Meet the Researcher - Kavya Ravishankar

Breakout Room: 20

Kavya_R_HeadshotResearcher Name: Kavya Ravishankar
Title of Research: Modeling, Analysis, and Control of Student Loan Debt using Epidemiological Models
Division Representing: Mathematics and Computer Science
Institution: University of Pennsylvania
Institution Location: Pennsylvania
Home State: Oregon
District Number: 11
Advisor/Mentor: Padmanabhan Seshaiyer
Funding Source: N/A

Research Experience:  
My name is Kavya Ravishankar, and I am a student at the University of Pennsylvania's Jerome Fisher Program in Management & Technology. My work experiences are incredibly diverse and exhibit a standout theme of a fierce passion to make quality education globally accessible.My first volunteering experience was with VIDYA, an NGO that empowers and educates women and children in India. Here, I recognized the need for integrated solutions to combat challenges such as language and financial barriers. To tackle the problem my non-English speaking students faced when given English textbooks, I used my strong technical foundation to design a customized, multilingual online database of classroom materials that has sparked increased learning and performance in class. In high school, I learned about student loan debt's debilitating effects on the broader community. I was selected as a participant of the Aspiring Scientists Summer Internship Program to work with Dean Padmanabhan Seshaiyer from George Mason University, where I proposed to conduct research on the SEIR compartmental model of epidemiology to study student loan debt. I was later invited to present this research at the International Symposium for Bioinformatics and Ecology Education Research hosted by Illinois State University. On entering college, I joined the Penn Wharton Budget Model (PWBM), a research-based organization that provides an accessible economic analysis of public policy's fiscal impact. Working with Dr. Kent Smetters, Professor at the Wharton School and the Faculty Director of PWBM, I now conduct research that uses mathematical modeling and data-driven algorithms to optimize educational policy.

Presentation Experience: 
As the leader of my high school's State-level Mock Trial program, I have experience delivering speeches in courtrooms before judges, juries, and large groups of spectators. The intense, and often impromptu, nature of arguing in court has given me the necessary skills to coherently and concisely break down complex information and present it confidently to an audience.While conducting research with Dr. Padmanabhan Seshaiyer, I was selected to present my work to professors and graduate students at the International Symposium for Bioinformatics and Ecology Education Research. I demonstrated my understanding of the work and answered the audience members' academically nuanced questions.Additionally, while working as a Product Management Intern at NetSpeed Systems, a software company in California, I crafted a competitive analysis of NetSpeed's new product and eloquently articulated my findings at their Global Sales Kick-Off event. I also represented the company at the Design Automation Conference(DAC) in San Francisco, attended by over 2500 people.Furthermore, as a volunteer at VIDYA(an educational non-profit based in India), I have had a breadth of experience interacting with the underserved communities in Bangalore, India. I have been responsible for preparing and teaching engaging lessons for subjects including Math and Computer Science to students from 3rd to 12th grade. In addition, as an ambassador and outreach coordinator for the organization, I set up fundraising events where I spread awareness about the organization's reach and impact.

Significance of Research:       
Student loan debt is a debilitating problem that threatens a large subset of the American population. As of February 2019, the total amount of debt in the U.S. due to student loans amounted to $1.56 trillion. This paper works to mathematically model the student debt situation from the lens of an infectious disease contagion model. The study describes a belief proliferation model. Specifically, the spread occurs through the unfounded external reassurance to students that the value of their college education will amount to a future job that will enable them to pay off their loans in full and on time. Built on the classical SEIR compartmental model of epidemiology, this study analyzes the movement of individuals in the study set from the susceptible stage to the recovered stage using interconnected differential equations. We additionally consider an enhanced model to study the potential effect of an educational awareness program and the financial strain of the COVID-19 pandemic through respective optimal control variables. Utilizing Pontyagrin's maximum principle, the augmented model determines the ideal control value to mitigate the rate of students refinancing their loans when unable to meet the required payments.

Uniqueness of Research: 
The increasing cost of attending college has marginalized large segments of the population, forcing students to take on debilitating debt. My research innovatively models student loan debt as an epidemic that propagates through the social belief that an expensive higher education is worth the cost. The model accounts for relevant factors such as the financial impact of the COVID-19 pandemic.