Teaching

Primary Instructor

Graduate-level:

1. Florida State University, Computational Probabilistic Modeling - ISC 5935 - Spring 2023

   • In this course, students are introduced to probabilistic programming and modeling for modern data science and machine learning applications. Algorithms for predictive inference are covered from a theoretical and practical viewpoint with an emphasis on implementation in Python. Topics include an introduction to probability and learning theory, graph-based methods, machine learning with neural networks, dimensionality reduction, and algorithms for big data.

2. Simon Fraser University, Mathematics of Data Science - APMA 940 - Summer 2021

• Theory and algorithms for problems in data science with an emphasis on mathematical aspects. Topics may include dimension reduction, supervised learning, including regression and classification, unsupervised learning, including clustering and latent variable modeling, deep learning, algorithms for big data, and foundations of learning.

Undergraduate-level:

1. Florida State University, Computational Probabilistic Modeling - ISC 4933 - Spring 2023

   • Undergraduate listing for dual-listed course ISC 5935. 

2. Simon Fraser University, Mathematical Topics in Data Science- MATH475 - Spring 2022

•  An exploration of the mathematics of data science. Analysis of the foundations of algorithms currently used in the field. Potential topics to be covered include: machine learning, compressed sensing, clustering, randomized numerical linear algebra, complex networks and random graph models. 

3. Simon Fraser University, Applied Linear Algebra - Math 232 - Spring 2020

4. Simon Fraser University, Applied Linear Algebra - Math 232 - Spring 2019

   • Linear equations, matrices, determinants. Introduction to vector spaces and linear transformations and bases. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. An emphasis on applications involving matrix and vector calculations.

5. University of Tennessee, Calculus I - Math 141 - Fall 2017

   • Single variable calculus especially for students of science, engineering, mathematics, and computer science. Differential calculus with applications.

Recitation Leader

1. University of Tennessee, Differential Equations - Math 231 - Fall 2016

   • First course emphasizing solution techniques. Includes first-order equations and applications, theory of linear equations, equations with constant coefficients, Laplace transforms, and series solutions. 

Supervision Experience

• Juan Cardenas, PhD student co-supervised with Prof. Ben Adcock in the mathematics department at SFU (Spring 2020-current)

• Sebastián Moraga Scheuermann, PhD student co-supervised with Prof. Ben Adcock in the mathematics department at SFU (Spring 2020-current)

The cover photo was taken at Schloss Dagstuhl – Leibniz Center for Informatics in Wadern, Germany.