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There have been subjects I didn't enjoy, but math was never one of them. I understand the frustration of such an exact field of study though: it requires patience and practice to learn it well. The same goes for writing software and for physics.

I have written software for a living for decades and plan to continue to do so in the

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My undergraduate program had a focus in computer science, but we didn't cover C, so I taught myself in 1985. Since then I have written dozens of large programs in C as an engineer, mostly for embedded systems, which had to be both efficient and structured. C and C++ are completely second-nature to me.

In 1990 I taught myself C++, and have used it as an engineer since then for a variety of applications. Those included complete GUI apps, GUI windows and controls as part of team, mathematical analysis, and dozens of test apps. By using it I learned the value of the object-oriented techniques I had been taught, for keeping large software projects manageable, and for code reuse. I have also used it for fun to generate various animations.

MS Applied Mathematics - An understanding of multivariable calculus was an essential prerequisite for the program.

I have had a twenty year professional career as a software engineer. In that time I have learned and used a wide variety of languages, including Fortran, Lisp, C/C++, Java, and Matlab. I also used a variety of assembly languages, including 6800, 56000, and 8051. I have training in computer science and experience implementing several large and many small software projects. Most of my experience is in mathematical algorithms, embedded systems, and GUI.

Computer science was the minor focus in my undergraduate program. We studied a variety of topics, including data structures, algorithms, object-oriented programming, and compiler construction. I have been writing software software professionally much of my life, and often the computational complexity of an algorithm is an important factor. I have always found algorithms and their efficiency interesting.

A thorough knowledge of differential equations was required for my graduate degree. I have studied Laplace transforms, nonlinear dynamics, partial differential equations, and perturbation theory. A focus in my MS program was numerical solution of PDEs.

Linear algebra was a core requirement in my undergraduate program, and I have used it extensively for other subjects, and also professionally. I have a good understanding of most of the subject, such as linear solutions, subspaces, factorizations, eigenvectors/values, and matrix powers. I have used matrices in such subjects as optimization, nonlinear dynamics, and numerical solution of differential equations.

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