جست‌وجوی استاد و پژوهشگر

Christian Bargetzمشاهده پروفایل

استاد

• Nonlinear Functional Analysis
• Banach Spaces
• Locally Convex Spaces
• +۴ مورد دیگر

Christian Bargetz is a Professor of Functional Analysis at the University of Innsbruck, Austria, affiliated with the Faculty of Mathematics, Computer Science, and Physics (MIP). His primary research focuses on nonlinear functional analysis, Banach space theory, and distribution theory. He teaches advanced courses such as Optimization, Distribution Theory, and Functional Analysis, demonstrating his expertise in both theoretical and applied aspects of his field. Education: Completed his PhD in 2012 at the University of Innsbruck under the supervision of Norbert Ortner. His diploma thesis (2008) explored differential behaviors with Ulrich Oberst. Bargetz has held continuous academic positions since 2008, including roles as a lecturer and researcher. Research Interests: Specializes in iterative projection methods, generic properties of nonexpansive mappings, Fréchet spaces, and vector-valued distributions. His work bridges functional analysis with geometric measure theory and optimization, with applications in metric geometry and topological tensor products. Publications: Over 30 peer-reviewed articles in prestigious journals such as Canadian Journal of Mathematics , Journal of Mathematical Analysis and Applications , and Proceedings of the American Mathematical Society . Recent work includes studies on extremal nonexpansive mappings and Lipschitz function spaces. Grants & Projects: Principal investigator in FWF-funded projects on nonexpansive mappings and Banach spaces. Collaborates internationally, including with institutions in Israel, Poland, and Serbia. Teaching: Leads advanced courses in functional analysis, optimization, and distribution theory. Supervises bachelor's theses and master's projects on topics like extension operators for Lipschitz functions. Affiliations: Active member of the Functional Analysis working group and regularly participates in international conferences such as the Banach Afternoon, Winter School in Abstract Analysis, and DMV-ÖMG Annual Conferences.

David Croydonمشاهده پروفایل

دانشیار

• Probability theory
• Diffusions on random fractals
• Scaling limits
• +۵ مورد دیگر

David Croydon is an Associate Professor at the Research Institute for Mathematical Sciences (RIMS), Kyoto University. His research focuses on probability theory, particularly diffusions on random fractals and scaling limits of random walks on random graphs. He also investigates discrete integrable systems with random initial conditions. Dr. Croydon's primary research interests span several areas of probability theory and mathematical physics. His work centers on diffusions on random fractals and how these processes can be constructed as scaling limits of related random walks on random graphs. He has made significant contributions to understanding random walks on critical structures including Galton-Watson trees, uniform spanning trees, and percolation clusters. More recently, he has developed a growing interest in the behavior of discrete integrable systems such as the box-ball system, particularly when started from random initial conditions. His research often bridges theoretical probability with applications in statistical physics and mathematical physics. Dr. Croydon's recent publications demonstrate a dual focus on theoretical probability and mathematical physics. His work on random walks spans various structures including binary trees, critical percolation clusters, and uniform spanning trees. He has made significant contributions to understanding aging phenomena, heat kernel fluctuations, and scaling limits in random media. Simultaneously, his research on discrete integrable systems explores the connections between probability theory and soliton theory, particularly through the lens of the box-ball system and related models. These two research strands converge in his investigations of scaling limits and invariant measures for complex stochastic systems. Dr. Croydon's scientific contributions have been recognized through publications in top-tier journals across probability theory and mathematical physics, though specific awards are not mentioned in the available information. Dr. Croydon has supervised several doctoral students to completion, including Adam Bowditch (2017), George Andriopoulos (2019), Eleanor Archer (2020), and Takumu Ooi (2024). He has also served in advisory roles for other students including John Sylvester (2017). His collaborative research spans multiple international institutions, suggesting involvement in various research grants supporting his work in probability theory and mathematical physics. While specific lab names aren't mentioned, Dr. Croydon is part of the vibrant probability theory research group at the Research Institute for Mathematical Sciences (RIMS) at Kyoto University. His extensive collaborations with researchers worldwide, particularly in the UK, France, and Japan, indicate active participation in international research networks focused on stochastic processes, random media, and discrete integrable systems.

