## Courses

## University of Alabama

**Fall 2023.**Math 311: Introduction to Scientific Computing and Problem Solving.

**Fall 2023.**Math 359: Mathematical Theory of Data Science.

**Math 311: Introduction to Scientific Computing and Problem Solving.**

Spring 2023.

Spring 2023.

**Math 421: Nonlinear Optimization.**

Spring 2023.

Spring 2023.

**Math 311/537: Introduction to Scientific Computing and Problem Solving.**

Fall 2022.

Fall 2022.

**Spring 2022.**Math 421: Nonlinear Optimization.

**Math 452/552: Math Stats II.**

Fall 2021.

Fall 2021.

**Fall 2021.**Math 520: Linear Optimization Theory.

**Spring 2021.**Math 421: Nonlinear Optimization.

**Spring 2021.**Math 451/551: Math Stats I.

**Fall 2020.**Math 520: Linear Optimization Theory.

**Fall 2020.**Math 355: Introduction to Probability.

**Spring 2020.**Math 300: Introduction to Numerical Analysis

**.**

Spring 2020.Math 410: Numerical Linear Algebra.

Spring 2020.

**Fall 2019.**Math 520: Linear Optimization Theory.

**Fall 2019.**Math 355: Introduction to Probability.

**Summer 2019.**Math 237: Introduction to Linear Algebra.

**Spring 2019.**Math 237: Introduction to Linear Algebra.

**Spring 2019.**Math 410: Numerical Linear Algebra.

**Fall 2018.**Math 300: Introduction to Numerical Analysis.

**Fall 2018.**Math 451/551: Math Stats with Applications.

**Spring 2018.**Math 421/521: Nonlinear Optimization Theory.

**Spring 2018.**Math 410/510: Numerical Linear Algebra.

**Fall 2017.**Math 420/520: Linear Optimization.

**Fall 2017.**Math 451/551: Math Stats with Applications.

**Spring 2017.**Math 302: Topics in Discrete Mathematics.

**Spring 2017.**Math 227: Calculus II (sections 005 and 006).

**Fall 2016.**Math 302: Topics in Discrete Mathematics.

**Summer 2016.**Math 237: Intro to Linear Algebra.

**Spring 2016.**Math 126: Calculus II.

**Spring 2016.**Math 421/521: Nonlinear Optimization.

**Fall 2015.**Math 126: Calculus II.

**Fall 2015.**Math 420/520: Linear Optimization.

**Summer 2 2015.**Math 125: Calculus 1.

**Summer 2 2015.**Math 112: Precalculus Algebra.

**Spring 2015.**Math 410/510: Numerical Linear Algebra.

**Spring 2015.**Math 300: Introduction to Numerical Analysis.

**Fall 2014.**Math 125: Calculus 1.

## California Institute of Technology

**Spring 2014.**ACM 270 Special Topics in Applied and Computational Mathematics: Numerical Optimization. course materials for ACM 270

**Fall 2013.**ACM 106a Introductory Methods of Computational Mathematics: Numerical Linear Algebra. course materials for ACM 106a

## University of Minnesota

**Fall 2012.**Calculus II. course materials for Calc II

## Undergraduate Research

## Fall/Spring 2015-16: UA Computer-based Honors Program

Myself and my student investigated the use of sparse regression techniques for predicting NHL hockey results and analyzing properties of successful teams; our results were presented at the 2017 Alabama Program in Sports Communication Symposium and summarized in the paper A sparse regression approach for evaluating and predicting NHL results.

## Fall/Spring 2014-15: UA Computer-based Honors Program

Myself and my students studied the use of network topology and clustering for the purpose of developing computer-based ranking systems in college football.

## Summer 2014: Caltech SURF (Summer Undergraduate Research Fellowships)

I participated in Caltech's SURF program this summer. Myself and my students investigated algorithmic approaches for optimization problems with explicit structural constraints (e.g. the solutions possess some block structure, or orthogonality, or sparsity, etc).

## Summer 2012: MAXIMA REU

In 2012, I participated in the MAXIMA REU program as a postdoctoral mentor. MAXIMA is a six week REU program in interdisciplinary mathematics hosted by Macalester College (MAX) and the Institute for Mathematics and its Applications (IMA). My team studied pursuit-evasion games in polygonal environments. Specifically, we designed a pursuit strategy for two pursuers and categorized classes of environments where two pursuers are able to capture their quarry following our leap-frog strategy; our results are summarized in the paper A Leapfrog Strategy for Pursuit-Evasion in a Polygonal Environment.

## Teaching Assistantships

## University of Waterloo

CO370 Deterministic Operations Research Models (W08, F09, W09, F10, and W11).

CO350 Linear Optimization (S08, S09, S10).

CO372 Portfolio Optimization (W10).

CO250 Introduction to Optimization (S11).

Math 115 Linear Algebra for Engineering (F07).

CO350 Linear Optimization (S08, S09, S10).

CO372 Portfolio Optimization (W10).

CO250 Introduction to Optimization (S11).

Math 115 Linear Algebra for Engineering (F07).

## University of Guelph

Math 2130 Numerical Methods (W06, W07).

Math 3240 Operations Research (F06).

Math 1200 Calculus 1 (F06).

Math 3240 Operations Research (F06).

Math 1200 Calculus 1 (F06).