جست‌وجوی استاد و پژوهشگر

Jianxin Zhouمشاهده پروفایل

استاد

• Applied Mathematics
• Nonlinear Multiple Solution Problems
• Instability Analysis
• +۳ مورد دیگر

Jianxin Zhou is a Professor of Mathematics at Texas A&M University, affiliated with the College of Arts & Sciences. His primary research focuses on applied analysis and scientific computation, particularly in nonlinear multiple solution problems, instability analysis, multi-level optimization, and control/game theory for differential systems. He earned his Ph.D. in Mathematics from Pennsylvania State University in 1986. Education: Ph.D., Mathematics, Pennsylvania State University, 1986 Research Interests: His work emphasizes computational methods for solving nonlinear PDEs, including minimax-based algorithms, boundary element methods, and numerical optimization techniques. He has contributed to the development of the local minimax method and virtual geometric object approaches for identifying multiple solutions in complex systems. Recent Research Projects: Computational theory and methods for nonlinear multiple solution problems Development of augmented singular transforms and Newton-correction methods Analysis of eigenvalue problems and spatial vector solitons Advising & Grants: He has supervised 9 Ph.D. students and actively participates in international workshops, such as the 2009 Variational and Computational Methods conference in Beijing. His grants and collaborations include projects supported by the NSF and CNSF. Labs/Teams: Collaborates with researchers in computational mathematics, including work on multiscale enrichment procedures and boundary control systems.

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.

Panos Parpasمشاهده پروفایل

دانشیار

• Mathematical Optimization
• Computational Mathematics
• Scientific Computing
• +۳ مورد دیگر

Panos Parpas is a Reader in Computational Mathematics at the Department of Computing, Imperial College London. His research focuses on mathematical optimization algorithms, computational mathematics, and scientific computing, with applications in science, engineering, and finance. He previously held roles as a postdoctoral fellow at MIT and a quant at Credit Suisse. Key research interests include dynamical systems, numerical methods for optimization, and stochastic processes. He teaches courses such as Computational Optimization and Computational Finance with C++. His work bridges theoretical optimization with practical applications in areas like water distribution networks, financial modeling, and machine learning. Panos has authored numerous publications on topics like multilevel optimization methods, stochastic mirror descent algorithms, and the analysis of saddle points using Witten Laplacians. His research emphasizes algorithmic efficiency and scalability, particularly in high-dimensional and distributed settings. Notable collaborations include projects on optimizing water distribution systems (e.g., pump scheduling and pressure management) and developing robust algorithms for financial and engineering systems. His contributions span journals like Automatica , SIAM Journal on Scientific Computing , and Journal of Optimization Theory and Applications .

• Differential Equations
• Nonlinear Dynamics
• Mathematical Analysis
• +۷ مورد دیگر

Marco Sabatini is a Professor in the Department of Mathematics at the University of Trento, Faculty of Engineering. With over 35 years of academic service, he has established himself as a leading researcher in differential equations and dynamical systems. His institutional commitment is evident through his long-standing teaching responsibilities and leadership roles within the university. His educational background includes a Degree in Mathematics from the University of Palermo (1980) and an M.Sc. at SISSA, International School for Advanced Studies in Trieste (1983). These foundational experiences prepared him for his extensive career in mathematical research and education. Sabatini's research focuses on the qualitative analysis of planar differential systems, with particular emphasis on integrability, isochrony, symmetries, bifurcation theory, limit cycle existence and uniqueness, and the XVI Hilbert problem. His work also explores global invertibility of locally invertible maps, contributing significantly to the Jacobian Conjecture field. His approach combines rigorous mathematical analysis with geometric insights to solve complex problems in nonlinear dynamics. His recent publications (2013-2023) demonstrate remarkable consistency in exploring planar dynamical systems, with recurring themes in limit cycle theory, Jacobian Conjecture investigations, and period function analysis. The research shows increasing sophistication in handling non-singular planar maps and extending classical conjectures in dynamical systems theory. Sabatini has served as a PhD advisor, notably guiding Luca Trussoni (2000-2002), and coordinated the Mathematics PhD program at University of Trento (2005-2007). He has participated extensively in national research projects, serving as local coordinator for G.N.A.F.A. projects (1991-1997) and national coordinator for G.N.A.M.P.A. projects (2005-2006). As coordinator of research groups including 'Mathematical Physics and Dynamical Systems' (2007-2014) and 'Dynamical Systems and Control Theory' (2015-2023), he has fostered collaborative research environments. His leadership extends to serving on hiring committees for professorships and PhD admissions at multiple Italian universities, demonstrating his respected position within the national mathematical community.

