جست‌وجوی استاد و پژوهشگر

Chris Peikertمشاهده پروفایل

استاد

• Cryptography
• Lattice-based Cryptography
• Coding Theory
• +۲ مورد دیگر

Chris Peikert is a Professor in the Department of Computer Science and Engineering at the University of Michigan's College of Engineering. He received his Ph.D. from MIT's Computer Science and Artificial Intelligence Laboratory in 2006 under the supervision of Silvio Micali. Peikert is a leading researcher in cryptography, particularly known for his foundational work in lattice-based cryptography. His research interests span cryptography, lattices, coding theory, algorithms, and computational complexity, with a particular focus on cryptographic schemes whose security can be based on the apparent intractability of lattice problems. Peikert has made significant contributions to the development and analysis of lattice-based cryptographic primitives, including ring-LWE, fully homomorphic encryption, and zero-knowledge proofs. Peikert's recent work demonstrates continued leadership in post-quantum cryptography, with publications in top venues like CRYPTO, EUROCRYPT, and STOC. His research spans theoretical foundations of lattice problems to practical implementations of lattice-based cryptographic systems, including hardware acceleration for fully homomorphic encryption. IACR Fellow (2024) Test-of-Time Award from Crypto 2008 (2023) TCC Test-of-Time Award (2017) Patrick C. Fischer Development Professor of Theoretical Computer Science (2017) Best Paper Award at Eurocrypt 2010 Best Paper Award at STOC 2009 Alfred P. Sloan Foundation Fellowship Google Research Award Peikert has been actively involved in the cryptographic research community, serving on program committees for major conferences including CRYPTO, EUROCRYPT, FOCS, and TCC (where he was program co-chair in 2021). He has also developed educational resources, including extensive lecture materials on lattice-based cryptography and teaching courses on cryptography and theoretical computer science at both the undergraduate and graduate levels.

Anna Wienhardمشاهده پروفایل

استاد

• Discrete Subgroups of Lie Groups
• Deformation Spaces of Geometric Structures
• Representation Varieties
• +۶ مورد دیگر

Prof. Anna Wienhard holds the position of Professor at the Mathematical Institute of Heidelberg University since 2012, where she leads the Differential Geometry research group. She is also Scientific Director of the Research Station Geometry and Dynamics (since 2020) and Co-Spokesperson of the Excellence Cluster STRUCTURES (since 2019). She serves as a Group Leader at the Heidelberg Institute for Theoretical Studies (HITS) since 2015 and chairs the Heidelberg Laureate Forum Foundation. Her roles include editorships for journals like Annales Henri Lebesgue, Annales scientifiques de l'Ecole Normale Supérieure, and Geometric and Functional Analysis. Anna Wienhard earned dual degrees in theology and mathematics from the University of Bonn (2003/2004). After a theological research phase supported by the CRC 'Judaism – Christianity', she completed her PhD in mathematics at the University of Bonn in 2004. She held positions as a Dickson Instructor at the University of Chicago (2005–2007), postdoctoral research at the Institute for Advanced Study (IAS) in Princeton (2005–2006, 2009–2012), and was an Assistant Professor at Princeton University (2007–2012). She also served as Director of Graduate Studies at Princeton (2007–2010). Her research focuses on discrete subgroups of Lie groups , deformation spaces , representation varieties , Anosov representations , higher Teichmüller theory , and positivity in Lie groups . She explores these areas with interdisciplinary applications in physics and data science. Notable projects include the ERC Consolidator Grant (2014) and leadership in the DFG Excellence Cluster 2181 and Graduiertenkolleg 2229. Her work has been recognized through awards such as the Sloan Research Fellowship (2012–2014) and Fellow of the American Mathematical Society . She has organized workshops on topics like Ergodic Decompositions, Flat Conformal Lorentzian Structures, and Ratner's Theorem. Her grants span DFG-funded initiatives and international collaborations, including the GEAR Network and MSRI programs. She is actively involved in editorial roles, academic committees, and interdisciplinary research activities. Prof. Wienhard advises doctoral candidates and oversees research groups. She collaborates with institutions such as the IAS, Technical Universities in Munich and Ingolstadt, and the Berlin-Brandenburg Academy of Sciences. Her research group at Heidelberg University specializes in differential geometry, and she contributes to the Excellence Cluster’s unifying approach to emergent phenomena across mathematics and physics.

