جست‌وجوی استاد و پژوهشگر

• Geometric Deep Learning
• Compositional Learning
• Optimal Transport
• +۴ مورد دیگر

Mircea Petrache is an Assistant Professor at the Department of Mathematics, Pontifical Catholic University of Chile. His research focuses on geometric deep learning, compositional learning, optimal transport, calculus of variations, and geometric measure theory, with applications to large point configurations and mathematical analysis. He holds a PhD in Mathematics from ETH Zürich (2013) and an MSc from Scuola Normale Superiore (2008). Education: PhD in Mathematics, ETH Zürich, 2013 MSc in Mathematics, Scuola Normale Superiore, 2008 Research Interests: Petrache explores the interplay between geometric principles and machine learning, particularly in equivariant networks and compositional systems. His work on optimal transport and calculus of variations addresses energy minimization and crystallization problems in materials science. Recent projects include symmetry-based structured matrices and topological pseudodistances for data analysis. Grants: Fondecyt Regular Grant (2021–2025) on rigidity and uniformity in large point configurations. Events & Organization: Co-organized workshops such as 'Theoretical and Mathematical Aspects of Deep Learning' (2022) and 'Calculus of Variations: A New Generation' (2024). Active in conferences including NeurIPS, ICIAM, and AIM workshops on discrete geometry.

Dmitriy Bilykمشاهده پروفایل

استاد

• Harmonic Analysis
• Functional Analysis
• Discrepancy Theory
• +۲ مورد دیگر

Dmitriy Bilyk is a Professor in the School of Mathematics at the University of Minnesota, based in Vincent Hall. His research explores harmonic analysis, functional analysis, and discrepancy theory, with applications to geometric inequalities and optimization problems on spheres. Research focuses on: Energy minimization and measure discreteness on spheres Discrepancy theory in arbitrary dimensions Geometric inequalities and spherical optimization Publications address mathematical structures in discrepancy theory, energy optimization, and geometric inequalities, with recent emphasis on sphere packing and measure theory applications. No awards are documented in the provided text. Research is supported by NSF grants and the Simons Foundation Collaboration Grant.

Russell W. Howellمشاهده پروفایل

استاد

• Complex Analysis
• Mathematics and Theology
• Philosophy of Mathematics
• +۳ مورد دیگر

Russell W. Howell is the Kathleen Smith Chair of Natural and Behavioral Sciences at Westmont College. He holds a BS from Wheaton College, an MSc from the University of Edinburgh, and a PhD from The Ohio State University. His research focuses on complex analysis and the intersection of mathematics with theology and philosophy. Howell has held visiting positions at institutions including UC Berkeley, Calvin University, and Oxford University, and has been honored twice as Westmont’s Teacher of the Year. He co-authored Complex Analysis for Mathematics and Engineering and contributed to interdisciplinary works like Mathematics Through the Eyes of Faith . His textbook Complex Analysis for Mathematics and Engineering is now freely available via the Open Textbook Initiative. Howell’s academic contributions span theoretical mathematics, pedagogical innovation, and interdisciplinary scholarship. His work bridges mathematical rigor with theological inquiry, exploring questions about the nature of mathematical beauty, faith-based perspectives in STEM, and the philosophical implications of mathematical concepts. He has also served as a leader for Westmont’s study abroad programs in Europe and Mexico, integrating academic and experiential learning. Notable achievements include his Teacher of the Year awards, his role as co-editor of Mathematics in a Postmodern Age , and his advocacy for open educational resources. Howell’s research articles address topics ranging from annular functions and harmonic polynomials to the historical and cultural dimensions of mathematics. His awards and recognitions highlight his excellence in teaching and scholarship, while his academic service includes military service in the U.S. Army in South Korea and leadership in fostering interdisciplinary dialogue between mathematics and religion.

