# Teaching

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*

**Basic DNA Sequence Analysis** | A tutorial on using DNA sequence to understand the biogeography of Skinks on Fernando de Naronha. [data set]

**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.

** Physical Biology Bootcamp** [2019, 2018, 2017]

**:**An intensive week-long graduate course which teaches the utility of biological numeracy and its application from theory to experiment.

** Bi1 - The Great Ideas of Biology** [2017]

**:**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** [2016]

**:**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.