1. Information and signaling mechanisms in neurons and circuits.

    This is a popular computational neuroscience course, taught by my thesis advisor Steve Baccus. The course examines how cellular properties (such as membrane time-constants) and circuit properties (such as synaptic depression) are used to implement interesting computations. I’ve served as the course TA twice.

  2. Analysis techniques for the biosciences using MATLAB.

    This course introduces fundamentals of software design and data processing tools in Matlab, geared towards biological science graduate students. Statistics, linear algebra, dimensionality reduction, model-fitting, image and signal processing, and simulations are common topics.

    The course also introduces students to basic software engineering principles and best practices, include basic programming and debugging; data structures and algorithms; code structure and commenting; and version control systems.

  3. Stanford Institutes of Medicine Summer Research (SIMR).

    SIMR is an intensive summer program in which high school students perform basic scientific research in labs throughout the biological sciences at Stanford. In 2013-2015, I presented an introduction to the visual system to the SIMR students, aimed an providing a high-level survey of the scientific questions and methodologies used to study visual information processing. Slides for the most recent year can be found here.