Teaching

During the academic year 2022-23 I am thrilled to be a Project NExT fellow in the Red'22 cohort!  This is a year long professional development program addressing all aspects of an academic career. 

During the academic year 2021-22 I completed the two following Fellowship programs. 

• Preparing Future Faculty Fellow, Duke University (awarded to five Duke university postdocs each academic year)

• Teaching for Equity Fellow, Duke University (year-long series of workshops designed to address topics around race and identity)

I have taught a variety of graduate and undergraduate level courses at Grinnell College, Duke University and at the University of Maryland. Below are some sample materials from classes I have taught in the past. 

Teaching Experience 

• Spring 2023, Multivariable Calculus and Differential Equations

• Fall 2022, Multivariable Calculus and Foundations of Analysis

• Spring 2022, Probability (Graduate-level class)

• Fall 2021, Probability

• Summer 2021, Applied Stochastic Processes (Graduate-level class)

• Spring 2021, Introduction to Real Analysis

• Fall 2020, Probability 

• Summer 2020, Probability

• Spring 2020, Probability and Elementary Differential Equations

• Fall 2019, Probability

• Summer I 2018, Elementary Calculus I

• Summer I 2017, Elementary Statistics and Probability

• Spring 2016, College Algebra and Trigonometry

Applied Stochastic Processes (Graduate-level class) Summer 2021

• Syllabus

• Sample Quiz

• Sample Class: Branching Processes

 Introduction to Real Analysis Spring 2021

• Syllabus

• Sample Quizzes: Short Quiz, Long Quiz

• Sample Classes: 

  1.  Bolzano-Weierstrass Theorem(Part I) 

  2. Bolzano-Weierstrass Theorem (Part II)

  3. Intermediate Value Theorem (Part I)

  4. Intermediate Value Theorem (Part II)

Probability Fall 2020 and Summer 2020

• Syllabus

• Midterm 1

• Sample Groupwork Problems: Groupwork, Solutions to Groupwork

• Sample Class: 

  1. Introduction to Continuous Distributions

  2. Uniform Distribution

  3. Exponential Distribution

  4. Normal Distribution

  5. Gamma Distribution

  6. Introduction to Random Variables

  7. Conditional Distributions