جست‌وجوی استاد و پژوهشگر

• Algebraic Geometry
• Complex Geometry
• Mathematical Physics
• +۳ مورد دیگر

Robert Berman is a Professor in the Department of Mathematical Sciences at the University of Gothenburg. He is affiliated with the Algebra and Geometry division and can be reached at robertb@chalmers.se. His research focuses on advanced areas of mathematics including algebraic geometry, complex geometry, and geometric analysis, with a particular emphasis on Kähler metrics, Monge-Ampère equations, and probabilistic methods in geometry. His work bridges pure mathematics with applications in theoretical physics and numerical analysis. Key research themes include the study of K-stability in algebraic geometry, the interplay between statistical mechanics and geometric structures, and the analysis of discretized Monge-Ampère equations in optimal transport. Recent publications (2023–2025) address Hölder inequalities in Kähler geometry, Manin-Peyre conjectures, and probabilistic approaches to Kähler-Einstein metrics. Berman collaborates extensively with leading researchers such as Bo Berndtsson and Sébastien Boucksom. His contributions span foundational results in geometric analysis and their implications for birational geometry and arithmetic geometry. No awards or grants are explicitly listed in the provided materials.

Klas Markströmمشاهده پروفایل

استاد

• Combinatorics
• Graph Theory
• Hypergraphs
• +۳ مورد دیگر

Klas Markström is a Professor at the Department of Mathematics and Mathematical Statistics, Umeå University. He holds academic qualifications as a Docent and a Recognised University Teacher in Mathematics. His primary research interests include combinatorics, graph theory, hypergraphs, computational combinatorics, linear algebra, and mathematical physics. He utilizes Swedish supercomputing resources, including those at HPC2N, for his research. Markström has advised PhD students Lan Anh Pham (2019) and Joel Larsson (2018). His postdoctoral collaborators include Jakub Sliacan, Fei Song, and Victor Falgas-Ravry. His work spans theoretical contributions to combinatorics, computational methods, and applications in statistical mechanics and algorithm design. Notable research trends include explorations of Condorcet domains in social choice theory, extremal graph/hypergraph problems, and algorithmic solutions for SAT problems. His software contributions include the Umsat SAT-solver and GrafPack, a Mathematica package for graph theory. He has published extensively on topics such as Turán hypergraphs, covering designs, and computational techniques for graph enumeration. Collaborations involve interdisciplinary projects with physicists and computer scientists, reflecting his engagement with both pure and applied mathematics. His research often bridges combinatorial theory with computational experimentation, yielding impactful results in discrete mathematics and beyond.

Robert Johanssonمشاهده پروفایل

دانشیار

• Discrete Mathematics
• Graph Theory
• Combinatorics
• +۳ مورد دیگر

Robert Johansson is an Associate Professor at the Department of Mathematics and Mathematical Statistics, Umeå University, and holds an affiliated position with the Faculty Office of Science and Technology. His research focuses on discrete mathematics and graph theory, with a strong emphasis on combinatorial structures and theoretical foundations. Research Focus His work explores critical areas in graph theory, including edge-decompositions, chromatic numbers, and path-factors. He has contributed to understanding extremal properties of graphs and combinatorial optimization problems in planar and r-partite graph systems. Publications The majority of his publications fall under discrete mathematics and theoretical computer science, with recurring themes in graph theory, combinatorial analysis, and network structures. His 2012 educational text on advanced mathematics further highlights his contributions to pedagogical frameworks. Labs & Teams Member of the Discrete Mathematics research group at Umeå University

• Quantitative Finance
• Credit Risk
• Financial Engineering
• +۳ مورد دیگر

Roles and Affiliations: Alexander Herbertsson is a Senior Lecturer in Statistics and Quantitative Finance at the University of Gothenburg, affiliated with the CFF-Centre for Finance. He is based in the Department of Economics with Statistics, located at Vasagatan 1, Gothenburg. His work focuses on financial risk management, credit risk modeling, and quantitative finance methodologies. Education: Ph.D. in Economics: Quantitative Finance (2007), University of Gothenburg Licentiate of Engineering in Industrial Mathematics (2005), Chalmers University of Technology M.Sc. in Engineering Physics (Applied Mathematics specialty) (2001), Chalmers University of Technology Research Interests: Herbertsson's research emphasizes applied financial mathematics and statistical methods in finance. Key areas include credit risk modeling (default contagion, systemic risks), financial engineering, and the development of dynamic models for portfolio credit risk. His work often integrates Markov chain models, phase-type distributions, and stochastic processes to analyze dependency structures and pricing of credit derivatives. Recent studies explore saddlepoint approximations for portfolio risk analysis and risk management under exogenous shocks. Teaching: He teaches advanced courses in credit risk modeling, quantitative finance, and applied probability theory, emphasizing practical applications in risk management and financial markets. Grants and Labs: While specific grants are not detailed in the text, his affiliation with the CFF-Centre for Finance suggests involvement in collaborative financial research projects. His work often addresses real-world applications of theoretical models in systemic risk and portfolio hedging.

