Available for opportunities · Bengaluru, India
B.Tech CSE student at PES University building production-grade AI systems — real-time computer vision pipelines, LLM-powered backends, scalable REST APIs, and edge-deployed ML models that work in the wild.
About Me
I'm an AI/ML Engineer & Full-Stack Developer who builds things end-to-end — from training deep learning models to shipping them behind production-grade FastAPI backends, containerized with Docker, running on edge hardware or in the cloud.
My interests span Computer Vision, LLM & GenAI integrations, ADAS systems, and real-time inference on constrained devices. I care about the full pipeline: data, architecture, optimization, deployment, and observability.
When I'm not training models, I explore biomedical AI, systems programming, and building developer tools — because great engineers understand the whole stack.
Career
Selected Work
Multi-omic ML framework using Graph Neural Networks and co-attention mechanisms to predict NAFLD progression from MRI scans and multi-omic profiles. Leveraged SHAP and LIME for XAI-driven interpretability, enabling personalized risk stratification and biomarker discovery.
Architected a secure, multi-threaded client-server system supporting remote file upload, download, delete, and listing over TLS-encrypted sockets. Implemented concurrent multi-client handling with threading for high scalability on Linux VMs.
Fully configurable multi-level cache simulator supporting Direct Mapped, Fully Associative, and Set Associative caching policies. Integrated LRU, FIFO, and Random replacement strategies with accurate hit/miss rate simulation using real-world memory access traces.
Technologies
Toolkit
Let's Connect
Open to AI/ML engineering roles, research collaborations, and interesting problems at the intersection of computer vision and real-world deployment.