• Numerical Analysis
• Partial Differential Equations
• Wave Propagation
• +۷ مورد دیگر

Olof Runborg is a Professor in Numerical Analysis at the Royal Institute of Technology (KTH) in Stockholm, Sweden. He works in the Division of Numerical Analysis, Optimization and Systems Theory within the Department of Mathematics at KTH. His research focuses on developing and analyzing numerical methods for partial differential equations, particularly for wave propagation problems. His educational background includes: MSc in Electrical Engineering from KTH (1992) BSc in Economics & Business Administration from SSE (1994) PhD in Numerical Analysis/Applied Mathematics from KTH (1998) Postdoc at Paris VI University (1999) Postdoc at Princeton University's Program in Applied and Computational Mathematics (2000-2001) Became Docent at NADA in 2003 Appointed Professor at KTH in 2010 Professor Runborg's research centers on the numerical treatment of partial differential equations, with special emphasis on wave propagation problems. His work spans multiple areas including high-frequency waves, multiscale phenomena, numerical homogenization, uncertainty quantification, multiresolution analysis, Gaussian beams, and mesh generation. A recurring theme in his research is developing methods to solve computationally expensive problems more efficiently while maintaining accuracy. His approach often involves coupling different numerical methods or reformulating equations to create more efficient computational approaches. His research has applications across physics and engineering domains where wave phenomena are important. An analysis of his recent publications (2015-2025) shows continued focus on high-frequency wave propagation with expanding applications to areas like the Landau-Lifshitz equation for magnetic materials and elastic wave propagation. His work bridges theoretical numerical analysis with practical computational techniques, often developing novel methods like the WaveHoltz iteration for solving the Helmholtz equation. The publications demonstrate increasing attention to uncertainty quantification and multiscale methods while maintaining strong theoretical foundations in error analysis. Professor Runborg teaches several courses at KTH including Numerical Methods (basic course), Applied Numerical Methods, Numerical Algorithms for Data-Intensive Science, and Selected Topics in Numerical Analysis II. He serves as examiner for degree projects in Scientific Computing. His teaching reflects his research expertise in numerical methods and computational mathematics, providing students with both theoretical foundations and practical implementation skills. Beyond his core research, Professor Runborg has engaged in interesting side projects, such as his analysis of 'Numbers on the Web' where he investigated the frequency of numbers 11-1000 in web content, revealing patterns related to dates, time, computer systems, and cultural phenomena. This demonstrates his broader interest in data analysis and computational approaches to understanding patterns in information.

Susanna Thonمشاهده پروفایل

دانشیار

• Renewable Energy Conversion
• Photovoltaics
• Nanomaterials Engineering
• +۵ مورد دیگر

Susanna Thon is an Associate Professor in the Department of Electrical and Computer Engineering at Johns Hopkins University (JHU), affiliated with the Whiting School of Engineering. She serves as Associate Director of the Ralph O’Connor Sustainable Energy Institute (ROSEI) and a member of the Data Science and AI Institute. Her research focuses on nanomaterials engineering for optoelectronic devices, emphasizing solar energy conversion and sensing. Notable areas include plasmonic-photocatalytic systems using aluminum nanoparticles and nanostructured materials like colloidal quantum dots for next-generation devices. Thon holds a BSc from MIT (2005) and MSc/PhD in Physics from UC Santa Barbara (2008/2010). She joined JHU in 2013 after postdoctoral work at the University of Toronto. Her work is funded by agencies such as the NSF, U.S. Army, and Maryland Energy Innovation Institute. She has published over 50 peer-reviewed papers and received JHU’s Catalyst and Discovery awards. Key research projects include developing plasmonic systems to enhance light absorption in titanium dioxide and creating scalable fabrication techniques for optoelectronic materials. Thon’s team also advances quantum dot solar cells and novel characterization methods for energy materials. She actively participates in professional societies, including the Optical Society of America and IEEE. Her grants and collaborations aim to train the next generation in sustainable energy research, with recent initiatives funded through NSF and Space@Hopkins seed grants. Thon’s lab integrates nanophotonics, materials science, and machine learning to address global energy challenges.