Simon Masnouمشاهده پروفایل

استاد

• Applied Mathematics
• Image Processing
• Shape Optimization
• +۵ مورد دیگر

Simon Masnou is a Full Professor at Université Claude Bernard Lyon 1, affiliated with the Institut Camille Jordan (CNRS UMR 5208). He holds leadership roles as Head of the 'Applied Mathematics, Statistics' Master's degree and Head of the 'M2 Maths in Action' program. Previously, he served as Director of the Camille Jordan Institute (2018-2022). His research focuses on applied mathematics, image processing, shape optimization, and geometric measure theory, with contributions to variational models, geometric flows, and applications in computer vision and materials science. Education: PhD in Mathematics (1998, Paris Dauphine) and HDR (2008, Paris 6). Research projects include ANR STOIQUES (2024-2028), PEPR PDE-AI (2023-2028), and collaborations with industry on topics like defect prediction in aluminum production and high-dimensional data analysis. Teaching includes courses on linear algebra, optimization, and machine learning at undergraduate and graduate levels. Key contributions span phase field models, varifold-based surface approximation, and image inpainting. He supervises PhD students in geometric variational problems and computational methods. His work bridges theoretical mathematics with industrial challenges, addressing issues in materials science, medical imaging, and cultural heritage preservation.

• Machine Learning
• Data-Driven Modeling
• Numerical Solutions of Partial Differential Equations
• +۵ مورد دیگر

Kailiang Wu is an Associate Professor at the Department of Mathematics, Southern University of Science and Technology (SUSTech), and holds concurrent roles at the Shenzhen International Center for Mathematics and National Center for Applied Mathematics Shenzhen. His research bridges Machine Learning and Computational Fluid Dynamics , focusing on High-Order Numerical Methods for Hyperbolic Conservation Laws and Relativistic Astrophysics . Education: Ph.D. in Mathematics (Peking University, 2016), B.Sc. in Mathematics and Statistics (Huazhong University of Science and Technology, 2011) His work develops Structure-Preserving Schemes for multidimensional PDEs, including Oscillation-Eliminating Discontinuous Galerkin (OEDG) and Geometric Quasilinearization (GQL) frameworks. These methods ensure positivity , divergence-free , and bound-preservation in simulations of relativistic flows and MHD systems. Recent publications emphasize Deep Learning applications in operator learning (e.g., DUE framework) and Data-Driven Modeling of unknown PDEs. His group has produced 20+ peer-reviewed articles in top journals (Math. Comp., SIAM J. Numer. Anal., JCP) since 2014. Honors: SUSTech President's Research Award (2025) World's Top 2% Scientist (2024) NSFC Major Program (2023, 0.7M CNY) Shenzhen Distinguished Young Scholar (2023, 4M CNY) National Excellent Young Scholar Program (2020, 2M CNY) Zhong Jiaqing Mathematics Award (2019) He advises 10+ graduate students and postdocs, with alumni securing academic positions at Sun Yat-sen University and HKUST. His lab collaborates on relativistic hydrodynamics , traffic models , and uncertainty quantification , supported by competitive funding.

