Aneesh Narayan Bandaru

I’m an AI/ML-focused B.Tech student in Data Science and Artificial Intelligence at IIIT Naya Raipur, where I build practical models with a strong emphasis on reliability and measurable impact. I bring a hands-on mindset across the full pipeline—from data preparation to deployment-ready evaluation.

In my internships, I translated research-grade ideas into working systems. At FinChain Labs, I engineered automated validation scripts for ACTUS DeFi contracts, improving logic consistency by 25% across 50+ scenarios and reducing edge-case discrepancies by 30% to better align with Radix DLT standards. At Digital Blinc, I improved NLP and healthcare vision performance by annotating 2,000+ samples to reduce hallucination rates by 15%, and by finding annotation inconsistencies in 500+ medical images to increase classification accuracy.

My projects reflect my drive to solve high-stakes problems with deep learning: I built an AI-Detection & Content Authentication System achieving 94.5% classification accuracy and enabling 100% traceability using invisible adversarial watermarking. I also developed therapeutic EEG & music emotion recognition reaching 92% valence-arousal accuracy, and an abdominal trauma 3D segmentation pipeline with 0.83 IoU. I’m especially motivated by work that blends GenAI/LLMs with robust evaluation—so teams can ship trustworthy AI systems.