My Military Tactical Audio Enhancer used a GAN/Bi-LSTM architecture and voice activity detection to suppress non-stationary noise in battlefield radio audio. I optimized its inference pipeline to sub-15ms latency while achieving a 14–16 dB SNR gain, and presented the project at the Nitte Young Innovators Summit.
For Smart Algae, I built an IoT-based microalgal bioreactor with continuous air-quality monitoring and an ML model for real-time CO2 prediction and automated control. I presented the research at the Green Microbiology Summit 2026, where it won 3rd place at the CODERIUS IEEE paper competition.
As a Cybersecurity and ML Intern at Pas3CyberLabs, I built a Python logistics supply-chain risk prediction system and owned its pipeline from data preprocessing through model training and risk classification. At MUTBI - Manipal University Technology Business Incubator, I built a React.js application that automated patent offer-letter generation.
I'm currently a Python Developer Intern at Oasis Infobyte, building Python tools, backend API modules, and automated workflow scripts. I also built an agentic PDF extraction pipeline that converts unstructured documents into validated, schema-conformant JSON, with auto-correction and OCR fallback.