Yuan Gaoمشاهده پروفایل

استادیار

• Partial Differential Equations
• Computational and Applied Mathematics
• Stochastic Analysis
• +۷ مورد دیگر

Yuan Gao is an Assistant Professor of Mathematics at Purdue University's Department of Mathematics (College of Science). His research focuses on analysis and computations of PDEs in materials science, biology, and microfluidics, with recent emphasis on optimal control, Hamilton-Jacobi equations, and non-equilibrium chemical reactions. His work is supported by NSF awards DMS-2204288 and DMS-2440651. Previously, he held the William W. Elliott Assistant Research Professor position at Duke University (2019-2021). Research interests include PDE analysis in materials science (crystal growth, dislocation dynamics), numerical methods for interface dynamics, applied stochastic analysis (Langevin dynamics, transition path theory), and mean-field games for fluid systems. He organizes the PSU-Purdue-UMD Joint Seminar on Mathematical Data Science. Key publications span topics like dislocation evolution, Wasserstein gradient flows, and stochastic algorithms for rare events. Awards include NSF CAREER funding recognizing his contributions to mathematical analysis of non-equilibrium systems.

• Computational Fluid Dynamics
• Discontinuous Galerkin Methods
• Finite Volume Methods
• +۶ مورد دیگر

Michael Dumbser is a Full Professor at the University of Trento's Department of Civil, Environmental and Mechanical Engineering. His research focuses on computational fluid dynamics, numerical methods for hyperbolic conservation laws, and high-performance computing. He specializes in developing structure-preserving numerical schemes such as discontinuous Galerkin and finite volume methods for continuum mechanics, relativistic fluid dynamics, and multiphase flows. Teaching responsibilities include courses like Calcolo numerico e programmazione , High-Performance Computing for Multi-Functional Metamaterials , and Metodi numerici per l'ambiente . His work emphasizes thermodynamically compatible formulations and adaptive numerical methods for complex physical systems. Recent research trends involve hyperbolic reformulations of classical models (e.g., Navier-Stokes-Korteweg, Einstein equations), staggered semi-implicit schemes for incompressible flows, and GPU-accelerated algorithms. His publications span topics from geophysical fluid dynamics to relativistic astrophysics, with a focus on maintaining physical conservation principles in numerical implementations. No scientific awards are explicitly listed in the provided information. His advising record is not detailed here, though his courses suggest involvement in student mentorship. Research collaborations include projects on metamaterials and computational geophysics. Current initiatives include developing unified models for earthquake rupture dynamics, non-Newtonian fluid simulations, and adaptive mesh refinement techniques. His lab work involves high-performance computing frameworks like ExaHyPE for large-scale wave propagation studies.

Anil N. Hiraniمشاهده پروفایل

استاد

• Differential Equations
• Numerical Analysis
• Computational Topology
• +۵ مورد دیگر

Anil N. Hirani is a Professor in the Department of Mathematics at the University of Illinois at Urbana-Champaign (UIUC), affiliated with the College of Liberal Arts & Sciences. He holds a PhD from the California Institute of Technology (2003) in Computer Science with minors in Mathematics and Control and Dynamical Systems. His academic journey includes roles as Assistant Professor (Computer Science, UIUC, 2005–2013) and Associate Professor (Mathematics, UIUC, 2013–2022) before becoming a full Professor in 2022. His research focuses on the interplay between geometry/topology and algorithms, with emphasis on structure-preserving discretizations of exterior calculus and differential geometry. Key areas include Discrete Exterior Calculus (DEC), numerical methods for PDEs, computational topology, and machine learning applications. He has organized workshops, such as the 2025 Discrete Exterior Calculus workshop at IMSI, and contributed to software like PyDEC. Education: PhD, Caltech (2003); MS in Computer Science (Stanford); Undergraduate degree in Computer Science (BITS Pilani, India). Awards include the NSF CAREER Award (2007–2012). Teaching includes courses on Differential Geometry (MATH 423), Vector and Tensor Analysis (MATH 481), and Computational Mathematics (MATH 490). He has advised numerous PhD students, notable among them Kaushik Kalyanaraman and Vaibhav Karve. Articles span DEC applications in fluid dynamics, cohomology computations, and machine learning. His work bridges theoretical foundations with practical applications in engineering and computer science.