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.

Chongchun Zengمشاهده پروفایل

استاد

• Applied Dynamical Systems
• Nonlinear Partial Differential Equations
• Fluid Dynamics
• +۷ مورد دیگر

Chongchun Zeng is a Professor in the School of Mathematics at Georgia Institute of Technology since 2009, previously holding roles at the University of Virginia and New York University's Courant Institute. His research focuses on applied dynamical systems and nonlinear PDEs, particularly fluid dynamics, nonlinear waves, and invariant manifold theory. Education PhD in Mathematics (1997), Brigham Young University Bachelor of Mathematics (1993), Nankai University, China Research Interests Explores regularity and dynamics of nonlinear PDEs, invariant manifolds in semiflows, and applications to fluid equations (e.g., water waves) and Schrödinger-type systems. Recent work addresses stability of traveling waves, spectral analysis of linearized operators, and inviscid damping phenomena. Awards & Grants Sloan Fellowship (2004) AMS Fellow (2019) NSF grants (2003–present, including DMS-2350115 for fluid dynamics research) Grants & Collaborations Analysis of Fluids and Nonlinear Waves (NSF DMS-2350115, 2024–2027) Studies on gravity water waves and nonlinear Schrödinger equations Lab/Team Affiliation Active in Georgia Tech's School of Mathematics research groups focused on PDEs and dynamical systems.

• Differential Equations
• Applied Mathematics
• Variational Calculus
• +۷ مورد دیگر

Mark A. Peletier is a Full Professor at the Technische Universiteit Eindhoven within the Department of Mathematics and Computer Science. His research bridges differential equations, variational calculus, and applications in biology, geology, chemistry, and physics. He has held visiting positions at institutions in London, Bath, and Vancouver, and serves on editorial boards of international journals. Education: MSc (cum laude) and PhD in Mathematics from Leiden University, Diplôme d'Études Approfondies from Université Paris VI. Appointments: University of Bath (1997-1998), CWI Amsterdam (1998-2004), TU Eindhoven (2004-present). Peletier’s research spans gradient flows, large deviations, and nonlinear systems. His work on Hamilton-Jacobi equations and molecular motors provides theoretical insights into transport phenomena, while his contributions to neural stochastic differential equations integrate mathematics with machine learning. He emphasizes breaking detailed balance for directional transport in stochastic models. Recent publications focus on spectral problems, Coulomb interactions, and interpretable AI. His mathematical frameworks unify stochastic processes, variational principles, and multiscale modeling. Collaborations extend across disciplines, including energy engineering and computational chemistry. Scientific recognition includes NWO Vidi (2003) and Vici (2011) grants, and membership in De Jonge Akademie (2006-2011). He has supervised 49 research works and contributes to journals like Electronic Journal of Probability and Lecture Notes on Mathematical Modelling in the Life Sciences .

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 .

Jia Liuمشاهده پروفایل

استاد

• Computational Mathematics
• Numerical Linear Algebra
• Sparse Matrix Computations
• +۹ مورد دیگر

