جست‌وجوی استاد و پژوهشگر

• Differential Geometry
• Algebraic Topology
• Critical Point Theory
• +۳ مورد دیگر

Cornel Pintea is an Associate Professor at the Department of Geometry within the Faculty of Mathematics and Computer Science at Babeş-Bolyai University, Cluj-Napoca, Romania. His academic journey includes a B.Sc. and Ph.D. from Babeş-Bolyai University and West University of Timişoara, respectively. He has held postdoctoral fellowships in France and Poland under EU-supported networks in Geometric Analysis. His research focuses on differential geometry, topology, critical point theory, and convex analysis. He has authored several textbooks and contributed to peer-reviewed journals. Pintea is a member of the Romanian Mathematical Society and the Balkan Society of Geometers. Education: B.Sc. (1991): Babeş-Bolyai University, Mathematics Ph.D. (1996): West University of Timişoara, Mathematics Research Interests: Pintea’s work spans critical point theory, differential geometry, convex geometry, and operator monotonicity. He has explored global injectivity conditions, topological criticality, and manifold mappings. His recent studies include convex decompositions, generalized monotone operators, and properties of closed convex sets. His contributions address foundational problems in geometric analysis and nonlinear functional analysis. Professional Activities: Pintea has participated in multiple research projects, including the EU-funded Geometric Analysis Network (2000–2004) and national initiatives on variational problems and equilibrium theory. His teaching spans algebraic topology, differential geometry, and linear algebra. Labs/Teams: Collaborations include work with Prof. G. Kassay on monotone operators and with Prof. M. Kohr on boundary value problems. His research often intersects with geometric analysis and applied mathematics.

• Fluid Mechanics
• Machine Learning
• Chaotic Systems
• +۳ مورد دیگر

Luca Magri is a Reader in Data-Driven Fluid Mechanics at Imperial College London's Department of Aeronautics. He holds affiliations as a Fellow of The Alan Turing Institute and a Hans Fischer Fellow at the Technical University of Munich (TUM). His research focuses on physics-constrained machine learning, chaotic systems, and fluid mechanics. Magri’s work bridges computational methods with fluid dynamics, addressing challenges in turbulence, combustion, and acoustics through innovative approaches like reservoir computing and adjoint-based optimization. Education & Career PhD in Engineering, University of Cambridge (2015) Postdoctoral Fellow, Stanford University Center for Turbulence Research (2015–2017) Lecturer at Cambridge University Engineering Department (2017–2018) Current: Reader at Imperial College London since 2018 Research Interests Magri’s research integrates machine learning with fluid dynamics to model chaotic systems, optimize combustion processes, and analyze turbulence. Key areas include: Physics-informed neural networks for extreme event prediction Adjoint-based methods for thermoacoustic stability Bayesian data assimilation in nonlinear systems Publications & Awards His impactful work has been recognized with awards such as the ERC Starting Grant (2019), Royal Aeronautical Society Fellowship (2022), and multiple fellowships from Stanford and Cambridge. Over 50 publications span journals like Journal of Fluid Mechanics and Proceedings of the Royal Society A . Grants & Collaborations Magri leads projects funded by the EU Horizon 2020, UKRI, and the ERC. He collaborates globally, including with TUM’s Institute for Advanced Study and Cambridge’s Engineering Department.

Robert Altmannمشاهده پروفایل

استاد

• Partial Differential Algebraic Equations
• Poroelastic Equations
• Dynamic Boundary Conditions
• +۴ مورد دیگر