Friedrich Martin Schneiderمشاهده پروفایل

پژوهشگر

• Topological Groups
• Functional Analysis
• Ergodic Theory
• +۴ مورد دیگر

Friedrich Martin Schneider is a mathematician affiliated with the Institute of Discrete Mathematics and Algebra at the Faculty of Mathematics and Computer Science , Technische Universität Freiberg. His research focuses on topological groups, functional analysis, ergodic theory, and dynamical systems, often intersecting with algebra and geometry. His work explores exotic groups without non-trivial unitary representations, measure concentration phenomena, and the escape property in topological groups. He has contributed to the MacWilliams extension theorem for infinite rings, the Liouville property in random walks, and the classification of profinite algebras. Collaborations with Sławomir Solecki, Andreas Thom, and Vladimir Pestov highlight his interdisciplinary impact. Recent publications emphasize geometric group theory, invariant means, and applications to computer science, including constraint satisfaction problems and intrinsic dimensionality in data analysis. Funded by the German Research Foundation (DFG), he leads a research group with Paula Kahl, Josefin Bernard, and Yannik Höll.

Jörn Schulzمشاهده پروفایل

دانشیار

• Statistical Shape Analysis
• Medical Imaging
• Computational Statistics
• +۳ مورد دیگر

Jörn Schulz is an Associate Professor in the Department of Mathematics and Physics at the University of Stavanger, affiliated with the Faculty of Science and Technology. His research focuses on statistical shape analysis, medical imaging, and computational statistics with applications in neuroscience and biostatistics. Recent work includes studies on shape representation in medical imaging, rotational deformation analysis, and clinical studies related to Parkinson's disease and neonatal resuscitation outcomes. Key research areas include statistical methods for geometric data, non-Euclidean analysis, and interdisciplinary applications in healthcare. His publications span journals like Journal of Computational and Graphical Statistics, Medical Image Analysis, and Neurology. Notable contributions include developing shape analysis techniques for medical objects and analyzing clinical data from Parkinson's disease cohorts. Publications trends show strong focus on combining statistical theory with medical applications, particularly in imaging and patient outcomes. He has collaborated on projects involving newborn resuscitation protocols, elderly transitional care safety, and sleep pattern analysis in aging populations. His work frequently integrates advanced statistical modeling with real-world clinical challenges. Academic activities include presentations at conferences such as DAGStat and ERCIM, and involvement in projects like the Safer Births initiative. Despite not explicitly listing awards, his extensive publication record reflects significant contributions to statistical methodology and medical data analysis.

Michael Goldmanمشاهده پروفایل

پژوهشگر

• Partial Differential Equations
• Geometric Measure Theory
• Image Processing
• +۵ مورد دیگر

Michael Goldman is a junior CNRS researcher at the Centre de Mathématiques Appliquées (CMAP) of École Polytechnique. His research focuses on Partial Differential Equations (PDEs), Geometric Measure Theory, Optimal Transportation, and Calculus of Variations. He explores applications in material sciences, homogenization, and mathematical physics. Notable contributions include studies on Gamma convergence in superconductors, optimal transport dynamics, and branched transport models. His work bridges theoretical analysis with applied problems, addressing topics like liquid drop models, particle systems, and phase transitions. Goldman actively participates in academic networks, organizing conferences and contributing to seminars such as the Parisian Calculus of Variations group. His research also touches on image processing and geometric flows, reflecting interdisciplinary interests in mathematical modeling and analysis.

Yassine El Maazouzمشاهده پروفایل

پژوهشگر

• Algebraic Geometry
• Non-Archimedean Geometry
• Commutative Algebra
• +۴ مورد دیگر

Yassine El Maazouz is a Harry Bateman Postdoctoral Scholar in the Division of Physics, Mathematics and Astronomy at Caltech, mentored by Matilde Marcolli. His research focuses on interactions between algebraic geometry, non-Archimedean geometry, number theory, and probability theory. He holds teaching roles at Caltech and UC Berkeley, including courses like Toric Geometry (Ma132C) and Probability (Ma140B). His work bridges pure mathematics with applications in mathematical physics and combinatorics. Research Interests: Algebraic Geometry (Tropical/Non-Archimedean aspects) Combinatorics (with applications to Grassmannians and cluster algebras) Number Theory (p-adic measures and arithmetic geometry) Mathematical Physics (amplitude calculations and spinor-helicity formalism) Recent Work Trends: Developing geometric frameworks for p-adic manifolds and invariant measures Exploring positive geometries in scattering amplitudes Investigating combinatorial structures in matrix algebras and valuations Teaching & Mentorship: Instructed advanced courses on toric varieties and probability theory at Caltech. Supervised student projects in algebraic geometry and stochastic processes. Active mentor in UC Berkeley's Statistics bridge program.

