Teaching
Teaching
I greatly enjoy teaching and connecting with students over the material. I'm a proponent of structured, partially flipped classrooms for maximum learning potential.
Completely flipped classrooms require heavy time commitments from students outside of the classroom, and in my experience, they frequently don't put in the time. Partially flipped includes lecturing half the time, and then going through guided, scaffolded questions and examples with the students highlighting the processes and focusing on building intuition and the problem solving skills.
I've been a GTA for CMSE 382: Optimization in Data Science. This is an upper-level requirement for the major in Data Science at MSU that focuses on optimization theory, algorithms, and their applications to big data.
My primary responsibilities were grading, facilitating class time, and holding office hours. I also created course content on occasion. For more information, refer to this page.
I founded the CMSE graduate linear algebra bootcamp. One of the core courses for the PhD in CMSE is Numerical Linear Algebra; due to the diverse academic and professional backgrounds of the CMSE graduate community, some students have not taken undergraduate linear algebra before grad school, and many more haven't taken a linear algebra course or used its material in years. Accordingly, I organized a bootcamp with guided examples that lasted an afternoon the week before classes.
For more information, refer to this page.
I have an academic background in physics, math, and data science. Accordingly, I can teach courses that cover material of all three disciplinary areas, as well as those that are a mixture of them.
Some courses I am interested in teaching that are not as common yet are:
Fundamentals of Plasma Physics
Prerequisites: intermediate level of E&M
Suggested textbook: Bittencourt's Fundamentals of Plasma Physics
Applied Machine Learning
Prerequisites: introductory python
Suggested textbook: Géron's Hands-On Machine Learning with Scikit-Learn, Keras, & TensorFlow
I am also interested in developing curricula, and I have two ideas so far:
Survey of High-level Computational Research: Introduction to Real-World Processes and Methodology of Career Computational Research
Intuitive Physics: A Introduction to Physics Applications to Your Everyday, Lived Experiences
For more information, please refer to this page.