Prof. Robert Altmann is a Professor of Numerical Mathematics at the Otto von Guericke University Magdeburg, leading the Institute for Analysis and Numerical Analysis (IAN). He holds a PhD from TU Berlin and has held academic positions at institutions including the University of Augsburg and TU Berlin. His research focuses on numerical methods for partial differential equations, particularly PDAEs, poroelasticity, dynamic boundary conditions, and energy-based modeling frameworks like port-Hamiltonian systems. Education and Career: Bachelor's/Master's in Mathematics, Humboldt University Berlin (2007–2011) Research Stay at École des Ponts ParisTech (2011) Research Associate at TU Berlin (2011–2017) Academic Councillor at University of Augsburg (2017–2023) Research Interests: His work emphasizes numerical analysis for complex systems, including: Development of robust discretization schemes for PDAEs and poroelastic networks Energy-preserving methods for dynamic boundary value problems Riemannian optimization techniques for quantum systems Model reduction and multiscale methods for heterogeneous materials Grants and Projects: DFG Project: Decoupled computational methods for nonlinear parabolic problems (2020–2023) DFG Project: Higher-order decoupling integration schemes for poroelastic networks (2021–2024) DFG Project: Wave-type problems with non-standard boundary conditions (2024–2026) Awards and Recognition: Member of GAMM Juniors (2014) Dr.-Klaus-Körper Prize (GAMM, 2016) 2nd Tiburtius Prize (Berlin Universities, 2016) Team and Collaborations: His research group includes Dr. Afsaneh Moradi, Dr. Riccardo Morandin, and Jochewed Schmeck, focusing on computational methods for coupled systems and energy-based modeling.

Izaak Neriمشاهده پروفایل

مدرس ارشد

• Statistical Mechanics
• Biological Physics
• Non-Equilibrium Thermodynamics
• +۷ مورد دیگر

Dr. Izaak Neri is a Senior Lecturer in Disordered Systems at the Department of Mathematics, King's College London, within the Faculty of Natural, Mathematical & Engineering Sciences. He obtained his PhD in Theoretical Physics from KU Leuven (2010) and held postdoctoral positions at the University of Montpellier, and the Max Planck Institutes for Molecular Cell Biology and Genetics and Physics of Complex Systems. His research focuses on statistical physics, mathematical physics, and biological physics, particularly non-equilibrium thermodynamics, sparse non-Hermitian random matrices, and network dynamics. He explores phase separation in biological systems, spin glass theory, and ecosystem stability using tools from statistical mechanics and stochastic processes. Education: PhD in Theoretical Physics (KU Leuven, 2010), MSc in Physics (Ghent University, 2005) Awards: APS Outstanding Referee (2020), Irwin Oppenheim Award (2024) Key Research Themes: Complex networks, random matrices, biological physics, nonequilibrium systems His work bridges theoretical frameworks and applications, such as modeling cytoskeletal transport and analyzing entropy production in Markov processes. He contributes to understanding how network structure influences dynamical systems and develops methods for studying large sparse systems. Current projects include phase separation in multicomponent biological mixtures and stability analysis of predator-prey networks.

Beatrice Pelloniمشاهده پروفایل

استاد

• Partial Differential Equations
• Nonlinear Problems
• Boundary Value Problems
• +۳ مورد دیگر

Beatrice Pelloni is a Professor in the School of Mathematical & Computer Sciences at Heriot-Watt University, specializing in the Department of Mathematics. Her research focuses on partial differential equations (PDEs), integrable systems, and nonlinear phenomena, with contributions to boundary value problems, dispersive equations, and applications in geophysical fluid dynamics. She has pioneered methods for solving evolution PDEs using the Fokas transform, and her work bridges theoretical analysis with computational techniques. Her research interests include integrable systems, dispersive wave equations, and mathematical physics, with particular emphasis on revivals in PDE solutions and optimal transport methods. She has collaborated internationally, contributing to the European Mathematical Society Young Academy (EMYA) and advancing collaborative research in applied mathematics. Pelloni's recent work explores revival phenomena in linear and nonlinear dispersive equations, periodic boundary conditions, and the application of geometric methods to atmospheric models like the Eady slice equations. Her articles span theoretical developments and numerical implementations, emphasizing interdisciplinary impact in fluid dynamics and mathematical physics. Her contributions have been recognized through editorial roles in journals and conference proceedings, reflecting her leadership in advancing the study of boundary value problems and integrable systems.

