CS + Econ @ JHU. Interested in AI, math, and building things that matter.
I'm a CS + Econ student at Johns Hopkins, with minors in Applied Mathematics & Statistics, and Financial Economics (maybe computational medicine too?).
I'm passionate about building projects/research/startups with tech that have the potential to help people. I like to view technology in terms of its beauty but also the impact it can have on people.
I am currently working on CS and econ research at Johns Hopkins. I am building Delineo (working with WHO to simulate and stop diseases), researching causal inference in empirical studies through the BDP research fellowship, helping build BlueJay programming language, and working on an upcoming NLP project.
Aside from research and software engineering, I love creating community of people who love CS and econ as much as I do. Fall 2025: Starting Data Science Club @ JHU, VP @ HopAI, Secretary @ WiCS and Treasurer @ SWE. When I'm not working on a structured projects, I like learning for fun (currently learning: language modeling).
Highlights from my work in AI, research, and engineering

Paper with the Computational Social Sciences Lab at JHU:
Devising new sampling method to represent diverse perspectives for LLM training datasets. Under submission to ACL ARR and COLM.
Advisor: Dr. Kristina Gligorić

Working with WHO and Ruvos to make a disease modelling platform that can demonstrate the spread of diseases at a small town level with different interventions. Presented at JHU Design Day and DREAMS, won Dean's Design Award in Computer Science. Read more here.
Advisors: Dr. Anton Dahbura, Dr. Kimia Ghobadi

Winning project at TreeHacks (Stanford's hackathon). Built a full-stack application under 36 hours. Stack overflow like platform for AI agents to ask each other questions and improve efficiency. Won Best Use of Multi Agent Systems by Fetch.ai ($1500) and Best Use of Runpod Flash ($3090).

Paper with the Computational Social Sciences Lab at JHU:
Multi-Perspective LLM Annotations for Valid Analyses in Subjective Tasks. Under submission to ACL ARR and COLM.
Advisor: Dr. Kristina Gligorić

Working with WHO and Ruvos to make a disease modelling platform that can demonstrate the spread of diseases at a small town level with different interventions. Presented at JHU Design Day and DREAMS, won Dean's Design Award in Computer Science. Read more here.
Advisors: Dr. Anton Dahbura, Dr. Kimia Ghobadi

Using unsupervised learning models (clustering, double machine learning) to answer causal inference questions using disease modeling: e.g. how much does an intervention help?
Advisors: Dr. Anton Dahbura, Dr. Kimia Ghobadi

Received a $6000 award (Bloomberg Distinguished Professor Summer Research Fellowship) to work on analysing and categorizing causal inference in empirical economics studies. Analyzed hundreds of papers. Explored different mathematical techniques to infer causal relationships.
Advisor: Dr. Paul Ferraro (Bloomberg Distinguished Professor)
Working with JHU Programming Languages lab to develop and test a new semantically typed programming language: BlueJay. BlueJay is a novel language with a semantic type checker for bug finding.
Advisors: Dr. Scott Smith, Brandon Stride (grad student)

Winning project at TreeHacks (Stanford's hackathon). Built a full-stack application under 36 hours. Stack overflow like platform for AI agents to ask each other questions and improve efficiency. Won Best Use of Multi Agent Systems by Fetch.ai ($1500) and Best Use of Runpod Flash ($3090).

Built at Technica Hackathon. A blockchain-based platform to enable transparent and accessible microfinance loans for underserved communities.
Winner of the Claude Hackathon. An end-to-end accounting system powered by AI: automates bookkeeping, categorization, and financial reporting.

Made at HackMIT with Sutharsika, Jane, and Sunny.
AI agent pulls data about companies and builds a graph, then a prediction algorithm forecasts company performance.

Launched the Data Science Club at JHU as Club President and built a website for it. Our mission is to give students the skills and opportunity to work on impactful data projects.
Selected for Goldman Sachs' Emerging Leader Series. Built a mutual funds analysis tool to help surface insights for investment decision-making.
Data science project analyzing how LLM adoption has affected productivity and labor markets across different industries, using econometric methods to quantify the impact.
Academic & Industry Research
Academic Support & Mentoring
Building Community & Mentoring