Statistics for Neuroscience Research
MIT, Spring 2021
A survey of statistical methods for neuroscience research. Core topics include introductions to the theory of point processes, the generalized linear model, Monte Carlo methods, Bayesian methods, multivariate methods, time-series analysis, spectral analysis and state-space modeling. Emphasis on developing a firm conceptual understanding of the statistical paradigm and statistical methods primarily through analyses of actual experimental data.
Topics in Neural Signal Processing
MIT, Spring 2020
A seminar course consisting of primarily guest lectures on modeling, estimating, and imaging neural signals. Topics included point process and state space modeling, source localization, stereo EEG, fMRI, MEG, Granger causality, and more. Students also did individual final projects on a topic of their chosing.
Fundamentals of Engineering
UCSD, Summer 2018
Part of the IDEA student center’s Summer Engineering Institute. Students learned the basics of Python and Arduino programming, fundamental math concepts from an engineering perspective, and engineering tools such as 3D-printers, laser cutters, and soldering irons. Students did final group projects using Arduinos.
Introduction to Engineering
UCSD, Fall/Winter/Spring 2015/2016
A one year series of seminar courses aimed at increasing engineering student retention by introducing fundamental math and programming concepts through hands-on engineering exercises. These seminars ultimately served as the foundation for the Fundamentals of Engineering course.