Fan Weiمشاهده پروفایل

استادیار

• Extremal Combinatorics
• Probabilistic Combinatorics
• Theoretical Computer Science
• +۳ مورد دیگر

Fan Wei is an Assistant Professor of Mathematics and Computer Science at Duke University, affiliated with the Trinity College of Arts & Sciences. She holds a PhD in Mathematics from Stanford University (2019), a Master of Advanced Study from Cambridge University (UK), and a Bachelor's degree from MIT. Her research focuses on extremal and probabilistic combinatorics, with applications to computer science, particularly in analyzing large networks using tools from probability, analysis, and algebra. Education: PhD in Mathematics, Stanford University, 2019 Master of Advanced Study, Mathematics, University of Cambridge, UK Bachelor's degree in Mathematics, MIT Research Interests: Extremal combinatorics, probabilistic combinatorics, graph theory, theoretical computer science, and applications to network analysis. Recent work includes studies on undecidability in graph homomorphism densities, independent transversals, and irregularity strength conjectures. Publications: Her work spans over 30 peer-reviewed articles, focusing on graph theory, combinatorial optimization, and algorithmic applications. Notable topics include undecidability in combinatorial problems, spectral graph theory, and phase transitions in graph properties. Awards & Funding: NSF Award DMS-2401414 (2023–2028) NSF Award DMS-1953958 (2020–2023) Simons Foundation Algorithms & Geometry Unit Fellowship (2020) Teaching & Mentoring: Teaches combinatorics courses at Duke, leads a research group, and mentors students in REU programs. Previously taught discrete mathematics and calculus. Labs/Teams: Active in Duke's combinatorics research community, collaborates internationally on projects such as the Barbados Graph Theory Workshop. Hosts a minicourse on regularity methods in combinatorics.

Andrea Bonitoمشاهده پروفایل

استاد

• Numerical Analysis
• Partial Differential Equations
• Adaptive Finite Element Methods
• +۳ مورد دیگر

Andrea Bonito is a Professor in the Department of Mathematics at Texas A&M University, affiliated with the College of Arts and Sciences. His research focuses on numerical methods for partial differential equations (PDEs), including adaptive finite element methods, free boundary problems, geometric PDEs, and non-Newtonian fluid dynamics. He explores topics like finite element approximations of thin structures, fractional operators, and optimal learning algorithms. His work emphasizes applications in material science and fluid dynamics, such as modeling bilayer plates, folding mechanics, and electroconvection of thin liquid crystals. Recent contributions include advancements in PINNs (Physics-Informed Neural Networks) for elliptic PDEs and gamma-convergent methods for large deformations. Bonito’s research bridges theoretical analysis with computational implementation, addressing challenges in high-dimensional approximation and incomplete information scenarios. His academic output spans over two decades, with notable publications on geometric PDEs, spectral fractional diffusion, and adaptive methods for elliptic problems. Bonito collaborates on interdisciplinary projects, leveraging numerical analysis to solve complex physical phenomena.

Klaus Neymeyrمشاهده پروفایل

استاد

• Numerical Analysis
• Linear Algebra
• Chemometrics
• +۳ مورد دیگر

Prof. Dr. Klaus Neymeyr is a Professor of Numerical Mathematics at the University of Rostock, affiliated with the Faculty of Mathematics and Natural Sciences and the Institute of Mathematics. Since 2023, he serves as Prodekan of the faculty. Previously, he was Dean (2014–2023) and an associated member at the Leibniz Institute for Catalysis (LIKAT). He obtained his habilitation in mathematics at the University of Tübingen (2001) and has held academic roles since 2003. His research spans numerical linear algebra, chemometrics, and catalysis, with a focus on eigenvalue problems, multivariate curve resolution (MCR), and spectral data analysis. Notable contributions include advancements in preconditioned eigensolvers and the development of FAC-PACK for feasible solution computation. Neymeyr’s work integrates computational methods with chemical applications, such as catalyst characterization via FTIR and NMR spectroscopy. He has been recognized with awards including the Kowalski Prize (2016) and a highly cited paper designation by ISI (2003). His collaborations extend to interdisciplinary projects in catalysis and biopharmaceutical data analysis. Publications emphasize algorithm development, convergence analysis, and data-driven methodologies. Scientific achievements include patents on energy-optimized pump regulation and contributions to the theoretical foundations of MCR and eigensolver convergence. His research group actively publishes in top journals like SIAM Journal on Matrix Analysis , Analytica Chimica Acta , and Journal of Chemometrics .