Martin Heidaمشاهده پروفایل

پژوهشگر

• Homogenization
• Partial Differential Equations
• Stochastic Homogenization
• +۶ مورد دیگر

Dr. Martin Heida is a researcher at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS), Berlin, where he has been a member of the Partial Differential Equations research group since 2015. His work focuses on homogenization theory, stochastic processes, and numerical methods for complex systems. He holds a PhD from the Universities of Heidelberg and Prague (2011), and prior to WIAS, he was a PostDoc at TU Dortmund (2011–2015) and a graduate student at the Heidelberg Graduate School of Mathematical and Computational Methods (2008–2011). Education : PhD in Mathematics and Physics, cotutelle between Heidelberg University (Prof. Willi Jäger) and Charles University Prague (Prof. Josef Málek), 2011 Diploma in Physics and Mathematics from Heidelberg University, 2008 Research Interests : His research spans stochastic homogenization, partial differential equations (PDEs), numerical analysis, and material modeling. He develops methods for multiscale problems in porous media, plasticity, and fracture mechanics, with applications to battery aging, geology, and phase separation. Grants & Projects : Third-party funded projects: SPP 2256 (Fractal and Stochastic Homogenization), Math+ project on battery aging dynamics Teaching : Recent courses include Nonlinear Analysis at TU Munich, Homogenization Theory, and Analysis for Engineers. Labs & Collaborations : Leads the HighVoronoi.jl project for high-dimensional Voronoi diagram computations and collaborates with researchers in applied mathematics and computational science.

• Financial Engineering
• Financial Risk Management
• Applied Mathematics
• +۴ مورد دیگر

Dan Pirjol is a Teaching Associate Professor at the School of Business, Stevens Institute of Technology. He holds a PhD in Theoretical Physics from the University of Mainz and an MS in Physics from the University of Bucharest. His research focuses on financial engineering, derivatives pricing, hedging, and risk management, employing asymptotic analysis and applied probability. Key areas include financial risk management, applied mathematics, numerical methods, and stochastic modeling of financial markets. He has industry experience in roles at Merrill Lynch, Markit Partners, and JP Morgan, specializing in model risk management and derivatives modeling. His publications span topics such as Asian options valuation, volatility modeling, GARCH risk analysis, and stochastic processes. He actively contributes to professional service roles, including co-editing a special issue of Risks and refereeing for journals like SIAM Journal on Financial Engineering. He teaches courses in financial engineering, market microstructure, and algorithmic trading. No scientific awards are listed, and no advising/grant details are provided. His work emphasizes quantitative finance and practical applications of theoretical models.

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.

Peter Gracarمشاهده پروفایل

مدرس

• Random Geometric Graphs
• Percolation Theory
• Interacting Particle Systems
• +۱ مورد دیگر

Peter Gracar is Lecturer in Probability at the University of Leeds School of Mathematics. His research focuses on geometric random graphs, multi-scale percolation, and interacting particle systems. He received his PhD from University of Bath (2017) and has held postdoctoral positions at University of Cologne. Current projects include percolation in inhomogeneous networks and analysis of spatial random processes. Research Areas: Percolation phase transitions, random graph connectivity, chemical distances in random media, and applications in network robustness. Academic Background: PhD University of Bath (supervised by Alexandre Stauffer), MSc ETH Zurich.

