Lennaert van Veen, PhD
Associate Professor
Graduate Program Director
Mathematics
Faculty of Science
Graduate Program Director
Mathematics
Faculty of Science
Using applied and computational dynamical systems theory to build a better understanding of physical and physiological processes
Full biography
Mathematically speaking, the complexity of the human brain and the unstable nature of turbulence really aren’t all that different. In fact, in spite of their peculiarities, the analysis techniques are very similar to these nonlinear dynamical systems. Lennaert van Veen, Ph.D., Associate Professor and Graduate Program Director of Modelling and Computational Science in the Faculty of Science, explores the application of dynamical systems theory to complex phenomena and high-dimensional chaos. A Project Leader with Collective Lab for Applied and Interdisciplinary Mathematics (CLAIM), his latest research focuses on transitions and pattern formation in physical and physiological systems with applications in fluid turbulence, as well as cortical dynamics of depression, both of which have been poorly understood. Dr. van Veen is investigating ways to model the human cortex and develop novel computational techniques for turbulence. His research will expand the knowledge of how these systems function, and feed into research to develop advanced techniques for minimizing turbulence, as well as create novel strategies for less invasive brain control, with the ultimate goal of curing brain disorders. He completed his Master of Science in Theoretical Physics at the University of Amsterdam and received his Doctorate in Applied Mathematics at the Utrecht University and the Royal Dutch Meteorological Institute in Bilt, Netherlands. Subsequently, he was awarded successive post-doctoral fellowships by the Japan Society for the Promotion of Science, and the Australian Research Council Centre of Excellence for Mathematics and Statistics of Complex Systems. In 2007, Dr. van Veen was appointed Assistant Professor in the Department of Mathematics and Statistics at Concordia University in Montréal, Québec, and continued to serve as an Adjunct Assistant Professor until 2011. Broadening his international teaching experience, he was named a Researcher in Residence for the Research Experiences for Undergraduates program at the Rochester Institute of Technology in New York and taught in the Geophysical Fluid Dynamics program of the Woods Hole Oceanographic Institution in Massachusetts. He continues to share his expertise via Virtual Researcher on Call (www.vroc.ca), enabling secondary school students to access interviews discussing his research topics. Ontario Tech University's
Areas of expertise
Courses
- MATH 4020UComputational Science IIThis course provides a variety of results and algorithms from a theoretical point of view. Students study numerical differentiation and integration; interpolation and approximation of functions; quadrature methods; numerical solution of ordinary differential equations; the algebraic eigenvalue problem. Computer software such as Maple and MatLab will be used in assignments.
- MATH 4050UPartial Differential EquationsThis course considers advanced aspects of the theory, solution and physical interpretation of first and second order partial differential equations in up to four independent variables. This includes the classification of types of equations and the theory and examples of associated boundary-value problems. The concepts of maximum principles and Green’s functions are studied, as well as an introduction to nonlinear equations. A broad range of applications are considered.
- MCSC 6030GHigh-Performance ComputingThe goal of this course is to introduce students to the tools and methods of high-performance computing (HPC) using state-of-the-art technologies. The course includes an overview of high-performance scientific computing architectures (interconnection networks, processor arrays, multiprocessors, shared and distributed memory, etc.) and examples of applications that require HPC. The emphasis is on giving students practical skills needed to exploit distributed and parallel computing hardware for maximizing efficiency and performance. In a number of in-class projects, students implement numerical algorithms that can be scaled up for large systems of linear or nonlinear equations. Topics may include survey of computer architectures; efficiency guidelines for HPC; parallel algorithm design; programming tools; timing, profiling and benchmarking; and optimizations.
Education
- 2002PhD - Applied MathematicsUtrecht University and the Royal Dutch Meteorological Institute, Netherlands
- 1996MSc - Theoretical PhysicsUniversity of Amsterdam, Netherlands
Speaking Engagements
- Montréal, Québec April 12, 2015Equilibria and Periodic Orbits in 3D Navier-Stokes Flow on a Periodic Domain2015 CMS Winter Meeting
- Durham, New Hampshire January 11, 2015Sub-Critical Transition Without Walls Workshop on Advancing Wall-Turbulence Model Development and ImplementationUniversity of New Hampshire Workshop
- Paris, France December 31, 1969Simple Invariant Solutions in Homogeneous Isotropic Turbulence with Various External ForcesSixth International Symposium on Bifurcations and Instabilities in Fluid Dynamics
- Waterloo, Ontario July 6, 2015Numerical Solution of the Kuramoto-Sivashinsky Initial-Boundary Value ProblemCanadian Applied and Industrial Mathematics (CAIMS) 2015 Annual Meeting
- Cusco, Peru December 31, 1969Bifurcations and Self-Organisation in a Continuum Model of the Human CortexAdvanced Computational and Experimental Techniques in Nonlinear Dynamics Workshop
- Paris, France December 31, 1969Pattern Formation in a Mean-Field Model of Electrocortical Activity23nd Annual Computational Neuroscience Meeting
- San Diego, California July 8, 2012Meta-Bifurcation Analysis of a Mean-Field Model of the Human CortexSociety for Applied and Industrial Mathematics (SIAM) Conference on the Life Sciences
- Atlanta, Georgia December 31, 1969Turing Instabilities in a Mean-Field Model of Electrocortical Activity22nd Annual Computational Neuroscience Meeting
- Seattle, Washington December 31, 1969Dynamics of a Mean-Field Cortex ModelSIAM Conference on Nonlinear Waves and Coherent Structures
- Chicago, Illinois December 31, 1969Pattern Formation and Nonlinear Oscillations in a Neural Population Model2012 Annual Meeting of the Cognitive Neuroscience Society
Affiliations
- Organization for Computational Neurosciences
- Japan Society for the Promotion of Science (JSPS)
- American Physical Society
- Canadian Applied and Industrial Mathematics Society
- Society for Industrial and Applied Mathematics
- Shared Hierarchical Academic Research Computing Network (SHARCNet)