Zhenxia Liuمشاهده پروفایل

دانشیار

• Mathematical Statistics
• Probability Theory
• Large Deviations
• +۳ مورد دیگر

Zhenxia Liu is an Associate Professor in the Department of Mathematics at Linköping University, Sweden, affiliated with the Division of Applied Mathematics (TIMA). Her work contributes to theoretical and applied probability, with a focus on stochastic processes and statistical modeling. Her research interests lie at the intersection of mathematical statistics and probability theory. Key areas include large deviations , longest runs in Markov chains , and Monte Carlo methods . These topics are central to understanding rare events, sequential dependencies, and numerical estimation techniques in complex systems. The recent publications demonstrate a consistent focus on probabilistic analysis of dependent structures, particularly through Markov models. Her work combines theoretical rigor with applications in computational statistics, showing trends toward improving bounds and simulation efficiency in stochastic modeling. Mathematical Statistics Probability Theory Large Deviations Markov Chains Monte Carlo Methods Computational Mathematics Zhenxia Liu has actively contributed to high-quality journals such as Statistics and Probability Letters , Results in Applied Mathematics , and Probability and Mathematical Statistics . While no formal advising or grant information is available in the provided text, her collaborative publications suggest engagement in research networks within applied mathematics. She is part of the research environment in Applied Mathematics at Linköping University, which focuses on computational mathematics, optimization, and mathematical modeling across science and engineering disciplines.

Tom Brittonمشاهده پروفایل

استاد

• Epidemic modeling
• Biostatistics
• Network analysis
• +۵ مورد دیگر

Tom Britton is a Professor in Mathematical Statistics (Holder of the Cramér chair) at the Department of Mathematics, Stockholm University. He leads the SU-Infection spread modeling research group and serves as chairman of the Stockholm Mathematics Center (SMC). His work primarily focuses on developing and analyzing mathematical/statistical models for infection spread and applying statistical methods to infection spread data. His research interests span epidemic modeling, biostatistics, network analysis, and mathematical statistics with applications toward genetics and molecular biology including phylogenetics. Britton's work encompasses applications of biostochastics and biostatistics, discrete random structures, and finance and insurance. He has made significant contributions to understanding disease transmission dynamics, particularly during the COVID-19 pandemic. Britton's recent publications demonstrate a strong emphasis on practical applications of mathematical models to public health challenges. His work examines contact tracing strategies, vaccine impact analysis, immunity waning dynamics, and optimal intervention strategies. There is a clear pattern of translating theoretical mathematical models into actionable public health insights, with particular focus on the interplay between population heterogeneity, immunity levels, and intervention effectiveness. As an academic leader, Britton serves as academic editor for PLoS Comp Biol and associate editor for Journal of Mathematical Biology and JRSS A (Statistics in Society). He is also a board member of the European Society for Mathematical and Theoretical Biology (ESMTB). Britton actively mentors the next generation of researchers, currently supervising PhD student Fanny Bergström and Post Doc Martina Favero. Throughout his career, he has successfully guided 13 PhD students and multiple postdoctoral researchers. His current research is supported by significant grants from the Swedish Research Council (3.6 MSek, PI 2021-2024) and the KA Wallenberg Foundation (0.7 MSek, PI 2023-2025). The SU-Infection spread modeling research group, which Britton leads, develops and analyzes mathematical/statistical models for the spread of infection and applies statistical methods to adapt these models to infection spread data. This work has been particularly relevant during recent pandemics and continues to inform public health decision-making.

• Dynamical systems
• Discrete mathematics
• Machine learning
• +۸ مورد دیگر

Jonas Nordqvist is an Assistant Professor at the Department of Mathematics, Faculty of Technology, Linnaeus University. His research spans dynamical systems , discrete mathematics , and machine learning , with a focus on reinforcement learning and interdisciplinary applications.

Timo Vilkasمشاهده پروفایل

مدرس ارشد

• Probability Theory and Statistics
• Interacting Particle Systems
• Finite Graphs
• +۲ مورد دیگر

Timo Vilkas is a Senior Lecturer at the Department of Statistics, Lund University. His research focuses on probability theory and stochastic processes on discrete structures. Key Research Areas: Random walks, finite/infinite graphs, interacting particle systems, branching processes Recent publications analyze probabilistic dynamics on lattices and trees, including water transport on finite graphs (2025), Maker-Breaker games on Galton-Watson trees (2024), and competitive processes driven by branching random walks (2023). His work combines combinatorial probability with graph-theoretic applications. The averaging process on infinite graphs (2024) and left-continuous random walks on Z (2024) highlight his technical expertise in discrete stochastic systems. Research trends show emphasis on structural properties of graphs and probabilistic modeling of competitive/cooperative processes.