• Business economics
• Statistics
• Probability theory
• +۱ مورد دیگر

Fioralba Ajazi is a Research Fellow at the Danish Institute for IT Program Management, specializing in Software Engineering. She is a Co-Investigator on the Villum Kann Rasmussen Professorship project (2022–2027), focusing on IT Program Management and Program Management methodologies. Her work involves interdisciplinary research across Business economics, Statistics, Probability theory, and Applied mathematics. Research Interests Her research explores the intersection of stochastic processes and network modeling, particularly in neuronal connectivity and spatial network structures. This includes applications of random geometric graphs, phase transitions in complex systems, and the analysis of 2D network growth dynamics. Project Highlights Villum Foundation Project: Villum Kann Rasmussen Professorship (2022–2027), contributing to IT and program management frameworks. Awards No scientific awards explicitly mentioned, though she participates in a prestigious Villum Foundation-funded initiative. Advising & Grants While no students are listed, she collaborates on a multi-year, multi-disciplinary grant focusing on program management methodologies. Funding: Villum Foundation (~DKK 100M).

Matthew Kahleمشاهده پروفایل

استاد

• Combinatorics
• Probability Theory
• Geometric Group Theory
• +۳ مورد دیگر

Matthew Kahle is a Professor in the Department of Mathematics at The Ohio State University, where he has served since 2011. His research focuses on the interplay between topology, geometry, probability, and combinatorics, with applications to statistical physics and geometric group theory. He holds a PhD from the University of Washington (2007) and has held positions at Stanford University and the Institute for Advanced Study. Kahle advises multiple PhD students and has mentored numerous postdocs. His honors include the Simons Fellowship, NSF CAREER Award, and Sloan Research Fellowship. Education: PhD (2007) in Mathematics from the University of Washington; MS (2001) in Mathematics from Colorado State University. Earlier studies include a BS from the University of Chicago. Research interests emphasize stochastic topology, configuration spaces, and random simplicial complexes. He explores how probabilistic methods reveal structural properties in geometric and combinatorial systems. His work on persistent homology and topological phase transitions has influenced computational topology and statistical mechanics. Key awards include the 2019 Mercator Fellowship, AMS Fellowship, and Simons Fellowship. His Erdős number is 2, reflecting collaborations in combinatorics and graph theory. Kahle has also engaged in visiting roles at institutions worldwide, including TU Berlin and Queen Mary University of London. Advising spans over a dozen PhD students and postdocs, contributing to their success in academic and applied mathematics. His grants include NSF funding for research on topological phases and configuration space topology. Collaborative efforts with international researchers highlight his global impact in mathematical science. Labs/Teams: Kahle leads a research group focused on algebraic topology and its applications, collaborating with postdocs and students on projects ranging from random geometric complexes to topological data analysis.

• Stochastic Processes
• Differential Equations
• Financial Mathematics
• +۳ مورد دیگر

Tim King is a researcher specializing in stochastic processes and their applications on geometric structures. His work intersects probability theory, numerical analysis, and financial mathematics, with a focus on stochastic differential equations (SDEs) and their behavior on manifolds. He has contributed to the development of numerical schemes for SDEs on curved spaces and explored recurrence properties of Markov chains in negatively curved environments. Key research interests include geometric numerical integration, manifold approximations, and the interplay between stochastic processes and geometric structures. His findings have implications for modeling complex systems in finance, physics, and applied mathematics. King has co-authored three peer-reviewed articles in prestigious journals such as the Proceedings of the Royal Society A and ADVANCES IN APPLIED PROBABILITY . His research aligns with UN Sustainable Development Goals, particularly in areas requiring advanced mathematical modeling.

Damiano Brigoمشاهده پروفایل

استاد

• Financial Mathematics
• Risk Management
• Credit Risk
• +۳ مورد دیگر

Damiano Brigo is a Professor specializing in financial mathematics, risk management, and stochastic modeling. His research focuses on pricing, credit risk, counterparty risk, and commodities/inflation modeling. He holds a PhD in Filtering By Projection from VU Amsterdam (1996) and a Bachelor of Science from the University of Padua (1990). His work contributes to UN Sustainable Development Goals related to education and economic systems. Brigo has led projects like the 'Towards next generation energy systems models' (2011-2015) and actively participates in academic conferences, including the C.R.E.D.I.T. conference in Venice and the Scottish Financial Risk Academy in Edinburgh. His recent publications address XVAs in valuation, risk measures in portfolio constraints, and rough path theory applications in finance. Brigo’s contributions include over 50 research outputs in journals like Mathematical Finance and Journal of Banking and Finance . His research emphasizes theoretical advancements and practical applications in quantitative finance.