Building RAG systems, VAE anomaly detection models, and FastAPI inference services.

• ✓Built a document question-answering system using Retrieval-Augmented Generation (RAG) with embeddings to generate context-aware responses.
• ✓Implemented text preprocessing, chunking, and semantic search using vector embeddings to improve retrieval relevance.
• ✓Developed a Variational Autoencoder (VAE) for feature learning and anomaly detection, improving data representation quality.
• ✓Evaluated model performance using standard metrics such as accuracy, reconstruction loss, and precision@k.
• ✓Integrated trained ML models into a FastAPI backend to provide prediction APIs for web-based applications.
• ✓Used Docker for local deployment and version control to ensure consistent development environments.

Led hardware intern team for Sewage Treatment Plant (STP) monitoring system.

• ✓Led the hardware intern team in researching and selecting industrial-grade sensors and devices for STP monitoring.
• ✓Conducted technical analysis of water treatment methodologies including biological, chemical, and filtration processes.
• ✓Evaluated water quality sensors (pH, turbidity, TDS, dissolved oxygen, flow sensors) for real-time monitoring applications.
• ✓Studied control units and automation systems including microcontrollers and PLC-based architectures for process regulation.
• ✓Assisted in designing a hardware framework for integrating sensors with monitoring and data collection systems.