Aarya Gandhe

I’m a software engineer and embedded ML researcher who enjoys turning prototypes into production-ready systems. As a Junior Software Intern at Vulnuris security solutions, I architected and deployed a production-ready application on AWS (EC2, S3, DNS, Amplify), scaled it for real-time load, optimized CI/CD pipelines, and automated infrastructure to reduce manual setup time. I also supported production with software monitoring and built an ML algorithm to analyze and automate the workflow of prowler.

At IIT-Bombay, I designed and implemented a wireless sEMG acquisition and transmission pipeline using Muscle BioAmp Candy and Python, then brought gesture intelligence to embedded firmware by implementing threshold-based gesture classification in embedded C to detect open, close, and pinch. I integrated PWM-controlled servos and achieved end-to-end latency of 50–80 ms for muscle activation, enabling real-time remote transmission for monitoring and analysis. I bring this same end-to-end mindset to my projects—like an sEMG rehabilitation glove using ESP-NOW and Deep Learning models such as a CNN for brain tumor classification (87% accuracy) and a ResNet-based Ayurvedic plant identification app with full offline support.