جستجوی استاد راهنمای دانشگاهی

Chun-Hua Guoمشاهده پروفایل

استاد

• Matrix analysis
• Scientific computing
• Numerical linear algebra
• +۳ مورد دیگر

Chun-Hua Guo is a Professor in the Department of Mathematics and Statistics at the University of Regina, Faculty of Science. His research focuses on matrix analysis, scientific computing, and applications in tensor computations and nonlinear matrix equations. He teaches advanced courses such as MATH 869 Numerical Analysis. Dr. Guo’s recent work emphasizes iterative methods for solving eigenvalue problems of nonnegative tensors, matrix equations arising in nano research, and convergence analysis of numerical algorithms. His publications address topics like Newton-Noda iteration, modified Newton methods for Z-eigenpairs, and algebraic Riccati equations associated with M-matrices. His research trends highlight advancements in computational techniques for matrix functions (e.g., matrix pth root), tensor Perron pairs, and stability analysis of iterative algorithms. These contributions bridge theoretical linear algebra with practical computational challenges in engineering and scientific domains. Dr. Guo’s advising and grants involve developing efficient numerical methods for complex systems. His work has implications for fields requiring high-precision matrix computations, such as control theory, stochastic modeling, and nano-material simulations.

Patrick Dumondمشاهده پروفایل

دانشیار

• Vibration and Acoustic System Design
• Inverse Eigenvalue Methods
• Mechanical/Biomechanical Design
• +۳ مورد دیگر

Associate Professor Patrick Dumond holds a Ph.D., M.A.Sc., and B.A.Sc. from the University of Ottawa. He is affiliated with the Department of Mechanical Engineering, Faculty of Engineering. His research focuses on vibration/acoustic system design, inverse eigenvalue methods, biomechanical design, design theory, musical acoustics, and experiential engineering education. He actively contributes to the Centre for Entrepreneurship and Engineering Design (CEED) and advises students in engineering competitions. His work bridges mechanical engineering with biomedical and educational applications, emphasizing practical, hands-on learning. Education: All degrees earned at the University of Ottawa—Ph.D. (2015), M.A.Sc. (uOttawa), B.A.Sc. (uOttawa). Research interests include vibration systems, biomedical prosthetics (e.g., hip joint prostheses), and machine learning for fault diagnosis. He has published extensively on topics like bearing fault detection, data fusion, and educational program design. Professional Involvement: CEED co-development, advising student teams, and advancing multidisciplinary engineering education. Labs/Teams: Core contributor to the Centre for Entrepreneurship and Engineering Design (CEED).

• Numerical Analysis
• Scientific Computing
• Matrix Theory
• +۵ مورد دیگر

Nicola Guglielmi is a Professor of Numerical Analysis at the Gran Sasso Science Institute (GSSI) in L'Aquila, Italy, since February 2018. He currently serves as Deputy Rector of GSSI (2022–2026) and Director of the Division of Mathematics (2019–2025). Previously, he held positions at the University of L'Aquila, including Full Professor of Numerical Analysis (2006–2018). His education includes a Laurea from the University of Bologna (1991, summa cum laude) and a PhD in Computational Mathematics from the University of Padova (1996). His research focuses on numerical analysis, particularly delay differential equations, matrix theory applications, and stability analysis of dynamical systems. He has authored over 100 publications and developed the RADAR5 software for delay differential equations. Recent grants include the 2023 MIUR/PNRR project on geothermal energy modeling and the 2022 PRIN project on numerical methods for PDEs. Notable awards include the New Talent Award at SciCADE-99 (1999) and a plenary lecture at the UMI-23 conference (2023). He has supervised numerous PhD students, many now in academia and industry. Upcoming activities include visits to the Courant Institute (2025) and McGill University (2025). His work bridges theoretical and applied mathematics, with contributions to scientific computing, control theory, and data science.

Angelo Mingarelliمشاهده پروفایل

استاد

• Celestial Mechanics
• Spectral Theory of Differential Operators
• Fuzzy Cellular Automata
• +۵ مورد دیگر

Angelo Mingarelli is a Professor in the School of Mathematics and Statistics at Carleton University, Ottawa, Canada. He specializes in Differential Equations, Spectral Theory, and Fuzzy Cellular Automata, with contributions to Celestial Mechanics and Number Theory. His research explores topics such as asymptotic analysis of differential equations, inverse Sturm-Liouville problems, and the dynamics of cellular automata. Dr. Mingarelli has taught numerous courses, including Calculus for Engineers, Advanced Calculus, and Theory of Differential Equations, spanning over two decades at Carleton. His work bridges pure and applied mathematics, with a focus on theoretical foundations and their applications. His publications span over 50 peer-reviewed articles, emphasizing nonlinear differential equations, spectral analysis, and fuzzy systems. Recent trends in his work include asymptotic methods, inverse problems, and the mathematical modeling of dynamic systems. While no formal awards are listed, his extensive contributions to mathematical research and education reflect his expertise and dedication to academia. He maintains an active role in mentoring students and advancing interdisciplinary mathematical inquiry.