Johan Håstadمشاهده پروفایل

استاد

• Theoretical Computer Science
• Computational Complexity
• Circuit Complexity
• +۳ مورد دیگر

Johan Håstad is a Professor at the Department of Mathematics, School of Engineering Sciences, KTH Royal Institute of Technology. His research focuses on theoretical computer science, particularly algorithms, computational complexity, approximation algorithms, and cryptography. He is funded by the Knut and Alice Wallenberg Foundation through project grants and the Wallenberg AI, Autonomous Systems and Software Program (WASP). External Funding: Knut and Alice Wallenberg Foundation, WASP Editorial Roles: Theory of Computing, TheoretiCS Professional Activities: Cyber Defense Center, Royal Swedish Academy of Sciences (former chairman) Research Interests : • Algorithms and Complexity • Circuit Complexity • Approximation Algorithms • Quantum Computing and Cryptography Scientific Awards : Knut and Alice Wallenberg Foundation Support Labs and Teams : • Involved in KTH's Cyber Defense Center • Editor for key journals in theoretical computer science

Carl Johan Casselgrenمشاهده پروفایل

استاد

• Discrete Mathematics
• Graph Theory
• Graph Coloring
• +۴ مورد دیگر

Carl Johan Casselgren is a Professor and Head of the Division of Algebra, Geometry and Discrete Mathematics (ALGD) at the Department of Mathematics, Linköping University. He is actively engaged in research and teaching in discrete mathematics and is a core member of the graph theory research group at the university. Institution: Linköping University Department: Department of Mathematics (MAI) Division: Algebra, Geometry and Discrete Mathematics (ALGD) Role: Professor and Head of Division His research focuses on discrete mathematics, particularly graph theory, with emphasis on graph coloring, structural properties of graphs, and combinatorial optimization. He investigates problems such as edge colorings, list colorings, and the coloring of graph products, contributing to both theoretical developments and algorithmic aspects. Recent publications (2024–2025) reveal a consistent focus on edge coloring problems, including near-interval colorings, extensions of partial colorings, and the coloring of Cartesian products and hypergraphs. These works demonstrate a deep engagement with combinatorial structures and theoretical graph problems, often involving probabilistic and structural methods. While no specific scientific awards are mentioned in the provided texts, his sustained publication record in high-quality journals such as Discrete Applied Mathematics , The Electronic Journal of Combinatorics , and Discussiones Mathematicae. Graph Theory underscores his active and respected role in the mathematical community. He collaborates with researchers from Sweden and abroad, including Mesfin Masre, Fikre B. Petros, and Petros A. Petrosyan. Although no formal advisees are listed, his leadership role and publication collaborations suggest involvement in mentoring students and junior researchers. He is part of a vibrant research division with around twenty members, contributing to a dynamic academic environment. The ALGD division conducts research in algebra, geometry, topology, dynamical systems, combinatorics, and graph theory. The graph theory group specifically focuses on classical problems with an emphasis on graph coloring and Hamiltonian graph theory, aligning closely with Casselgren’s research interests.

Johan Lyhagenمشاهده پروفایل

استاد

• Time series econometrics
• Cointegration analysis
• Panel data analysis
• +۶ مورد دیگر

Johan Lyhagen is a Professor of Statistics at the Department of Statistics, Uppsala University, within the Faculty of Social Sciences. His contact information includes mobile phone: +46 70 425 02 02 and email: Johan.Lyhagen@statistik.uu.se. He has been a full Professor of Statistics since 2010, having been promoted to professor specializing in time series econometrics two years prior. Professor Lyhagen's main research area is time series econometrics, with particular focus on cointegrated relationships in economic equilibriums. His work examines how to empirically test for and estimate these equilibriums, with recent interest in how short-term dynamics may differ across business cycles. Beyond his primary focus, he has conducted research in psychometrics (non-linear structural equation models, robust inference), optimal binning in histograms, and measurement error problems. His research demonstrates a strong methodological foundation with applications across multiple economic and social domains. His recent publication trends (2016-2025) show a diverse research portfolio that spans econometrics, statistics, and interdisciplinary applications. His work demonstrates expertise in spatial econometrics, climate change impacts on agriculture, robust statistical methods, structural equation modeling, and policy evaluation. The research shows a consistent methodological focus on time series analysis, panel data, and statistical modeling across various substantive domains including economics, environmental science, health, and energy markets. Professor Lyhagen has substantial experience in academic administration, having served as head of department, member of faculty board, and on committees for the recruitment of professors. He supervises PhD students and is actively involved in teaching, demonstrating a commitment to both research excellence and academic development.

