Convex Optimization
Graduate course, Toyota Technological Institute at Chicago, 2018
Teaching assistant. The course was taught by prof. Nathan Srebro. This course covers techniques in unconstrained and constrained convex optimization.
Teaching
Matrix Computations
Graduate course, The University of Chicago, 2018
Teaching assistant. The course was taught by prof. Lek-Heng Lim. The course is attended by PhD students and Master students and lays out a solid foundation for numerical linear algebra. Most up to date syllabus for this course is avalible on here
Statistical Models
Undergraduate course, The University of Chicago, 2017
Teaching assistant. The course was taught by Dr. Linda Collins. This course presents basic ideas of probability theory and statistics, and is recommended for students throughout the natural and social sciences who want a broad background in statistical methodology and exposure to probability models and the statistical concepts underlying the methodology.
Optimization
Undergraduate course, The University of Chicago, 2017
Teaching assistant. The course was taught by prof. Lek-Heng Lim. A rigorous introductory course on unconstrained and constrained optimization optimization covering relevant topics from multivariate analysis and differencial calculus.
Matrix Computations
Graduate course, The University of Chicago, 2017
Teaching assistant. The course was taught by prof. Lek-Heng Lim. The course is attended by PhD students and Master students and lays out a solid foundation for numerical linear algebra. Most up to date syllabus for this course is avalible on here
Statistical Methods And Applications
Undergraduate course, The University of Chicago, 2017
Teaching assistant. The course was taught by Dr. Loretta Au. This course introduces statistical techniques and methods of data analysis, including the use of statistical software. Examples are drawn from the biological, physical, and social sciences. Students are required to apply the techniques discussed to data drawn from actual research.