• Applied Mathematics
• Partial Differential Equations (PDE)
• Numerical Analysis
• +۵ مورد دیگر

Nilima Nigam is a Professor of Mathematics at Simon Fraser University (SFU), part of the Department of Mathematics within the Faculty of Science. She holds a Ph.D. in Applied Mathematics from the University of Delaware (1999). Her research focuses on numerical analysis of partial differential equations (PDEs), computational electromagnetics, mathematical physiology, and biomechanics. She is also actively involved in interdisciplinary projects, such as modeling muscle-tendon complexes and spectral geometry problems. Nigam serves on editorial boards for journals like the SIAM Journal on Scientific Computing and Mathematics-in-Industry Case Studies. She supervises graduate and undergraduate students in applied mathematics, with a focus on structure-preserving discretizations, computational biology, and spectral problems. Her work includes collaborations with researchers in biomechanics, notably with James Wakeling in studying muscle mechanics and energy dynamics. She has mentored numerous students through programs like the SFU Department of Mathematics USRA competition. Her teaching spans advanced courses in numerical analysis, PDEs, and mathematical physics.

Alec Jacobsonمشاهده پروفایل

دانشیار

• Geometry Processing
• Discrete Differential Geometry
• Computer Graphics
• +۳ مورد دیگر

Alec Jacobson is an Associate Professor in the Department of Computer Science at the University of Toronto, with a courtesy appointment in Mathematics. He holds the Canada Research Chair in Geometry Processing and serves as a Senior Research Scientist at Adobe Research Toronto. Located at the Bahen Centre, he leads research in computer graphics and geometry processing as part of the Dynamic Graphics Project lab. His research focuses on Geometry Processing , Discrete Differential Geometry , and Computer Graphics , with applications in 3D reconstruction, computational fabrication, and neural representations. Key areas include mesh processing algorithms, physics-based simulation, and differentiable rendering techniques that bridge theoretical foundations with practical implementations. Recent publications demonstrate strong trends in neural field optimizations, robust 3D reconstruction, and physics simulation. His team frequently combines machine learning with geometric methods to solve challenging inverse problems in computer vision and graphics, with consistent innovation in computational efficiency and mathematical foundations. Scientific Awards: Canada Research Chair in Geometry Processing AXL Faculty Fellow Best Paper Honourable Mention (SGP 2024) Best Paper Award (SIGGRAPH 2022) Test of Time Award (SIGGRAPH 2024) He leads the Third Space research group advising numerous graduate students and postdocs. Current research infrastructure includes collaborations with the Vector Institute and Adobe Research, supported by grants focused on geometric algorithms and neural representations.

Karen Meagherمشاهده پروفایل

استاد

• Combinatorics
• Algebraic Graph Theory
• Erdős-Ko-Rado Theorems
• +۵ مورد دیگر

Karen Meagher is a Professor and Chair of the Graduate Studies Committee in the Department of Mathematics and Statistics at the University of Regina's Faculty of Science. Her research focuses on combinatorics and algebraic graph theory, with particular emphasis on Erdős-Ko-Rado theorems and their extensions. Her primary research interests include: Combinatorics and algebraic graph theory Erdős-Ko-Rado theorem generalizations Design theory and covering arrays Extremal set theory applied to partitions and permutations Zero-forcing sets and metric dimension of graphs Applications of algebraic methods to combinatorial problems Analysis of her recent publications reveals a consistent focus on extending Erdős-Ko-Rado theory to various combinatorial structures including graphs, permutation groups, and set partitions. Her work frequently employs algebraic graph theory techniques and has significant applications in design theory and extremal combinatorics. Meagher leads the Discrete Math Research Group at the University of Regina, which includes faculty members Shaun Fallat and Allen Herman, multiple post-doctoral fellows, and graduate students. She has supervised three PhD students to completion: Alison Purdy (2014), Fatemeh Alinaghipour (2013), and Bahman Ahmadi (2013), with Alison Purdy also completing a Master's under her supervision in 2010. Outside of mathematics, Meagher maintains a 'super-nerdy hobby' of mathematical quilting, creating designs based on combinatorial structures like Greco-Latin squares.

• Numerical Analysis
• Scientific Computing
• Domain Decomposition Methods
• +۴ مورد دیگر

Conor McCoid is a Research Fellow in Mathematics at McMaster University, specializing in numerical analysis, scientific computing, and computational geometry. His research focuses on domain decomposition methods, spectral collocation techniques, and algorithm development for computational problems such as phase field models and geometric intersections. He holds a PhD from the University of Geneva, where he worked on domain decomposition under Martin Gander, and a Master's from Simon Fraser University in spectral collocation methods with Manfred Trummer. His postdoctoral work at McMaster involves accelerating phase field models for fractures and optimizing Schwarz methods. McCoid's research interests include developing robust algorithms for geometric intersections (e.g., triangles and tetrahedra), improving spectral collocation methods for boundary value problems, and prototyping machine learning algorithms for music analysis (e.g., Mozart classification). His GitHub repository includes code for tetrahedral intersections, adaptive Schwarz methods, and music data processing using tools like music21 and scikit-learn. His publications explore numerical methods for multigrid cycles, nonlinear solvers, and geometric algorithms, often emphasizing robustness and efficiency in computational contexts. Collaborations include work with Blaise Bourdin (McMaster), Felix Kwok (Université Laval), and Martin Gander (Geneva).