Alexander Pushnitskiمشاهده پروفایل

استاد

• Spectral Theory
• Operator Theory
• Hankel and Toeplitz Operators
• +۳ مورد دیگر

Professor Alexander Pushnitski is a Professor of Analysis in the Department of Mathematics at King's College London. He earned his PhD from St. Petersburg State University in 1998 under M.Sh.Birman. His career includes roles at Sussex University (postdoc, 1999–2005), Loughborough University (Lecturer, 1999–2005), and King's College London since 2005. He held a Leverhulme Research Fellowship at Caltech (2005/06) and received the London Mathematical Society's Whitehead Prize (2011). His research focuses on spectral theory, operator theory, and scattering theory, with notable work on Hankel/Toeplitz operators and inverse spectral problems. Education: PhD in Mathematics, St. Petersburg State University (1998) Positions: Professor at King's College London (2015–present), Reader (2011–2015), Lecturer at Loughborough University (1999–2005) Awards: Whitehead Prize (2011), Leverhulme Trust Fellowship (2005) Research Interests: Spectral theory of operators, inverse spectral problems, Hankel and Toeplitz operators, scattering theory, Schrödinger operators. His work explores eigenvalue asymptotics, operator perturbations, and spectral analysis in mathematical physics. Publications: Over 70 peer-reviewed articles, including recent contributions on spectral asymptotics, inverse problems for Hankel operators, and the cubic Szegő equation. His research bridges operator theory and mathematical physics, with applications to matrix analysis and functional equations. Grants & Supervision: Supervised two PhD students and one postdoc. Led projects funded by EPSRC and Leverhulme Trust, focusing on spectral theory and inverse problems.

Jose Israel Rodriguezمشاهده پروفایل

استادیار

• Applied Algebraic Geometry
• Algebraic Statistics
• Nonlinear Algebra
• +۵ مورد دیگر

Jose Israel Rodriguez is an Assistant Professor in the Department of Mathematics at the University of Wisconsin-Madison, with secondary affiliations at the Institute for Foundations of Data Science and the Department of Electrical & Computer Engineering. He began his tenure-track position at UW Madison in Fall 2020 after serving as an NSF Postdoc with Jon Hauenstein and a Provost's Postdoctoral Scholar at the University of Chicago with Lek-Heng Lim. PhD in Mathematics from University of California, Berkeley (supervised by Bernd Sturmfels) Bachelor's degree from University of Texas at Austin (McNair Scholar) Dr. Rodriguez's research focuses on applied algebraic geometry, particularly in algebraic statistics, optimization, and engineering applications. His work bridges theoretical mathematics with practical problems in statistics, robotics, and data science. He is known for developing methods to compute Euclidean distance degrees and maximum likelihood degrees, and for applying multidegrees to solve polynomial systems in economics and kinematics. His recent publications reveal a strong focus on singularity theory applications, numerical algebraic geometry methods, and interdisciplinary collaborations. The research shows increasing emphasis on practical applications in robotics, computer vision, and systems biology, while maintaining strong theoretical foundations in algebraic geometry. Sloan Fellowship (2023) Nellie McKay Fellowship Chancellor's Fellowship (UC Berkeley) McNair Scholar (UT Austin) Dr. Rodriguez actively mentors students and postdocs, currently advising six PhD students with several recent graduates. He co-organizes the Applied Algebra Seminar at UW Madison and is a key organizer for the SIAM Activity Group in Algebraic Geometry. His research group receives funding from multiple sources to support graduate students and undergraduate researchers. He is also co-organizing a semester-long program at the IMSI institute in Chicago titled 'Algebraic Statistics and Our Changing World: New Methods for New Challenges' for Fall 2023. He maintains strong connections with the Max Planck Institute for Mathematics in the Sciences in Leipzig, having participated in their summer school on 'Randomness and Learning in Non-Linear Algebra.' His research group includes postdocs, PhD students, and numerous undergraduate researchers working on various aspects of nonlinear algebra and its applications.

