Designing AI systems for decisions that can’t wait.
Data Science @ Boston University. Passionate about using machine learning to solve real problems where the stakes are high.
Long-term, I'm interested in applying AI in mission-critical, time-sensitive environments where rapid, reliable decision-making is essential.
Trained a modified ResNet50 classifier with AdamW + cosine LR scheduling. Applied UMAP and distance-based outlier detection to flag noisy images and visualize dataset structure.
View on GitHub →Automated data pipeline to scrape and structure financial metrics, integrating live market data via yfinance. Rule-based valuation framework using P/E ratios, revenue growth, and earnings trends.
View on GitHub →End-to-end CNN/Transformer pipeline for endometrial cancer detection from ultrasound images. Achieved 89% classification accuracy using contrastive learning and custom feature engineering.
Full-stack React application built for a Georgia Tech behavioral study exploring how physical effort influences decision-making, enabling real-time experimental tasks and structured participant data collection.
View on GitHub →Open to research collaborations, internship opportunities, and interesting conversations.