Teaching
I teach classes on subjects such as deep learning, linear algebra, analytic geometry and calculus, elements of statistics, computational neuroscience with applications, mathematical statistics and math/statistics/data science capstone projects. Additionally, I am in the process of designing more courses focused on computational neuroscience, statistical computing, and mathematical modeling.
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Successes of my students is my foremost goal. I employ regular, structured assessments to continually gauge their understanding and development. Don't be startled if you're greeted with a pop quiz on day one—it's all part of the plan. In my classes, the journey you take to arrive at an answer is much more important than the answer itself. Hence, grading prioritizes the problem-solving methodology. Collaborative group projects are a staple in many of my courses, emphasizing the vital skills of teamwork and effective communication that students will need in professional settings.
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If you need to reach me, I am generally available in my office from Monday to Friday. You can also expect an email response within approximately 4 hours during regular work hours.
Linear Algebra
Study of linear systems: Gaussian elimination, matrix algebra, determinants, vector spaces, linear independence, bases, orthogonality, linear transformations, matrix representations, eigenvalues, and eigenvectors.
Mathematical Statistics
Introduction to fundamental concepts of Mathematical Statistics: counting methods, probability laws, Bayes' rule, discrete and continuous distributions, moments, and moment-generating functions.
Analytic Geometry and Calculus
Differential and Integral Calculus of Algebraic, Trigonometric, and Transcendental functions of single variables with some related applications.
Deep Learning
Introduction to fundamental concepts of deep learning: creation and practical application of ANNs, neural network learning, training, and various neural network architectures like CNN and RNN.
Math/Stats/Data Science Capstone Projects
The capstone project will allow student to gain experience in mathematical modeling, data wrangling, data visualization, statistical modeling, machine learning, numerical simulation, reporting, and presenting the results. Upon the completion of this course, you will have a paper and slides to show to potential hiring managers.