Raphaël Beuzart-Plessisمشاهده پروفایل

پژوهشگر ارشد

• Harmonic analysis
• Differential geometry
• Algebraic number theory
• +۵ مورد دیگر

Raphaël Beuzart-Plessis is a CNRS Research Fellow affiliated with Aix-Marseille University and the Institute of Mathematics of Marseille (I2M) at Luminy Campus. He specializes in advanced areas of mathematics, including harmonic analysis, automorphic forms, representation theory, and number theory, with a focus on unitary groups and conjectures like Gan-Gross-Prasad. His work bridges algebraic geometry, differential geometry, and operator theory. Arithmetic, Geometry, Logic and Representations Group (AGLR) 2022-2027 ERC RELANTRA grant recipient Research interests span automorphic representations, L-functions, periods of automorphic forms, and harmonic analysis on real spherical spaces. He works extensively on the local and global Gan-Gross-Prasad conjectures, endoscopy, and supercuspidal representations. His recent publications analyze Plancher1el formulas, spherical characters, and congruences of automorphic forms. His 15 most recent publications (2014-2022) address topics such as the Gan-Gross-Prasad conjecture, Jacquet-Rallis's fundamental lemma, and the Asai Rankin-Selberg integrals. These works reflect his expertise in automorphic forms, representation theory, and number theory, often involving collaborations with leading mathematicians. 2016-2017 Peccot Prize for young mathematicians under 30 2022-2027 ERC RELANTRA grant for research in automorphic forms and representation theory Beuzart-Plessis has no listed students or laboratory teams but participates in the AGLR-RGR (Reduction Group Representations) team and has been an invited speaker at the 2022 International Congress of Mathematicians. His career includes guest lectures at Collège de France, including four sessions on Period factorizations and Plancherel formulas in 2017.

• Dynamical systems
• Ergodic theory
• Homogeneous spaces
• +۴ مورد دیگر

Manfred Einsiedler is a Professor in the Department of Mathematics at ETH Zurich, Switzerland, with office HG G 64.2 at Rämistrasse 101, 8092 Zurich. He teaches undergraduate and graduate courses including Linear Algebra (HS 2019), Analysis I/II, and Functional Analysis I/II, using his co-authored textbook Functional Analysis, Spectral Theory, and Applications . His research centers on dynamical and equidistribution problems in homogeneous spaces, with focus on closed horocycle orbits, geodesic orbits on the modular surface, and measure rigidity. Key contributions include work on effective equidistribution, entropy methods, and connections between ergodic theory and number theory. He has co-authored foundational texts: Ergodic Theory with a view towards Number Theory and Functional Analysis, Spectral Theory, and Applications in Springer's Graduate Texts in Mathematics series, alongside multiple in-progress volumes on entropy, homogeneous dynamics, and unitary representations. Recent publications explore integer points on spheres, rigidity of invariant measures, and Diophantine approximation on fractals, emphasizing collaborations with Lindenstrauss, Ward, Margulis, and Venkatesh. His work demonstrates consistent focus on homogeneous dynamics with applications to arithmetic problems, particularly through effective methods and measure classification theorems. While no specific awards or student lists are documented in the source, his extensive publication record and textbook authorship establish significant scholarly impact.

• Continuum Theory
• General Topology
• Real Analysis
• +۱ مورد دیگر

Assoc. Prof. Dr. Pavel Pyrih works in the Department of Mathematical Analysis at Charles University , Faculty of Mathematics and Natural Sciences , Prague. His research focuses on Continuum Theory , General Topology , and Real Analysis , with an emphasis on solving open problems through the Open Problem Seminar he leads. The seminar prioritizes student participation and collaborative research, resulting in joint publications and a dynamic academic environment.

