Charan Kumar

I am a motivated AI/ML developer pursuing a B.Tech in Computer Science and Engineering, focused on building real-world intelligent systems and scalable AI applications. My work blends deep learning, applied machine learning, and web/backend development to deliver user-focused solutions.

As a research intern at NITK Surathkal, I developed XAI-based interpretation models for classification tasks, applying LIME, SHAP, and feature-attribution methods to analyze model decision behavior and visualize feature contributions. I contributed to experimental reporting and interpretability comparisons across multiple models.

My projects include an AI Meeting Assistant with Whisper and RAG, a live video transcriber using OpenCV and Google STT, an AI NewsReel generator, a Ruby-based AI voice assistant with document Q&A and local automation, and a movie ticket booking system. These projects emphasize real-time processing, integrations, and end-user automation.

I published an energy-prediction study using Random Forest (IEEE INDICON 2025) achieving 97.8% R² and 98.8% accuracy, and I’ve been recognized as a hackathon finalist and top-50 team member at national competitions. I seek opportunities to apply applied AI and LLM systems in production environments that value impact and continuous learning.