Joel Friedmanمشاهده پروفایل

استاد

• Algebraic Graph Theory
• Combinatorics
• Computer Science Theory
• +۵ مورد دیگر

Joel Friedman is a Professor in the Department of Computer Science at the University of British Columbia (UBC), Faculty of Science. His research focuses on Algebraic Graph Theory, Combinatorics, and Theoretical Computer Science, with significant contributions to spectral graph theory, sheaf theory, and computational complexity. He has supervised numerous PhD and Master's students in these areas. Friedman teaches courses such as CPSC 421 (Introduction to the Theory of Computing) and CPSC 531F (Discrete Hodge Theory and Topological Data Analysis). His work bridges pure mathematics and computer science, including studies on Riemann-Roch theorems for graphs, eigenvalue conjectures, and applications of linear algebra in discrete structures. He has authored over 50 publications, with recent contributions on topological data analysis, graph expansions, and algorithmic methods. Awards and honors include the Izaak Walton Killam Memorial Faculty Research Fellowship. Friedman actively engages in graduate supervision, advising students on topics like sparsifier constructions and coded caching problems. His research is affiliated with the Institute of Applied Mathematics at UBC. He has held academic positions since the 1980s, with a consistent record of contributions to theoretical computer science and discrete mathematics.

Justin Conroyمشاهده پروفایل

استاد

• Statistical Mechanics
• Theoretical Physics
• Transport Equations
• +۳ مورد دیگر

Dr. Justin Conroy is a Professor at the State University of New York at Fredonia. His research focuses on theoretical physics, statistical mechanics, and mathematical physics, with emphasis on entropy techniques, transport phenomena, and nonextensive thermostatics. He has contributed to topics like Tsallis statistics, quantum Hamiltonians, and grand unified theories. Dr. Conroy holds a Ph.D. from the College of William & Mary. His academic work includes presentations such as "What is Entropy?" at Georgia Southern University (2022) and publications in journals like Physica A and Springer. He administers scholarships such as the Computer Science, Mathematics, and Physics Scholarships (CSMAPS) since 2017. His research trends span from entropy-based modeling in environmental systems to high-energy physics applications of nonextensive statistics. Over 20 years, his work explores both foundational theories (e.g., transport equations) and applied problems (e.g., plume dispersion models). Dr. Conroy has no listed academic awards but maintains active grants related to STEM scholarships. His advising record and lab affiliations are not detailed in the provided texts.

• Partial Differential Equations
• Numerical Analysis
• Wave Propagation
• +۵ مورد دیگر

Dr. Martin Halla is a Junior Research Group Leader at the Karlsruhe Institute of Technology (KIT), specifically within the Institute for Applied and Numerical Mathematics, which operates under the Department of Mathematics. He assumed this faculty position in 2025 after completing several prestigious postdoctoral appointments. Dr. Halla completed his PhD at TU Wien in 2019 with the exceptional honor of "Promotio sub auspiciis Praesidentis rei publicae" in 2021, a distinction reserved for outstanding doctoral achievements in Austria. His academic path included postdoctoral positions at RICAM (2024-2025), University of Göttingen (2022-2024, 2020-2021), and the Max Planck Institute for Solar System Research in Göttingen (2021-2022, 2019-2020). His research focuses on advanced mathematical techniques for wave phenomena across multiple physical domains. He specializes in the analysis and numerical methods for partial differential equations, with particular expertise in wave propagation (acoustics, elasticity, electromagnetism, plasmonics, meta materials, stellar oscillations), eigenvalue problems (holomorphic, non-selfadjoint), transparent boundary conditions (perfectly matched layers, infinite elements), compatible discretizations (T-coercivity), and target signatures in inverse scattering. His work bridges theoretical mathematical analysis with practical computational methods. Dr. Halla's recent publications reveal a strong emphasis on developing robust numerical frameworks for complex wave phenomena, particularly addressing challenges with sign-changing coefficients, anisotropic media, and dispersive materials. His research shows a consistent trajectory toward creating innovative solutions for previously intractable wave propagation problems. DFG Sonderforschungsbereich 1173 "Wave Phenomena: Analysis and Numerics" (2025-present) DFG Emmy-Noether Project "T-coercivity and Target Signatures in Computational Wave Propagation" (2025-present) DFG Sachbeihilfe Project on "Analysis of eigenvalue problems arising in qualitative methods for inverse scattering" (2022-2024) Dr. Halla actively contributes to the academic community through organizing conferences and workshops, including a minisymposium at the Conference on Mathematics of Wave Phenomena (2025), the Spring School on "Novel Imaging Techniques with Waves" (2024), and serving on the organizing committee for the 11th Applied Inverse Problems Conference (2023).

