## 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.

### Example Computational tutorials

**Basic DNA Sequence Analysis**

Tutorial NotebookData Set

A tutorial on using DNA sequence to understand the biogeography of Skinks on Fernando de Naronha. This tutorial is written to given an introduction to basic programming skills with Python and provides introductory intuition on how DNA sequence can be used to
identify relationships between species.

**Euler-Forward Integration**

Tutorial Notebook

This tutorial was used to teach undergraduates how to integrate ordinary differential equations using the Euler-Forward method.

**Stochastic Simulations**

Tutorial Notebook

A primer on using the Gillespie algorithm to understand the dynamics of constitutive expression.

**Quantitative Image Processing**

Tutorial NotebookData Set

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.

**Bifurcation Analysis of an Autoactivation Circuit**

Tutorial Notebook

This tutorial explores the dynamics of an autoactivation genetic circuit and explains the origin of bifurcations.

**Chemical Master Equations**

Tutorial Notebook

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.

**Human Impacts by the Numbers**

2020

A zoom-based course open to the public which gave a wide view of all the ways in which human action changes the face of the planet.

**Evolution **

2020

A course for upper-level Caltech undergraduates which provides a quantitative and qualitative summary of biology’s greatest idea — evolution.

**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.