Courses

I have electronic notes, old exams, and problem sets for each of the courses below. Feel free to contact me for any of these resources.

Courses Taught at University of Maryland
  • Spring 2020
    • MATH 136 : Calculus for Life Sciences

Courses Taught at Morehouse College
  • MATH 120 : PreCalculus
  • MATH 130 : Basic Statistics
  • MATH 160 : Calculus for Business
  • MATH 161 : Calculus I
  • MATH 162 : Calculus II
  • MATH 255 : Set Theory
  • MATH 321 : Intro to Ordinary Differential Equations
  • MATH 467 : Numerical Analysis
  • MATH 497 : Senior Seminar
Short Courses
  • Advanced Calculus / Real Analysis
  • Introduction to Matlab and dynamical systems
  • What is Data Science?
   

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Undergraduate Mentoring

I have had the pleasure of directing a number of undergraduate research projects. This has helped me gain both research and mentorship skills. Below, I offer brief descriptions of a selected undergraduate projects that I have directed.

(* Went on to Graduate School)
  • Ernest Holmes (Aug 2019 - May 2019)
    Separating Data using Multi-layered Neural Networks

  • Nicholas Arosamena, Storm Chin, Frederick Jackson, Johnathan Russ (Jan 2019 - May 2019)
    Image Reduction using Singular Value Decomposition

  • Franck Nijimbere** (Jan 2018 - May 2018)
    Approximation Theory: A Bitcoin Case Study
    ** Class of 2020 Rhodes Scholar

  • Khensu-Ra Love El*, Darian Nwankwo*, Tyree Stevenson, (Jan 2017 - May 2018)
    Determining Near-Optimal Treatment Protocols via ODE Cancer Models

  • Lauren Casper, Alexandra Lara, Luc Olivier, Summer 2016
    Modeling Within-Host Dynamics of Schistosomiasis

  • Talon Johnson* (December 2014- May 2016)
    A Bio-mathematical Approach to the Stability of HIV and AIDS

  • Aquia Richburg* (January - May 2015)
    Modeling the Brain Using Math : Neural Networks and Liquid State Machines

  • Tre Wells* : (January - May 2014)
    Agent-Based Models of Transmission of Infectious Disease In Medical Facilities

  • Zerotti Woods* (January - May 2014)
    ODE Model Reduction Using Quasi-Steady State Approximation (QSSA)

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