Werner Bauerمشاهده پروفایل

مدرس

• Numerical Analysis
• Scientific Computing
• Fluid Dynamics
• +۵ مورد دیگر

Dr. Werner Bauer is a Lecturer in Mathematics at the University of Surrey, affiliated with the Mathematics at the Interface Group within the School of Mathematics and Physics. His research focuses on numerical analysis and scientific computing, particularly in the Mathematics of Planet Earth. Key areas include parallel-in-time methods for oscillatory PDEs, structure-preserving discretizations for fluid dynamics, stochastic flow models for ensemble prediction, and geometric formulations of fluid and magnetohydrodynamic systems. He also explores finite difference and finite element methods, with prior work on grid adaptation in weather and climate models. His research interests span numerical methods for geophysical flows, stochastic modeling of oceanic and atmospheric dynamics, and energy-conserving computational frameworks. Bauer’s recent work emphasizes uncertainty quantification, ensemble forecasting, and the development of compatible finite element schemes to ensure physical conservation laws in simulations. Bauer’s publications highlight advancements in structure-preserving discretizations, stochastic parameterization of mesoscale eddies, and variational integrators for geophysical equations. His work bridges applied mathematics and computational science with applications in climate modeling and environmental fluid dynamics.

Mark Ainsworthمشاهده پروفایل

استاد

• Numerical Approximation of Partial Differential Equations
• A Posteriori Error Estimation
• High Order Finite Element Methods
• +۵ مورد دیگر

Mark Ainsworth is a Francis Wayland Professor of Applied Mathematics at Brown University and holds a joint faculty appointment with Oak Ridge National Laboratory. He obtained his PhD from Durham University (1989) and has held prominent roles such as Director of the Centre for Numerical Algorithms and Intelligent Software (2011-2012). His research focuses on numerical analysis, particularly finite element methods for partial differential equations, a posteriori error estimation, and high-performance computing challenges like resiliency on exascale systems. Education: PhD in Mathematics, Durham University, 1989 BSc in Mathematics, Durham University, 1986 Research Interests: Numerical approximation of PDEs A posteriori error estimation and adaptive methods High order finite element methods Resiliency of numerical algorithms on emerging architectures Fractional PDEs and scientific data compression Awards: SIAM Fellow (2014) FIMA (2010) Whitehead Prize (2004) J.L. Lions Prize (2004) Fellow of Royal Society of Edinburgh (2003) Grants & Leadership: Co-PI for ARO MURI on fractional PDEs (2015-2020) Directed NAIS center (2011-2012), a £5M multi-institutional initiative Organized major international conferences on computational mathematics Labs/Teams: Collaborations include Oak Ridge National Lab and international research networks in numerical analysis and scientific computing.

• Quantum Topology
• Low-Dimensional Topology
• Hyperbolic Geometry
• +۳ مورد دیگر

Dr. Tian Yang is an Associate Professor in the Department of Mathematics at Texas A&M University , part of the College of Arts & Sciences . His research focuses on Quantum Topology, Hyperbolic Geometry, and Low-Dimensional Topology , with significant contributions to the study of quantum invariants, Turaev-Viro invariants, and geometric structures of 3-manifolds. Education & Professional Background: While specific degree details are not explicitly provided, his academic trajectory is reflected through extensive involvement in global research collaborations and teaching roles at Texas A&M. He has taught specialized courses like Quantum Topology and Geometric Topology . Research Interests: Dr. Yang’s work bridges algebraic and geometric topology, emphasizing: Quantum Invariants: Analysis of Turaev-Viro and Reshetikhin-Turaev invariants, their asymptotic behavior, and connections to hyperbolic volume. Hyperbolic Geometry: Investigations into hyperbolic polyhedral manifolds, cone metrics, and geometric rigidity. Topological Dynamics: Exploring surface diffeomorphism groups and their quantum invariant asymptotics. Publications: His recent work includes groundbreaking studies on the Volume Conjecture , asymptotics of 6j-symbols, and geometric-topological applications of quantum field theory. Key papers appear in Advances in Mathematics , Journal of Differential Geometry , and Communications in Mathematical Physics . Professional Engagement: He has delivered over 50 invited lectures globally, including at the International Congress of Basic Science (2025) and the Banff International Research Station . His research has been supported through collaborations with institutions like the Chern Institute of Mathematics and the Mathematical Sciences Center at Tsinghua University. Teaching & Mentorship: While specific student advisees are not listed, his courses reflect advanced topics in topology and geometry. He has organized summer schools and workshops in China and the U.S., fostering global academic exchange.

