## Consulting service

We would like to offer you, free of charge, a piece of advice on many aspects associated with Computational Mathematics as well as Scientific Computing in general. We are a group of graduate students and postdoctoral fellows who are passionate about computational aspects of many scientific and engineering disciplines. If you have a problem, for instance, with the implementation of sophisticated boundary conditions in your finite-element-based solver, or maybe you wondering which linear system algorithm would be the most effective for your simulation, then we invite you to contact one of our tutors or simply send an email to siam@math.mcmaster.ca. In the below table, you can find the list of our tutors that might help in solving your problem. If you are looking for more advanced expertise in some subfield, for example you are confused about your eigenvalues coming from a sophisticated system of elliptic PDEs, then please send an email before visiting us so we could arrange office hours with an appropriate tutor. However, if your question involves some basics of numerical analysis, programming languages or other related aspects, you are welcome to come by in the indicated time.

Please keep in mind that we are **not** here to solve your homework or course projects for numerical analysis-related courses, which does not mean that we must not discuss the problems you are struggling with!

## Tutors

Name | Areas of expertise | Environment |

John Ernsthausen | Text Based Computing, Static Websites, Content Managemnet, Search Engine Optimization, Data Coordination, Data Management, Numerical Methods for ODEs and DAEs, and more. | Ruby, C/C++ |

Adrian Forsythe | Bioinformatics Tools in Unix, Statistical Analysis and Graphics/ Visualization in R, Expertise in Latex (Beamer and Overleaf) | Unix, R |

Ramsha Khan | Finite Difference Methods, Numerical Linear Algebra with Matlab, Basics of Parallel Programming in OpenMP and MPI | MATLAB, Basic R |

Pritpal 'Pip' Matharu | Numerical Methods for ODEs and PDEs, Computational Fluid Dynamics, Spectral Methods, Finite Difference Methods, High Performance Computing: OpenMP, MPI, CUDA, GPU Computing | MATLAB, CUDA, C |

Carlos Hinrichsen Picand | Data Science, Statistical Learning, Clustering Algorithms, Dynamic Optimization, Simulation, Statistical Methods, Mathematical and Financial Modelling | R, Python |

Jonathon Riddell | Numerical linear algebra, computational methods for quantum and classical statistical mechanics (Monte Carlo, tensor networks and exact methods), MPI | Mathematica, C++ |