I enrolled in my first operations research (OR) course as a first-semester sophomore at the University of North Carolina at Charlotte (UNCC). In almost every OR lecture that semester, I was amazed by the translation of real-world problems into the language of mathematics and, specifically, optimization. In our OR coursework, we graphed feasible regions and used the simplex method to visit the feasible region's extreme points to solve linear programs. In addition, we drew Markov chains and learned their elegant mathematical properties.
The following semester, I enrolled in a computational methods course that radically altered my perception of problem-solving. Throughout the semester, the computational methods course taught me how to take the mathematical concepts I practiced in my OR course and use programming to solve similar problems at a larger scale. I began to imagine creating broader impacts by applying OR methods to any global challenge. In the middle of the semester, I gathered my courage and attended my computational methods course's instructor's office hours to ask how I could help his research team during the approaching summer. In the years since, we have written two academic journal manuscripts together and are preparing a third as I continue to work toward a Ph.D. in Industrial and Operations Engineering.
Above: Global Wealth Report 2021 from Credit Suisse Research Institute
By Leandrosalvador - Own work, CC0, https://commons.wikimedia.org/w/index.php?curid=107566084
I am a first-generation (first-gen) college graduate. I am privileged to have received my BS degree and be working toward a Ph.D. degree. Still, there are significantly more challenges facing first-gen students than other generational students, while the number of challenges faced by first-gen students of color is even more significant. The experience of first-gen students, and in particular first-gen students of color, is one example of social inequality called educational inequality that persists in our 21st Century society.
Current outcomes in education, health, and overall life quality suggest that resource allocation globally is based more on social hierarchies (i.e., the common opinion of the class of a person defined using that person's race, age, gender, and/or other characteristics) than on merit (i.e., effort, talent, etc.) or other more equitable frameworks. My current research motivation is to move our society towards one that values social harmony and equity above wealth or social status.
In particular, how can we use IE/OR models to improve the allocation of critical need-based resources to achieve higher levels of fairness?
On the publications page, you will find that my colleagues and I have done work in these areas that aim to address social inequality:
United States' County-Level Pandemic Risk Prediction
United States' Heart Allocation Policy Analysis
Global Analysis of Genes Related to Antibiotic-Resistant Escherichia Coli