Projects
A showcase of selected projects that highlight my experience in AI/ML, backend systems, and innovative engineering solutions.
LLM-Powered Medication Verification
Oct 2024
- Developed a multi-modal text extraction pipeline using Python OCR APIs and AWS Transcribe, increasing accuracy by 25% in processing images, ED notes, audio, and handwritten clinical notes.
- Optimized medication data organization with advanced prompt engineering using Gemini LLM, reducing reconciliation time by 50%.
- Architected high-performance backend REST APIs with the Django REST framework, improving response times by 60% and enhancing system efficiency for an Android application.
Food Classification Deployment Track
Dec 2023
- Maximized a food classification model using Transfer Learning with MobileNetV2, achieving 88% accuracy.
- Led the project from planning to deployment, utilizing Docker and Kubernetes to reduce resource utilization by 17%.
- Improved scalability and addressed deployment bottlenecks, enhancing response times by 85% and increasing overall project efficiency.
Beep Baseball
May 2023
- Researched and authored the project proposal, contributing to a team that secured $250 in funding for the project.
- Conducted rigorous testing on electrical components and collaborated with engineers to identify and resolve critical issues, reducing potential production errors by 30% and enhancing product reliability.
Neural Network Application
Dec 2022
- Implemented a perceptron training algorithm for image classification, achieving 92% accuracy on validation datasets.
- Optimized curve fitting using backpropagation, reducing error by 86%.
- Built a Python-based shape classification model, improving efficiency by 89%.