June 2023 - Present
University of California, Riverside
Human skin model with various cell types focused on understanding aging mechanisms
Agent-based modeling
Multiscale modeling
Parallel computing
High performance computing
MATLAB
C++
June 2024 - Present
University of California, Riverside
Model of cell dynamics during keloid scar expansion in collaboration with biologists from UC Irvine
Agent-based modeling
Multiscale modeling
Parallel computing
High performance computing
MATLAB
CITI Responsible and Ethical Conduct of Research Training
Dr. Yingzi Liu
Dr. Christain Fernando Guerrero-Juarez
Vargas Casillas, A. (2025). Multiscale Model of Keloid Scar Expansion. Open Research and Creative Activities Forum, 1(1). http://dx.doi.org/10.5070/J9.48778 Retrieved from https://escholarship.org/uc/item/6r80j2c2
Manuscript in progress
March 2025 - Present
University of California, Riverside
Collaborated with external program evaluators and with the office of Institutional research to safeguard data and comply with IRB policies
Program goal is to support incoming first-year undergraduate students
CITI Social & Behavioral Research Training
Program evaluation
Website development
Data analysis
Event organization
Program and peer mentorship organization
August 2017 – June 2018
Rhode Island College
Solved for periodic solutions to an IVP that modeled the Tacoma Narrows Bridge to better understand the 45 minutes of oscillations before its collapse in 1940
MATLAB (Octave)
ODE
PDE
Optimization
Newton's Method
Steepest Descent
Humphreys, Lisa D., and P. Joseph McKenna. “When a Mechanical Model Goes Nonlinear: Unexpected Responses to Low-Periodic Shaking.” The American Mathematical Monthly, vol. 112, no. 10, 2005, pp. 861–75. JSTOR, https://doi.org/10.2307/30037627. Accessed 3 Oct. 2025.
Humphreys, L. D., and R. Shammas. “Finding Unpredictable Behavior in a Simple Ordinary Differential Equation.” The College Mathematics Journal, vol. 31, no. 5, 2000, pp. 338–46. JSTOR, https://doi.org/10.2307/2687447. Accessed 3 Oct. 2025.
September 2016 – May 2017
Rhode Island College
Honors Project that focused on an application of Markov chains to Game 6 of the 1986 World Series
Data analysis
Markov chains
Probability
Statistics
Excel
Professor David Abrahamson