An agent-based educational system using FastAPI, LangChain, and LangGraph in a microservice architecture. Implemented real-time async endpoints, integrated Whisper for audio/video transcription, and PyMuPDF for PDF parsing. Built a RAG-based QA pipeline with embedding-based retrieval, and AI agents for question generation, summarization, and feedback refinement. Optimized for scalable human-in-the-loop workflows and efficient content transformation across diverse formats.
A modern implementation implemented a Hierarchical Deep Temporal Model for Group Activity Recognition, based on the CVPR 2016 paper. Achieved 93% accuracy using a two-stage LSTM architecture to recognize multi-person activities. Conducted ablation studies to evaluate the contributions of various model components and compared performance against 8 baseline models.
ImgCap is an image captioning model designed to automatically generate descriptive captions for images. It has two versions one based on a CNN-LSTM architecture, and the other an enhanced version that integrates a CNN-LSTM with an Attention mechanism. To further enhance the quality and coherence of generated captions, beam search is implemented during the inference stage.
Credit card fraud detection project using a highly unbalanced Kaggle dataset of 284,807 transactions with only 492 frauds. To address the imbalance the project implements a voting classifier and a neural network with focal loss in PyTorch achieving an F1 score of 86% and a PR AUC of 85%
Tennis-Analysis-System is a system that analyzes tennis matches and provides player statistics and mini court visualizations.