Dr. Jia Liu is a Professor and Chair of the Department of Mathematics and Statistics at the University of West Florida, within the Hal Marcus College of Science and Engineering. She has been a key academic figure at UWF since 2006, leading both research and departmental initiatives in computational and applied mathematics. Her educational background includes a Ph.D. in Mathematics from Emory University, funded by the National Science Foundation, focusing on preconditioned Krylov subspace methods for incompressible flow problems. She earned her M.S. and B.A. in Mathematics from Central China Normal University, where her bachelor's thesis received the highest honor. Dr. Liu's research lies at the intersection of numerical linear algebra, scientific computing, and interdisciplinary applications. Her primary interests include: Numerical solvers for large sparse linear systems Krylov subspace iterative methods Preconditioning techniques Applications to Navier-Stokes and optimization problems Geometric and topological analysis of ellipsoids Complex networks and community detection via spectral clustering Machine learning for disease prediction and biological modeling The trends in her publications reflect a consistent focus on robust numerical algorithms with applications across fluid dynamics, network science, and biomedical modeling. Her work emphasizes both theoretical development and practical implementation in high-performance computing environments. Dr. Liu has served as an editor and editorial board member for several peer-reviewed journals and regularly reviews submissions. While specific awards are not listed, her sustained publication record in prestigious venues such as SIAM Journal on Scientific Computing and Journal of Biological Dynamics underscores her scholarly impact. As department chair and professor, she plays a central role in academic advising, curriculum development, and research mentorship. She teaches core courses including Differential Equations, Numerical Analysis, and Real Analysis, contributing significantly to both undergraduate and graduate education. Her leadership extends to managing research grants and fostering collaborations across disciplines. Though no formal lab name is mentioned, her research activities suggest involvement with computational modeling groups, likely associated with applied mathematics and data science initiatives at UWF. Her ongoing work continues to advance numerical methods for complex systems in science and engineering.

Simão Correiaمشاهده پروفایل

دانشیار

• Partial Differential Equations
• Nonlinear Dynamics
• Mathematical Analysis
• +۳ مورد دیگر

Simão Correia is an Associate Professor at the Department of Mathematics of the University of Lisbon, affiliated with the Research Center CAMGSD. His research focuses on nonlinear dispersive and elliptic partial differential equations, particularly on local existence, stability of solutions, and blow-up dynamics. Current Position: Associate Professor, University of Lisbon Research Center: CAMGSD Projects: Co-PI of FCT project NoDES His recent publications address topics such as self-similar solutions for the modified KdV equation, nonlinear smoothing effects in dispersive equations, and stability transitions of NLS ground-states on metric graphs. These works emphasize sharp existence results, multiplier estimates, and applications to mathematical physics. He actively collaborates with researchers like Raphaël Côte, Hugo Tavares, and Jorge Drumond Silva, contributing to the understanding of nonlinear PDEs and their dynamical properties. Notable current trends include: Global and local well-posedness for higher-order dispersive equations Stability analysis of stationary and blow-up solutions Applications to metric graphs and expanding spacetime models Correia's work bridges theoretical analysis with physical phenomena, including cosmic rigid rod dynamics and quantum media systems.

Ahmad Mohammadpanahمشاهده پروفایل

مدرس

• Dynamics
• Vibrations
• Modal Analysis
• +۵ مورد دیگر

Ahmad Mohammadpanah serves as a Lecturer in the Department of Mechanical Engineering within the Faculty of Applied Science at the University of British Columbia (UBC). Holding a Professional Engineer (P.Eng.) designation, he earned his PhD and MASc from UBC alongside an MSc from Sharif University of Technology. His academic profile is anchored in mechanical engineering with specialized expertise in dynamic systems and manufacturing technologies. His educational qualifications include: PhD in Mechanical Engineering, University of British Columbia MASc in Mechanical Engineering, University of British Columbia MSc in Mechanical Engineering, Sharif University of Technology Dr. Mohammadpanah's research centers on Dynamics, Vibrations, and Modal Analysis , with pioneering work in Spherical Parallel Robots and Light Weight Lattice Design for Additive Manufacturing . His exploration of Generative Design & Topology Optimization bridges computational methods with practical manufacturing solutions. Current investigations focus on thermal management in metal extrusion additive manufacturing and vibration control in industrial saw systems, demonstrating strong alignment with industry needs in wood processing and advanced manufacturing. Analysis of his 10 publications (2012-2024) reveals consistent focus on vibration phenomena in rotating machinery and additive manufacturing defect mitigation. His work shows progressive evolution from fundamental dynamics research (2012-2018) toward applied industrial solutions (2021-2024), particularly in metal additive manufacturing and smart lumber production. The integration of machine learning in wood quality prediction (2023) highlights his adaptation to emerging computational techniques. No scientific awards were documented in the provided materials. Regarding academic mentorship, Dr. Mohammadpanah actively supervises undergraduate capstone projects (MECH 45X) and laboratory courses, though formal graduate student advisement isn't specified. His teaching portfolio spans foundational courses like MECH 223 (Introduction to Mechanical Design) through advanced topics including MANU 465 (AI in Manufacturing), reflecting comprehensive engagement with mechanical engineering education. His research operates through the "Intelligent Engineering" initiative, focusing on practical industrial applications rather than dedicated laboratory facilities. Current work emphasizes real-world implementation of vibration control systems and additive manufacturing optimization, with strong industry connections evident through Fpinnovations collaboration and patent development.

