RAGnarok 2.0
AI chatbot using Retrieval-Augmented Generation (RAG) to answer IIT Ropar-specific queries with vector databases and agentic architectures. Live: https://rag-narok.vercel.app/ | GitHub: https://github.com/aiclubiitropar/RAG-narok_2.0
AI & Deep Learning Researcher | Backend Engineer (Conversational AI)
B.Tech in Mechanical Engineering (CGPA: 8.74 / 10.0)
Minor Degree, Computer Science and Engineering
Senior Secondary (XII): 98.7% (2024) | Secondary (X): 96.6% (2022)
Backend Engineer (Conversational AI)
AI Data Consultant (Freelance)
Secretary
Languages: Python, C, C++, Bash, Java, SQL, JavaScript
AI / Machine Learning: PyTorch, TensorFlow, Deep Learning, GenAI, Retrieval-Augmented Generation (RAG), Computer Vision, Agentic Workflows, LangChain, Hugging Face, ROS2
Tools & Infrastructure: Linux/Ubuntu, Git, Docker, FastAPI, Vector DBs (FAISS, Chroma), CUDA, SolidWorks, ANSYS Fluent
AI system with vector database retrieval delivering accurate institutional responses for IIT Ropar.
Autonomous multi-agent financial analytics platform for processing high-volume live market data.
Custom CNN architecture generating high-fidelity intermediate video frames with perceptual loss.
Automated clash-free timetable generator resolving complex multi-department course constraints.
• AWS Certifications: AWS Machine Learning Foundations & Intro to ML: Art of the Possible
• Deep Learning: Coursera Deep Learning with PyTorch: Generative Adversarial Networks (GANs)
• Cisco: Introduction to Data Science
• InterIIT Tech Meet 13.0: Finalist representing IIT Ropar in competitive AI development
Saturday, August 29
AI Researcher · Backend Engineer
IIT Ropar
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