About Me
AI/ML engineer with hands-on experience in Computer Vision and LLM-based systems, focusing on building end-to-end AI pipelines from data preprocessing to deployment. Experienced in RAG pipelines, real-time CV systems, applied deep learning and Agentic AI.
Skills & Technologies
Work Experience
Python Intern
Automated data processing workflows using Python scripts, reducing manual processing time by 40%. Cleaned and structured datasets for internal reporting and analytics, collaborating with team members to improve data reliability and workflow efficiency.
AI Trainee
Built an AI-powered health assistant using LLM APIs for chatbot interaction and calorie estimation. Integrated external AI APIs and handled structured user input/output pipelines, working on prompt design and response evaluation.
Projects
IntelliVision: Real-Time Multi-Object Tracking & Event Detection Platform
Built a real-time multi-object detection and tracking system using YOLOv8 and DeepSORT to analyze live video streams and identify human activity and motion events. Implemented automated event-based logging with time-stamped video clips and snapshots for surveillance and monitoring use cases.
DocuMind AI: Retrieval-Augmented Knowledge Intelligence System
Developed an LLM-powered RAG system for context-aware question answering over custom document collections. Built a document ingestion pipeline with chunking and embedding-based retrieval for efficient knowledge access.
AgroSmart AI: Predictive Irrigation & Water Optimization System
Developed an AI-driven irrigation control system using sensor data and ML-based predictions to support precision farming. Automated watering decisions based on soil moisture and environmental conditions for efficient resource usage.
Education
B.Tech in Computer Science (AI & ML)
Computer Science