AI-powered Streamlit platform that converts long-form lecture audio into structured notes, quizzes, and flashcards using Whisper + transformer summarization models with GPU-tuned ASR/VAD.
Modular NLP components with caching and parallel chunking deliver 5× faster runs on 30+ minute inputs, while the interface adds progress tracking, Fast Mode, and PDF/DOCX/JSON exports.
EfficientNet-B0 classifier covering 7 skin lesion classes with 81% validation accuracy and 0.67 macro-F1 on HAM10000, accelerated via AMP and optimized Albumentations pipelines.
Integrates Grad-CAM explainability, macro-F1 driven evaluation, and a <50 ms Streamlit inference UI for clinician-focused prototyping.
Converted GitHub repos into interactive UML class diagrams across 7+ languages using AST parsing + AI enrichment; reduced manual diagramming effort by ~80% with one-click export.
Built an end-to-end pipeline on Windows: traffic generation (VoIP/FTP/HTTP), PyShark/TShark capture to CSV, sklearn model (~0.999 acc), and real-time shaping via Windows Firewall with safe rollback.
Developed and deployed a full-stack MERN + Cloudinary platform supporting 200+ campus users, cutting lost-item recovery time by 60% with streamlined reporting and secure JWT flows.
Enhanced backend efficiency by 35% through modular Express controllers, indexed MongoDB queries, and Cloudinary-driven media storage designed with RESTful best practices.
Increased user engagement by 45% via a responsive Tailwind UI, reusable components, and real-time status updates that raised report completion and item return confirmations.
Full-stack agricultural fintech platform using Flask, enabling 500+ farmers to manage crop insurance and loans with role-based access control, reducing manual errors by 70%.
Full-stack AI-powered search tool using FastAPI and React, expanding queries with NLP (T5/BART) and integrating Google/YouTube APIs with multithreaded backend for enhanced performance.
Real-time fog detection system using FastAPI and Next.js with dual-mode interfaces, implementing OpenCV-based analysis to classify visibility conditions and provide driving recommendations.
Flask-based NLP dashboard analyzing Reddit posts from financial subreddits using VADER sentiment analysis, with interactive dark-mode UI and Matplotlib visualizations.
Implementation of classic computer science problems: Dining Philosopher problem for OS synchronization using semaphores, and Word Ladder problem using graph traversal algorithms with optimized pathfinding strategies.