Werner Ballmannمشاهده پروفایل

استاد

• Differential Geometry
• Geometric Analysis
• Nonpositive Curvature
• +۳ مورد دیگر

Werner Ballmann is a renowned mathematician specializing in differential geometry and geometric analysis. He served as Full Professor at the University of Bonn (1989–2016) and the University of Zürich (1987–1989). Since 2007, he has been a Scientific Member and Director of the Max Planck Institute for Mathematics (2007–2019). His research focuses on nonpositive curvature, spectral theory, and geometric structures on manifolds. Ballmann holds a Diplom (1976) and Promotion (1979) from the University of Bonn, with a Habilitation in 1984. His work includes groundbreaking studies on the geometry of manifolds, hyperbolic spaces, and orbifolds. Recent articles address spectral instability, eigenvalue analysis, and stochastic processes on geometric structures. Notable contributions include investigations into Martin boundaries, diffusion discretizations, and the interplay between geometry and spectral properties. Ballmann has authored influential textbooks such as Lectures on Kähler Manifolds (2006) and Introduction to Geometry and Topology (2018). His research bridges geometric analysis, topology, and probability, with applications in manifold theory and group actions.

Aleksandra Slavkovicمشاهده پروفایل

استاد

• Statistical Data Privacy
• Differential Privacy
• Algebraic Statistics
• +۵ مورد دیگر

Aleksandra Slavković is a Professor of Statistics and Associate Dean for Graduate Education at Pennsylvania State University's Eberly College of Science. She holds a PhD in Statistics from Carnegie Mellon University (2004) and has held academic roles since 2004, including appointments at the Institute for Computational and Data Sciences and Penn State College of Medicine. Her research focuses on statistical data privacy, differential privacy, algebraic statistics, and applications in social and health sciences. She has authored over 50 peer-reviewed publications and serves on editorial boards of top journals like Journal of Privacy and Confidentiality and Annals of Applied Statistics . Slavković has received major honors including Fellowships from the Institute of Mathematical Statistics (2021) and American Statistical Association (2018). She leads initiatives to enhance graduate education, including the Science Achievement Graduate Fellows Program, and actively promotes diversity in STEM through her leadership roles. Her recent work emphasizes privacy-preserving techniques for genomic, healthcare, and network data, with contributions to synthetic data generation and secure multiparty computation protocols. Her academic service includes chairing ASA committees and advising at the National Academy of Sciences. She maintains collaborative ties with institutions like Cornell University and UC Berkeley through visiting scholar programs, and her research bridges statistics, computer science, and applied mathematics.

