srinu manchala

I’m a Machine Learning and AI Intern focused on building reliable AI/ML solutions and shipping them as usable products. I engineered an ML pipeline for breast cancer detection that reached 98.22% accuracy, improved diagnostic reliability, and supported real-time medical imaging workflows.

In my work, I don’t stop at prototypes: I systematically tuned models to reduce false negatives by 30% and increased inference performance by 25% to enable deployment. I also validate outcomes through experimentation, log analysis, debugging, and API testing.

I build full-stack and GenAI experiences as well—like a real-time MERN chat application handling 1000+ messages/day and reducing database latency by 35% with Redis caching and JWT authentication. I’ve also developed an EV analytics platform processing 10,000+ records and a scalable text-to-image system using Stable Diffusion with PyTorch, Docker, and AWS (CUDA-accelerated) to generate 100+ images per session.