Peter Huybersمشاهده پروفایل

استاد

• Climate change
• Paleoclimatology
• Environmental science
• +۸ مورد دیگر

Peter Huybers is a Professor of Earth and Planetary Sciences and Environmental Science and Engineering at Harvard University , where he investigates the climate system and its societal implications, including interactions between volcanism and glaciation , extreme temperature predictability , and climate change impacts on food production . Research interests span climate change attribution , paleoclimate reconstruction , drought dynamics , crop yield modeling , and earth system feedbacks . His work often integrates art-historical analysis with climate science, as seen in studies of 19th-century air pollution through Turner and Monet paintings . Scientific awards include funding from Harvard Data Science Initiative (2023) for projects on climate change and food supply volatility Amazon Web Services (2023) grant His 20+ peer-reviewed articles since 2020 focus on climate proxies , hydrological modeling , solar forcing , and agricultural-climate interactions , with recent work in Nature , PNAS , and Science Advances . Advising : Mentored 10+ PhD students including Parker Liautaud , Duo Chan , and Marena Lin , while leading research teams with current members like Greta Berendes and Caro Park . Former staff include Jon Proctor and Lucas Vargas Zeppetello , the latter now at UC Berkeley (2024).

Thomas Yizhao Houمشاهده پروفایل

استاد

• Multiscale Analysis
• Computational Mathematics
• Fluid Dynamics
• +۷ مورد دیگر

Thomas Yizhao Hou is the Charles Lee Powell Professor of Applied and Computational Mathematics at the California Institute of Technology, where he has served as a faculty member since 1998 and as Executive Officer of Applied and Computational Mathematics from 2000-2006. His research spans fundamental mathematical problems with significant implications for fluid dynamics and computational science. Hou received his B.S. in Mathematics from South China University of Technology in 1982, followed by an M.S. in 1985 and Ph.D. in 1987 from UCLA under the supervision of Prof. Bjorn Engquist. His academic journey includes positions at the Courant Institute and the Institute for Advanced Study before joining Caltech. Hou's research focuses on multiscale analysis and computation, interfacial problems, stochastic PDEs and uncertainty quantification, and the Millennium Problem concerning global regularity of 3D incompressible Euler and Navier-Stokes equations. His work on adaptive data analysis has led to significant methodological innovations. His research is characterized by the integration of rigorous mathematical analysis with computational approaches to tackle problems that have resisted traditional methods. His recent publications reveal a consistent focus on singularity formation in fluid equations, particularly the Euler and Navier-Stokes equations, with increasing sophistication in analyzing potential blowup scenarios. His work spans theoretical analysis, numerical verification, and the development of innovative mathematical frameworks for multiscale problems. Member of the National Academy of Sciences (2024) William Benter Prize in Applied Mathematics (2024) SIAM Ralph E. Kleinman Prize (2023) SIAM Outstanding Paper Prize (2018) Fellow of the American Mathematical Society (2012) Fellow of the American Academy of Arts and Sciences (2011) Hou has served in significant editorial roles including Founding Editor-in-Chief of the SIAM Journal on Multiscale Modeling and Simulation and Co-Editor-in-Chief of Research in Mathematical Sciences. His professional service includes membership on the SIAM Council and leadership roles at the Institute of Mathematics and its Applications. His research has been supported by numerous grants focusing on multiscale modeling, fluid dynamics, and computational mathematics.

Victor Beresnevichمشاهده پروفایل

استاد

• Metric Number Theory
• Diophantine Approximation
• Geometry of Numbers
• +۷ مورد دیگر

Professor Victor Beresnevich of the University of York, Department of Pure Mathematics, is a leading researcher in Metric Number Theory and Diophantine Approximation . He leads the Number Theory Research Group and collaborates on problems involving algebraic numbers , manifold approximation , and ergodic theory . PhD and DSc from Minsk EPSRC-funded projects on Duffin-Schaeffer conjecture and rational points near manifolds Organiser of conferences on Diophantine approximation, dynamical systems, and quantum chaos His work connects Diophantine approximation with dynamical systems , fractal geometry , and p-adic analysis . Recent projects focus on inhomogeneous approximation and shrink targets problems . He supervises PhD students and mentors collaborations in analytic number theory and measure theory . Scientific Awards : Advanced Research Fellow Current PhD Student : Dorsa Vakilzadeh Hatefi

