Teaching

2020-present
University of Illinois Urbana-Champaign

STAT430 – Unsupervised Learning

This is an applied course in unsupervised learning. This course surveys some of the most commonly used clustering algorithms and dimensionality reduction algorithms currently used by data scientists. Students apply these algorithms to real and artificial datasets in Python.

Fall 2020, Spring 2021, Fall 2021, Spring 2022

2020-present
University of Illinois Urbana-Champaign

STAT207 – Data Science Exploration

Explores the data science pipeline from hypothesis formulation, to data collection and management, to analysis and reporting. Topics include data collection, preprocessing and checking for missing data, data summary and visualization, random sampling and probability models, estimating parameters, uncertainty quantification, hypothesis testing, multiple linear and logistic regression modeling, classification, and machine learning approaches for high dimensional data analysis. Students will learn how to implement the methods using Python programming and Git version control.

Fall 2020, Spring 2021, Fall 2021, Spring 2022

2018-2020
Duke University

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STA101 – Data Analysis and Statistical Inference

This course introduces students to the discipline of statistics as a science of understanding and analyzing data. Throughout the semester, students will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.

Fall 2018, Spring 2019, Fall 2019, Spring 2020

Summer 2015
North Carolina State University

MA111 – Pre-Calculus

Real numbers, functions and their graphs (special attention to polynomial, rational, exponential, logarithmic, and trigonometric functions), analytic trigonometry.

Fall 2012
North Carolina State University

ISE361- Deterministic Models in Industrial Engineering

Introduction to mathematical modeling, analysis techniques, and solution procedures applicable to decision-making problems in a deterministic environment. Linear programming models and algorithms and associated computer codes are emphasized.

Summer 2012
North Carolina State University

MA241 – Calculus II

Second of three semesters in a calculus sequence for science and engineering majors. Techniques and applications of integration, elementary differential equations, sequences, series, power series, and Taylor’s Theorem. Use of computational tools.

Summer 2011
North Carolina State University

MA141 – Calculus I

First of three semesters in a calculus sequence for science and engineering majors. Functions, graphs, limits, derivatives, rules of differentiation, definite integrals, fundamental theorem of calculus, applications of derivatives and integrals. Use of computation tools.

Summer 2010
College of Charleston

MATH104 – Elementary Statistics

Probability concepts, descriptive statistics, binomial and normal distributions, confidence intervals and tests of hypotheses.

Summer 2010
College of Charleston

MATH101 – College Algebra

Description
A course that emphasizes algebraic functions. Topics include algebraic equations and inequalities, and the properties and graphs of algebraic functions.


Spring 2010
College of Charleston

MATH105 – Business Calculus

A one-semester course designed to introduce the basic concepts of calculus to students who are not majoring in mathematics or the natural sciences. Emphasis will be on applications of calculus to various disciplines.

Fall 2009
College of Charleston

MATH111 – Pre-Calculus Mathematics

A course that emphasizes the function concept. Topics include graphs of functions, the algebra of functions, inverse functions, the elementary functions and inequalities.