Michael Plumمشاهده پروفایل

استاد

• Nonlinear Partial Differential Equations
• Numerical Analysis
• Spectral Theory
• +۳ مورد دیگر

Prof. Dr. Michael Plum is a faculty member at the Institute for Analysis , part of the Karlsruhe Institute of Technology (KIT) . His research focuses on nonlinear partial differential equations , spectral theory , and computer-assisted proofs in mathematical physics and applied mathematics. He has contributed to the analysis of solitons, metamaterials, and stability problems in fluid dynamics. His recent publications include work on the spectral analysis of Maxwell equations , black soliton dynamics , and homogenization of metamaterials . He has developed rigorous numerical methods for eigenvalue problems and nonlinear boundary value problems. His teaching encompasses advanced courses in analysis , partial differential equations , and numerical methods . His research trends span nonlinear PDEs , metamaterial modeling , and stability analysis . He leads the Workgroup Nonlinear Partial Differential Equations at KIT and has collaborated extensively on problems involving photonic crystals , electromagnetic wave propagation , and nonlocal constitutive relations . His full description includes over 90 publications in journals like SIAM Journal on Mathematical Analysis , Communications in Mathematical Physics , and Physical Review B . He has supervised numerous seminars and courses on analysis and applied mathematics since joining KIT. His work integrates numerical computation with theoretical analysis to address complex problems in mathematical physics and engineering applications .

Alessandro Tasoraمشاهده پروفایل

استاد

• Theoretical Mechanics
• Numerical Methods in Multibody Dynamics
• Robotics
• +۷ مورد دیگر

Alessandro Tasora is a Full Professor at the University of Parma in the Department of Industrial Engineering and Department of Engineering and Architecture . He directs the Digital Dynamics Lab and serves as Scientific Director of the Smart Production Lab 4.0 . His work spans theoretical mechanics, robotics, and high-performance computing. Director, Digital Dynamics Lab (2019–present) Scientific Director, Smart Production Lab 4.0 (2017–present) National Scientific Qualification for Full Professor (2016) Honorary Associate, University of Wisconsin-Madison (2009–present) Research focuses on non-smooth multibody dynamics , GPU-accelerated simulation , and industrial robotics . He developed the Chrono::Engine software for multibody physics and HyperOCTANT for NLCP problems. His work addresses granular flows in nuclear reactors, vehicle mobility on deformable terrain, and historical structural analysis. Key article trends include GPU-based HPC for large-scale simulations, cone complementarity in contact dynamics, and isogeometric beam formulations for flexible bodies. Collaborations with Argonne National Laboratory and Fraunhofer ITWM highlight his international impact. Top-SNIP Paper (2017) International CAE Conference Poster Award (2015) Best Paper, Asian Conference on Multibody Dynamics (2010) TOP4 Paper, RAAD Robotics Workshop (2011) He has supervised over 40 theses in automation, tribology, and robotics. Grants include FFABR-MIUR , US Army RIF , and CNR projects . Projects involve seismic protection, autonomous AGVs, and Industry 4.0 consulting.