Alexander Vladimirskyمشاهده پروفایل

استاد

• Numerical Analysis
• Applied Mathematics
• Nonlinear PDEs
• +۵ مورد دیگر

Roles & Affiliations: Professor of Mathematics at Cornell University, Department of Mathematics. Member of graduate programs in Mathematics, Applied Mathematics, Operations Research and Information Engineering, Theoretical & Applied Mechanics, and Computational Science & Engineering. Co-organizer of the Scientific Computing and Numerics (SCAN) Seminar and founder of the Cornell Mathematical Contest in Modeling. Education: Ph.D. in Applied Mathematics from University of California, Berkeley (2001); B.A. in Applied Mathematics (with high honors) from University of California, Berkeley (1995). Research Interests: Focuses on numerical analysis, nonlinear PDEs, control theory, and dynamical systems. Explores applications in optimal control, front propagation, anisotropy, bifurcation theory, and mathematical biology. Develops methods for invariant manifold approximation, Eikonal equations, and stochastic systems. Recent work includes studies on cancer therapy optimization, surveillance evasion, and pedestrian flow modeling. Teaching: Teaches courses like Introduction to Partial Differential Equations, Differential Games, Numerical Analysis, and Mathematical Modeling. Recent courses include Math 4280 (Spring 2025) and Math 3610 (Fall 2024). Labs/Teams: Active in interdisciplinary collaborations, including work on computational biology, robotics path planning, and mathematical contest problem-solving initiatives.

Julia Kempeمشاهده پروفایل

استاد

• Data Science
• Machine Learning
• Quantum Computing
• +۳ مورد دیگر

Julia Kempe is a Silver Professor of Computer Science, Mathematics, and Data Science at New York University (NYU), holding joint appointments at the Courant Institute and the Center for Data Science (CDS). She serves as Director of the CDS and is on research leave at the CSD, ENS, Paris (2023–24). Her expertise spans interdisciplinary research in quantum computing, machine learning, and data science. She holds PhDs in Mathematics (UC Berkeley, 2001) and Computer Science (École Nationale Supérieure des Télécommunications, Paris, 2001), alongside advanced degrees in theoretical physics and mathematics from prestigious institutions in France and Austria. Research Interests: Data Science, Machine Learning (theoretical foundations and applications to physics), and past contributions to quantum computing. She focuses on robustness in machine learning models, adversarial examples, and interdisciplinary applications of physics-informed AI. Awards and Honors: Knight of the National Order of Merit (France, 2010), Femme en Or de la Recherche (France, 2010), ERC Starting Grant (2007, top-ranked in Europe), and numerous academic fellowships. She is a member of Academia Europaea (2018) and a Fellow of the Asia-Pacific Artificial Intelligence Association (2022). Grants and Leadership: Principal investigator of NSF NRT grants for CDS PhD programs, co-PI on NASA TCAN grants, and leader in NYU’s Senior Leadership Team. She designed NYU’s Data Science undergraduate programs and expanded interdisciplinary collaborations in machine learning and quantum computing. Labs and Teams: Directs the CDS, collaborates with the Courant Institute, and leads research initiatives in Paris. Her work bridges theoretical computer science, physics, and applied data science, emphasizing interdisciplinary innovation.

• Media Economics
• Communication Science
• Digital Media Transformation
• +۳ مورد دیگر

Prof. Dr. M. Bjørn von Rimscha is a full-time Professor of Media Economics at the Department of Social Sciences, Media and Sport, Johannes Gutenberg University Mainz. He serves as Prodekan for Studium und Lehre since 2023 and previously held leadership roles including Geschäftsführender Leiter of the Institute for Journalism. His research focuses on media economics, digital transformation, advertising markets, and cross-border media management. Positions: Professor (2015–present), Prodekan (2023–present) Education: Freie Universität Berlin, University of Ulster Key Collaborations: Co-edited De Gruyter Handbook of Media Economics (2024), Handbuch Medienökonomie (2021) His recent work examines digital disruption in media industries, payment models for journalism, and the economic value of creativity. He advises PhD students like Robin Riemann and holds editorial roles at the Journal of Media Business Studies . Contact: b.vonrimscha@uni-mainz.de