• Dynamical Systems
• Geometry
• Teichmüller Theory
• +۴ مورد دیگر

W. Patrick Hooper serves as Professor, Chair, and Majors Advisor in the Department of Mathematics at City College of New York, part of the City University of New York system. He maintains a dual appointment as Math Doctoral Faculty at the CUNY Graduate Center, where he holds office in Room 4217.02 and can be reached at 212-817-8567. Hooper completed his undergraduate studies in mathematics at the University of Maryland, where he participated in the Experimental Geometry Lab. He earned his PhD in 2006 from Stony Brook University under Yair Minsky, focusing on billiards in polygons and their connections to Teichmüller theory. Following approximately three years as a Boas Assistant Professor at Northwestern University, he joined City College in spring 2010. His research centers on dynamical systems defined by piecewise continuous maps that preserve geometric structure away from discontinuities. By studying piecewise continuous isometries, Hooper explores richer classes of dynamical systems that reveal novel phenomena beyond the constraints of continuous isometry groups. His work frequently connects to geometry through interval exchange maps and their relationship to Teichmüller theory, examining how discretization creates new dynamical behaviors bridging geometric and dynamical perspectives. Analysis of Hooper's publication record shows consistent advancement in understanding infinite translation surfaces and their ergodic properties, with recent work extending to prism geometries and stellar foliation structures. His research demonstrates increasing sophistication in connecting abstract dynamical systems to concrete geometric constructions, particularly through the lens of cube surfaces and periodic structures. Professor Hooper has mentored students including Kadar He, who recently advanced to the PhD program at CUNY's Graduate Center. His research has been presented at numerous international conferences including at the Hausdorff Institute in Bonn, Germany, and the Fields Institute in Toronto. The IT-ROCS REU program at CCNY, mentioned in August 2025 news, likely represents current undergraduate research initiatives he oversees. His mathematical image gallery showcases the visual dimension of his research, featuring eigenfunction curves, quasi-periodic truchet tilings, and the Necker cube surface, demonstrating how geometric visualization informs his theoretical work in dynamical systems.

Lina von Sydowمشاهده پروفایل

استاد

• Computational Science
• Computational Finance
• Ice Sheet Modeling
• +۲ مورد دیگر

Lina von Sydow is a Professor in Computational Science at Uppsala University's Department of Information Technology. She serves as Section Dean for the Mathematical-Computer Science Section since July 2023. Her academic journey includes becoming an Associate Professor in 2000, Senior Lecturer since 1997, and leading the Department of Information Technology from 2018 to 2023. PhD in Domain Decomposition Methods (1995, Uppsala University) Postdoctoral Fellow at Oxford University (1996-1997) Her research spans computational science with dual focuses on Computational Finance and Ice Sheet Modeling . In finance, she develops numerical methods for option pricing using PDEs, radial basis functions, and stochastic volatility models. In climate science, she contributes to ice sheet dynamics through full Stokes models and adaptive time-stepping approaches, particularly in simulating grounding line migration. Recent publications (2025) address gender disparities in IT education, including comparative analysis of admission trends and intervention studies to boost female enrollment. Earlier works (2020-2015) focus on high-order finite difference methods for financial derivatives, BENCHOP benchmarking projects, and preconditioning techniques for PDEs. Scientific awards include Excellent Teacher (2013) She actively collaborates on educational reforms, co-authoring studies like Gender-aware course reform in Scientific Computing (2013). Her leadership roles include Head of Department (2018-2023) and Section Dean (2023-present), influencing academic governance and interdisciplinary research. Labs and teams: Works with Uppsala University's Computational Science group, Elmer/ICE project collaborators (e.g., Per Lötstedt, Gong Cheng), and international partners in numerical finance and climate modeling.

François Le Maîtreمشاهده پروفایل

استاد

• Ergodic Theory
• Topological Dynamics
• Group Theory
• +۷ مورد دیگر

François Le Maître is a Professor of Mathematics at the Burgundy Institute of Mathematics (IMB) within the GADT team. He teaches at Polytech Dijon (formerly ESIREM) and was previously a Lecturer at IMJ-PRG in the AO team. His research spans ergodic theory, topological dynamics, group theory, and operator algebras. Research Interests : Orbit equivalence, full groups, Polish groups, measure-preserving actions, geometric group theory, and descriptive set theory. His recent publications focus on L1 full groups, high transitivity in tree actions, quantitative measure equivalence, and topological properties of Polish groups. He has supervised M2 internships and co-supervises ongoing PhD theses, including work on orbit equivalence, Boolean actions, and commensurating symmetric groups. Notable Events : Co-organizer of the 2025 CIRM conference on orbit equivalence, IMJ-PRG Summer School on groupoids, and past workshops on operator algebras and Polish groups.