I'm a passionate Computer Science major with a minor in the Mathematics of Finance, curious about how data and algorithms can drive better decision-making—especially in the world of finance. I enjoy working on projects that have real-world relevance and lead to insights that matter. I grew up coding and have fond memories of building games on Scratch as a little girl. Since then, my curiosity about the many ways technology can be applied has only grown.

Outside of tech, I love trying new recipes, watching Formula 1, or getting lost in a good book.

Projects

Finsense

Work in Progress

A personalized financial research assistant that combines live market data, news events, and risk analysis through modular MCP servers. Built with FastAPI, deployed on Vercel with intelligent AI coordination for multi-source financial insights.

Python Agentic AI MCP Claude Code Groq API Vercel Render

F1 GP Predictor

A pipeline that extracts FastF1 session laps, builds race data CSVs grouped by driver, and trains/predicts driver performance for the 2025 F1 Abu Dhabi Grand Prix.

Python FastF1 pandas Scikit-Learn Matplotlib NumPy Neural Networks

Rescura

Rescura was built at HackPrinceton (fall 25) in 36 hours to detect and aid those facing health emergencies, especially in rural areas by detecting ECG and motion data from an inexpensive wearable and contacting emeregency services and guiding bystanders through CPR.

Python Light GBM Data Transformation

Gaia

Winning 1st place at GirlHacks 25, Gaia is a web application with a dynamic AI chatbot designed to support women on campus by connecting them with resources, guidance, and community!

Python Gemini AI API

Easy S&P

Easy S&P is a stock screener that allows user to filter stocks by sector and sort them by key metrics. Future updates will include availability online and a news sentiment analyzer built using AWS Sagemaker.

Python SQL yfinance SQLAlchemy pandas Matplotlib FastAPI HTML/CSS

Banking Campaign Predictor

Implemented a Random Forest Classifier on the Banking Data - Marketing Targets dataset from Kaggle to predict whether a customer would subscribe to a term deposit.

Python Scikit-Learn pandas Matplotlib Seaborn Random Forest Classifier

NY Graduation Model

Trained a Multiple Linear Regression model on the 2005-2015 Graduation Rates Public - School dataset from NYC Open Data to predict Total Grad percentages.

Python Scikit-Learn pandas Seaborn Matplotlib Multiple Linear Regression

Credit Predictor

Trained a Random Forest Classifier model on the German Statlog Credit Dataset to determine whether a potential customer was credit-worthy or not.

Python Scikit-Learn pandas Matplotlib Random Forest Classifier

Mini-Projects

Descriptions of and my code for simple scripts, mini-projects, and more.


Certifications

AWS Certified Machine Learning Engineer – Associate AWS Certified AI Practitioner Badge C++ Certified Associate Programmer Badge

Skills

Programming Languages

Python SQL (MySQL) C/C++ Java

Tools/Platforms

Git Linux AWS Sagemaker AWS Lambda AWS S3 AWS RDS AWS IAM Jupyter Notebook Google Colab Visual Studio Code PyCharm IntelliJ MS Excel Anaconda

Libraries

FastAPI Scikit-Learn pandas NumPy Matplotlib Seaborn