the provided texts. His research has been supported by grants and collaborations with institutions worldwide.