Projects
From distributed message brokers to self-correcting AI pipelines. I design, build, and ship complete systems.
Software Engineer in my final year of Computer Science at Manipal, currently building fintech backend infrastructure at RupeeFlo. I work where distributed systems meet production ML.
From distributed systems to AI/ML pipelines,
here are some of the production-grade systems I've built.
Real-time chair occupancy detection using YOLOv11 and DeepSort with multi-camera spatial deduplication, hitting 30+ FPS across 10+ concurrent RTSP streams.
An automated VLM pipeline that generates structured scene descriptions from autonomous driving images. Features 8 prompt engineering strategies, an 8-metric evaluation framework, and an AI agent for error analysis.
An end-to-end multimodal deep learning system for marketplace price prediction. Trained on 1.48M Mercari listings with a BiLSTM + Attention + MLP fusion model achieving 0.430 RMSLE, beating XGBoost and LightGBM baselines. Full stack with FastAPI, Next.js, and MongoDB.
A fully deployed real-time fleet monitoring platform with FastAPI, Next.js, WebSocket live updates, OAuth 2.0 authentication, and geofencing. Live demo included.
A self-correcting Retrieval-Augmented Generation system with LLaMA3, ChromaDB, and hybrid BM25+vector search. Features hallucination detection and automatic query refinement.
A high-performance, fault-tolerant distributed message broker in Go with HashiCorp Raft consensus, partition sharding, ISR replication, gRPC transport, and topic-based pub/sub. Achieves 100K+ messages/sec.