Incoming Summer 2025 🚀

Spearheading the development of new organization website.

Utilizing unsupervised learning to identify significant relationships between specific genes and radiotherapy treatment responses, enhancing treatment strategies for head and neck cancer patients. Enhancing the quality of training data by curating and optimizing datasets.

Migrating legacy website supporting 750+ campus students to a Svelte/React-based platform, improving performance and scalability for future growth.

Selected alongside four students of 200+ CS students for a 12-week program to develop an AI/ML project for public showcase and display. Spearheading the development of a PyTorch-based LSTM model for time series forecasting to predict stock market volatility with high accuracy. Implemented a SQL-based pipeline to ingest, temporarily store, and preprocess live stock market data from the Yahoo Finance API, ensuring seamless data integration for forecasting model. Enhanced model performance 30% by using daily batch training with new data through deployment on AWS

Created user authentication and managagment system. Worked closely with CEO to ensure speedy and effective launch.

Optimized the training and development of a Convolutional Neural Network (CNN) for radiological image classification by curating and preprocessing a dataset of 50,000+ MRI scans in MATLAB, enhancing model accuracy and reliability. Partnered with radiology graduate students to refine the CNN model training process, incorporating domain-specific insights to improve training strategies and ensure clinically relevant outcomes