• Numerical Analysis
• Differential Equations
• Geometric Numerical Integrators
• +۳ مورد دیگر

David Cohen is a Professor in the Department of Applied Mathematics and Statistics at Chalmers University of Technology. His academic career centers on the development and analysis of numerical methods for differential equations, with particular expertise in geometric numerical integration techniques. His research focuses on structure-preserving numerical methods for approximating solutions to deterministic and stochastic dynamical systems. Cohen's work spans geometric numerical integrators, stochastic differential equations, and the numerical analysis of partial differential equations. His approach emphasizes preserving underlying geometric structures in numerical schemes, which is crucial for long-term accuracy and stability in simulations. The publication record shows consistent research output with a clear trajectory toward increasingly complex stochastic systems. Recent work focuses on splitting integrators, positivity-preserving schemes, and specialized methods for stochastic wave equations, Manakov systems, and Lie-Poisson structures. His research demonstrates strong connections to applications in physics, optics, and mathematical modeling of complex systems. Cohen leads or participates in multiple research projects funded by Vetenskapsrådet (VR) and the European Commission, including work on stochastic FitzHugh-Nagumo models and numerical methods for PDEs with random dispersion. His collaborative network includes researchers across Europe and North America, reflecting the international nature of his work in computational mathematics.

Daniel Ahlbergمشاهده پروفایل

دانشیار

• Probability Theory
• Spatial Stochastic Processes
• Percolation Theory
• +۳ مورد دیگر

Daniel Ahlberg is an Associate Professor in the Department of Mathematics at Stockholm University. His research utilizes probability theory to study spatial random processes including percolation models, random growth systems, branching processes, and combinatorial optimization problems. Current investigations focus on phase transitions in percolation, noise sensitivity of random systems, and geometric properties of random metrics. Research has established fundamental results on sharpness of phase transitions in continuum percolation, scaling limits of Boolean functions, and asymptotic behavior of first-passage percolation models. Recent work examines chaos phenomena in random growth models and statistical properties of geodesics in disordered media. Funded by multiple Swedish Research Council grants including a current research project grant (2022-2025). Recipient of the Ruth and Nils-Erik Stenbäck Foundation stipend (2022). Supervises doctoral students in probability theory and stochastic processes. Developed educational materials on probability fundamentals and Markov chain mixing. Teaches courses in probability theory, stochastic processes, and discrete mathematics.

• Dynamical Systems
• Number Theory
• Cryptography
• +۳ مورد دیگر

Marcus Nilsson is a Lecturer in Mathematics at Linnaeus University's Faculty of Technology, where he focuses on teaching, research, and administrative responsibilities. He serves as the program manager for the Applied Mathematics program and vice dean for teacher education. Nilsson has taught at UC Berkeley, supported by the STINT Teaching Sabbatical program, and represents Linnaeus University on the National Committee for Mathematics at the Royal Academy of Sciences, addressing school collaboration issues. Teaching: Courses in discrete mathematics, number theory, and cryptography. Research: Specializes in dynamical systems, number theory, and cryptography, with external projects in information security. Commissions: Vice Dean for Teacher Education, project manager for Sonja Kovalevsky Days 2024-2025. Collaboration: Member of the International Center for Mathematical Modeling (ICMM), emphasizing interdisciplinary applications.

Joanna Tyrchaمشاهده پروفایل

استاد

• Statistical Inference
• Econometrics
• Neuroscience
• +۶ مورد دیگر

Joanna Tyrcha is a Professor in Mathematical Statistics at the Department of Mathematics, Stockholm University, and currently serves as the Head of the Department. Her academic career spans institutions in Poland, Canada, and Sweden, with roles including Lecturer, Director of Undergraduate Studies, and Head of the Division of Mathematical Statistics. M.S., Mathematical Statistics, Warsaw School of Economics, 1980 Ph.D., Mathematics, Jagiellonian University, 1989 Associate Professor, Mathematical Statistics, Stockholm University, 2003 Professor, Mathematical Statistics, Stockholm University, 2011 Her research integrates statistical inference , econometrics , and neuroscience , focusing on cell cycle models , neural connectivity , biological information processing , causality , and ion channel modeling . Recent publications highlight applications of Ising models to neural data, nonstationary dynamics , and transfer entropy in non-Gaussian distributions. Key collaborations include work with J. Hertz and Y. Roudi on network inference, and with C. Nellåker on mixture models for genomic data. Joanna has taught courses such as Probability Theory and Econometrics . She leads the Mathematical Statistics research group at Stockholm University, which focuses on biostochastics , biostatistics , discrete random structures , and finance/insurance applications.