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.

• Calculus of Variations
• Partial Differential Equations
• Shape Optimization
• +۱۱ مورد دیگر

Paolo Tilli is a Full Professor in the Department of Mathematical Sciences "G. L. Lagrange" (DISMA) at Politecnico di Torino, Italy. He is actively involved in research, teaching, and doctoral supervision, with a strong presence in mathematical analysis and its applications. His research focuses on calculus of variations , partial differential equations , shape optimization , and phase space analysis with applications to quantum mechanics. He is a member of the Analysis and Quantum Theory research group at DISMA, and his work spans theoretical analysis of singular models, spectral theory, and nonlinear dynamics on networks and metric graphs. The recent publications of Paolo Tilli reveal a consistent and high-impact research trajectory in nonlinear PDEs , time-frequency analysis , and quantum graphs . His work frequently appears in top journals such as Inventiones Mathematicae and Advances in Mathematics , with a focus on Faber-Krahn inequalities, localization operators, and ground states in nonlinear Schrödinger equations. These contributions reflect deep analytical techniques and interdisciplinary relevance, particularly in mathematical physics and signal processing. He has supervised PhD students including Federico Riccardi and has been a long-standing member of doctoral college committees for the PhD programs in Mathematical Sciences at Politecnico di Torino and the University of Turin. His teaching includes core courses such as Metodi Variazionali e Applicazioni and Analisi Matematica II across various engineering and mathematics programs. His research groups include: Analysis and Quantum Theory Group (DISMA)

Hildeberto Jardón Kojakhmetovمشاهده پروفایل

استادیار

• Dynamical Systems
• Control Theory
• Mathematical Biology
• +۳ مورد دیگر

Hildeberto Jardón Kojakhmetov is an Assistant Professor in the Dynamical Systems, Geometry and Mathematical Physics (DSGMP) group at the Bernoulli Institute, University of Groningen. His research focuses on dynamical systems with multiple time scales, including applications in control theory, mathematical biology, neuroscience, and network science. He is particularly interested in slow-fast systems, bifurcation analysis, and the interplay between network structures and dynamical behavior. His research interests span theoretical and applied domains, emphasizing geometric singular perturbation techniques, hypergraph models, and the analysis of complex systems. Key areas include epidemic spreading on hypergraphs, co-evolutionary dynamics, and synchronization phenomena in heterogeneous networks. He also explores topological aspects of canards and singularities in fast-slow systems. Recent work trends highlight advancements in understanding multiscale dynamics through novel mathematical frameworks, such as tensor-based Hamiltonian systems and S-tensors for ecological models. His contributions address both foundational theory and practical applications in systems biology and network control. While no scientific awards are explicitly mentioned in available texts, his extensive publication record reflects a strong commitment to advancing nonlinear dynamics and complex systems research. His academic activities include organizing events like the Summer School on Multiscale Modelling and the Floris Takens Seminar.

Jay Gopalakrishnanمشاهده پروفایل

استاد

• Scientific computation
• Numerical analysis
• Finite elements
• +۳ مورد دیگر

Jay Gopalakrishnan is a Professor of Mathematics and the Maseeh Distinguished Chair at Portland State University's Department of Mathematics. His research focuses on scientific computation, numerical analysis, finite elements, and multigrid methods with applications in optics and mechanics. He has contributed significantly to the development of hybridizable discontinuous Galerkin (HDG) methods and the Discontinuous Petrov-Galerkin (DPG) framework, emphasizing structure-preserving numerical techniques. His work spans diverse domains including microstructured optical fibers, spacetime tents for hyperbolic systems, and eigenvalue cluster computations. Notable research activities include developing accurate computational tools for leaky modes in fibers, stability analysis of acoustic waveguides, and bone mineralization models. He advises doctoral students at institutions such as Intel Corporation, The MathWorks, and James Madison University. His teaching includes advanced numerical analysis courses and undergraduate mathematical computing. Collaborations with researchers like L. Demkowicz and J. Schöberl highlight his interdisciplinary impact in computational mathematics and engineering.