The future of education lies in personalized and scalable solutions, especially in fields like computer engineering where complex concepts often challenge students. This talk introduces Lumina (AI Teaching Assistant), a cutting-edge agentic system designed to revolutionize programming education through its innovative architecture and teaching strategies. Built using OpenAI API, LangChain, RAG, and ChromaDB, Lumina employs an agentic, multi-modal framework that dynamically integrates course materials, technical documentation, and pedagogical strategies into an adaptive knowledge-driven system. Its unique "Knowledge Components" approach decomposes programming concepts into interconnected teachable units, enabling proficiency-based learning and dynamic problem-solving guidance.
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Speaker
Nittin Murthi Dhekshinamoorthy
3
talks
Nittin Murthi Dhekshinamoorthy is a computer engineering student and researcher at the University of Illinois at Urbana-Champaign. His work focuses on advancing artificial intelligence to address real-world challenges in education and technology, including developing an AI agent-based Teaching Assistant for scalable, adaptive learning. He has contributed to projects such as natural language-to-SQL systems and deep learning models for clinical image segmentation.
Bio from: Jan 30 - AI, Machine Learning and Computer Vision Meetup
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The future of education lies in personalized and scalable solutions, especially in fields like computer engineering where complex concepts often challenge students. This talk introduces Lumina (AI Teaching Assistant), a cutting-edge agentic system designed to revolutionize programming education through its innovative architecture and teaching strategies. Built using OpenAI API, LangChain, RAG, and ChromaDB, Lumina employs an agentic, multi-modal framework that dynamically integrates course materials, technical documentation, and pedagogical strategies into an adaptive knowledge-driven system. Its unique “Knowledge Components” approach decomposes programming concepts into interconnected teachable units, enabling proficiency-based learning and dynamic problem-solving guidance. Attendees will discover how Lumina’s agentic architecture enhances engagement, fosters critical thinking, and improves concept mastery, paving the way for scalable AI-driven educational solutions.
The future of education lies in personalized and scalable solutions, especially in fields like computer engineering where complex concepts often challenge students. This talk introduces Lumina (AI Teaching Assistant), a cutting-edge agentic system designed to revolutionize programming education through its innovative architecture and teaching strategies. Built using OpenAI API, LangChain, RAG, and ChromaDB, Lumina employs an agentic, multi-modal framework that dynamically integrates course materials, technical documentation, and pedagogical strategies into an adaptive knowledge-driven system. Its unique “Knowledge Components” approach decomposes programming concepts into interconnected teachable units, enabling proficiency-based learning and dynamic problem-solving guidance. Attendees will discover how Lumina’s agentic architecture enhances engagement, fosters critical thinking, and improves concept mastery, paving the way for scalable AI-driven educational solutions.