About
I'm a student studying Computer Engineering & Statistics at UIUC, constantly learning how math and code can come together to solve real-world problems.
I've built sentiment-analysis pipelines, explored 3D graphics research in Unreal Engine, and prototyped fraud-call detectors using NLP.
Outside of programming, you'll find me watching UFC fights, playing soccer and basketball with friends, or relaxing to some Bossa Nova.
Projects
Personal Portfolio Website
A modern, responsive portfolio website showcasing my projects and skills with smooth animations and a clean design.
NBA Player Valuation Model
Developed a machine learning pipeline to predict NBA player value (VORP) using advanced feature engineering and Gradient Boosting, achieving a test R^2 of 0.90.
Fraud Call Detection Model
Used NLTK and bag-of-words to vectorize call transcripts and built a logistic regression pipeline with scikit-learn, achieving 89% accuracy in detecting fraud.
Link Analyzer
A full-stack web application that analyzes websites by extracting metadata, counting links and images, and providing valuable insights about web pages.
MRI Classification Model
Built a deep learning pipeline in PyTorch for brain MRI classification and tumor segmentation, integrating 2D/3D CNNs with advanced loss functions. Added uncertainty estimation (MC Dropout) and explainability (Grad-CAM) to highlight suspicious regions. Achieved 89% classification accuracy and 90% segmentation accuracy on a dataset of 3,200+ MRIs using Python, NumPy, and scikit-learn for preprocessing and evaluation.