Teaching has played an integral role in my development as a scientist. I am interested in teaching interdisciplinary methods to approach biological questions across all scales drawing heavily from physics and mathematics as well as from the computational sciences.
Computational tutorials for Bi1 - The Great Ideas of Biology
Euler-Forward Integration | This tutorial was used to teach undergraduates how to integrate ordinary differential equations using the Euler-Forward method.
Stochastic Simulations | A primer on writing stochastic simulations and using them to understand one of the most powerful forces of evolution - genetic drift.
Quantitative Image Processing | This tutorial covered the basics of quantitative image processing and led students through segmentation of single-celled bacteria to compute the intensity distribution of a YFP reporter gene. [data set]
Chemical Master Equations | Chemical master equations are incredibly useful in understanding the “rates and weights” of biological processes. This tutorial teaches the student how to write them and explore their behavior computationally.
Other Classes At Caltech & Beyond
Below are links to the various courses I have had the privilege to TA.
Bi1 - The Great Ideas of Biology : A freshman biology course for non-biology majors which teaches the fundamental principles of modern biology with an emphasis on calculation and quantitative thinking.
Physical Biology of the Cell [2018, 2017, 2016, 2015]: This courses takes a in-depth view at the investigation of biological phenomena using principles from physics. Typical topics of inquiry are dynamics of the cytoskeleton, back-of-the-envelope estimation, genetic regulation, cellular signaling, and evolution. This course is taught all over the world at universities such as Caltech, GIST, and Cold Spring Harbor Laboratory.
Intro. to Programming in the Biological Sciences : A week long course attended by undergraduates, graduate students, and post-docs which teaches the principles of programming and its application to real-life biological problems.
Data Analysis in the Biological Sciences [2016, 2015]: This course exposes undergraduates, grad students, and post-docs to practical data analysis using Bayesian inferential methods such as parameter estimation, hypothesis testing, and regression. The homework assignments are almost completely open ended and often involve cutting-edge data from Caltech and beyond.
Bi1x - Exploration through Experimentation [2015, 2014]: A course aimed at freshmen undergraduates which teaches the “great ideas of biology” through experimentation. Students perform a variety of experiments including single-cell microscopy, optogenetics, and DNA sequencing.