Motivated and detail-oriented Engineering graduate with knowledge of Data Analytics, Machine Learning, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG). Skilled in Python, data analysis, prompt engineering, and AI-driven application development. Passionate about leveraging AI and machine learning technologies to solve real-world problems and eager to contribute to innovative projects while continuously expanding technical expertise in Data Analytics, AI, and Generative AI.
Technical Skills
Programming: Python, SQL
AI/ML: Machine Learning, Data Analysis, Deep Learning Fundamentals
Generative AI: Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Prompt Engineering, LLM Evaluation, AI Agents
RAG Technologies: Vector Databases, Embeddings, Semantic Search, Document Retrieval, Knowledge Base Systems
LLM Frameworks: LangChain, LlamaIndex, Hugging Face Transformers
MLOps & LLMOps: CI/CD for LLM Applications, Model Monitoring, Automated Evaluation Pipelines, Experiment Tracking
AI Security & Governance: LLM Guardrails, AI Safety, Content Moderation, Secure AI Gateway Design
Tools & Platforms: Git, GitHub, Jupyter Notebook, VS Code, Docker
Soft Skills: Problem Solving, Analytical Thinking, Team Collaboration, Communication
Self-Healing RAG Pipeline
• Developed an intelligent Retrieval-Augmented Generation (RAG) system capable of detecting retrieval failures and improving response quality through iterative retrieval and validation.
• Implemented document ingestion, embedding generation, vector search, and response evaluation workflows.
• Improved answer accuracy and reliability by integrating self-correction mechanisms within the RAG pipeline.
AI Medical Chatbot
• Built a medical chatbot using Python and Large Language Models (LLMs) to answer basic healthcare-related queries.
• Integrated natural language processing techniques for user interaction and information retrieval.
• Developed a conversational interface for efficient and user-friendly query handling.
• GitHub: github.com/SatyamGangwar90/Medical-AI-Chatbot
Simulation-Based Load Flow Analysis on IEEE 13-Bus System (MATLAB)
• Implemented the Forward–Backward Sweep algorithm for load flow analysis in a radial distribution system.
• Calculated bus voltages, voltage drops, line currents, and power losses.
• Evaluated system performance under varying loading conditions using MATLAB simulations.
• Strengthened understanding of power system modeling, numerical methods, and simulation techniques.
Minor Projects
• Automatic Street Light Control Using LDR.
• Temperature Monitoring System Using LM35 Sensor.
• Overcurrent and Earth Fault Relay Study (Laboratory-Based).
ACHIEVEMENTS & HACKATHONS
• Top 10 Team – SuperHack 2025 Global AI Hackathon (SuperOps, AWS & Hack2Skill) | January 2026
• Developed and presented an AI-powered solution leveraging Generative AI concepts for real-world IT management challenges.
• Collaborated in a competitive global hackathon environment, applying problem-solving, innovation, and AI engineering skills.
• Recognized among the Top 10 teams for technical implementation and innovative approach.