Plotting a path to equitable education.

My name is Yesh Nagelli and I am a student researcher interested in computer science and machine learning.

Many problems persist in education today such as inequity, poor student outcomes, and lack of proper resources in many communities. I use computer science and machine learning to understand student outcomes, expand access to computing, and build tools that support educators.

Plainfield, IL · Class of 2027

Yesh Nagelli · founder · researcher · builder

Commit2Code

Founder & Chief Executive Officer

Growing up, I was fascinated by technology and computer science, but felt overwhelmed learning how to code on my own. A formal computer science class was not offered to me until my freshman year of high school. From that class, I learned so much about computer science, and had so many opportunities to collaborate with others and create things we were passionate about. I wanted everyone to have access to the same opportunity I did, especially younger students who lacked structured STEM programs in their schools.

I started Commit2Code to bridge the access gap in computer science. I developed a 12 week curriculum that teaches students to program in Python through short lectures, games, and projects. I have partnered with organizations such as the Boys and Girls Club of Joliet, Communities in Schools of Chicago, and the Plainfield Area Public Library to reach underserved students.

fig. 1 — Commit2Code, by cohort

50+ students reached, and counting.

Research

Independent research

Early Prediction of High School Dropout Using Machine Learning

Model deployed · paper submitted for publication

Why I did it

Throughout many of the classes I taught through Commit2Code, I noticed students began to stop attending or have irregular attendance. I started to consider the data and was fascinated by the similar characteristics of those who stopped attending. It was clear that there were some predictors of dropout.

I began to think about how dropping out of high school was common in many school districts near me and in some that I work with through Commit2Code. After talking with many teachers and administrators about the issue, I understood that it was too difficult for teachers to continuously monitor thousands of students to determine if they are at risk of dropping out.

What I did

I realized that data science and machine learning could be used to develop a model that can predict a student's likelihood of dropping out. Students at risk would clearly be flagged for administrators allowing them to extend additional support.

I used data from the High School Longitudinal Study of 2009 from the National Center of Education Statistics to train and test the model. Furthermore, I developed a 5-page research paper outlining my methodology in developing the model.

The model is currently deployed and free to use for teachers and administrators.

Where it is going

After deploying DropCast, I was left with more questions than I started with. I started to consider how educators could act on probability, how certain variables can build inequality into the model, and how the model could inform educator intervention. I want to learn more about machine learning and computer science to learn how models can provide useful and responsible insights. I want to continue to research how machine learning can further support educators and develop DropCast accordingly.

dropcast.org Try the model Open dropcast.org

BU RISE Data Science Practicum

I was selected into the BU Rise data science practicum program. Under this program, I researched machine learning methods for improving cross-region North Atlantic right whale upcall detection. I presented at the BU RISE symposium and devised a 5 page paper that was accepted into the IEEE MIT Undegraduate Research Technology Conference(URTC)

BU RISE research poster View full size

School Involvement

Computer Science Club

President

As president of my school's computer science club, I organized weekly coding competitions and tutorials to engage 50+ members in computer science. Tutorials I led included machine learning, APIs, and facial recognition. Furthermore, I launched team builds including an arcade machine and automated attendance system strengthing collaboration

Math Team

Competitor

I have been a competitor on my school's math team since freshman year. I placed regionally and competed at state 3 consecutive years.

Robotics Club

Founder

As someone who loved technology and valued educational equity, I was always frustrated by the fact that my school lacked a competitive robotics team. Since my sophomore year of high school, I worked closely with a club sponsor and school administration to start a team. I helped secure $2800 in funding through company sponsorships and prize money awarded in local competitions. Furthermore, I recruited underclassmen students and trained them across responsibilities to ensure long term program continuity .