• Conflict
• Group-based Antipathy
• Right-wing Extremism
• +۱۲ مورد دیگر

Prof. Dr. Andreas Zick is a leading scholar at Bielefeld University, serving as Scientific Director of the Institute for Interdisciplinary Conflict and Violence Research (IKG) and Professor for Socialization and Conflict Research at the Faculty of Education. He also co-leads the ConflictA initiative since 2023 and contributes to migration education through the Faculty of Education. 2008: Professor for Socialization and Conflict Research, Bielefeld University 2013: Director of IKG 2023: Scientific Head of ConflictA His research focuses on intergroup conflicts , group-based antipathy , right-wing extremism , radicalization , and socialization processes . He investigates spatial dimensions of radicalization, societal integration challenges, and prejudice dynamics through comparative studies. Recent publications analyze radicalization spaces (2024-2025) using spatial sociology, democratic conflict perceptions (2025), and cross-cultural prosocial behavior during pandemics. Key methods include ethnography, longitudinal surveys, and multi-perspective comparative analysis. Scientific contributions recognized by: Communicator Award (2016) Nevitt Sanford Lifetime Award (2022) Active in public policy as member of the Federal Agency for Civic Education's advisory board and Federal Commissioner's Antiracism Expert Council. Leads major projects on radicalization prevention and spatial conflict dynamics with national/international partners.

Joachim Weickertمشاهده پروفایل

استاد

• Image Processing
• Computer Vision
• Mathematical Modeling
• +۴ مورد دیگر

Joachim Weickert is a Professor of Mathematics and Computer Science at Saarland University where he heads the Mathematical Image Analysis Group since 2001. He received his diploma and Ph.D. in mathematics from the University of Kaiserslautern (1991, 1996), and a habilitation degree in computer science from the University of Mannheim (2001). Prior to his current position, he worked as a research assistant at the University of Kaiserslautern, as a post-doctoral researcher at the universities of Utrecht and Copenhagen, and as an assistant professor at the University of Mannheim. His research focuses on image processing, computer vision, and scientific computing, with special emphasis on techniques based on partial differential equations, variational principles, wavelets, morphological and nonlocal methods, as well as neuroexplicit approaches. He has developed mathematical models and efficient numerical algorithms for image restoration, enhancement, segmentation, compression, optic flow computation, stereo reconstruction, shape from shading, and signal processing methods for tensor fields. These ideas have been successfully applied in industry, biomedical image analysis, and other fields. Analysis of his recent publications reveals a strong trend toward combining traditional PDE-based methods with modern deep learning approaches, particularly in the areas of image inpainting and compression. His work increasingly explores the connections between numerical algorithms for partial differential equations and neural network architectures, demonstrating how mathematical foundations can inform cutting-edge AI techniques while maintaining strong theoretical guarantees. Gottfried Wilhelm Leibniz Prize (2010), considered the most important research award in Germany ERC Advanced Grant (2017) for "Inpainting-based Compression of Visual Data" Elected member of Academia Europaea - The Academy of Europe Jan Koenderink Prize for Fundamental Contributions in Computer Vision (2014) Multiple DAGM Prizes and Best Paper Awards throughout his career AAIA Fellow (2021) and Highly Ranked Scholar (2024) distinctions Professor Weickert has supervised over 250 bachelor's and master's theses and initiated the Master Programme in Visual Computing at Saarland University, the first of its kind in Germany taught in English. He has established numerous interdisciplinary collaborations with colleagues from medicine, bioinformatics, pharmacy, physics, mechatronics, and mechanical engineering. As Principal Investigator for Visual Computing within the Multimodal Computing and Interaction Cluster of Excellence, and former dean of the Faculty of Mathematics and Computer Science (2008-2010), he has played a significant leadership role in advancing visual computing research and education. He heads the Mathematical Image Analysis Group, which has been at the forefront of developing mathematical methods for image analysis. The group maintains strong connections with both theoretical mathematics and practical applications, bridging the gap between fundamental research and real-world implementation across various domains including medical imaging, industrial inspection, and multimedia processing.