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I'm Ramachandra

Software Engineer passionate about building elegant solutions to complex problems. Explore my background and my projects.

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About Me

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Ramachandra Yerramsetti

Software Engineer
Infosys Public Services

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Full-Stack Engineer with 4+ years of experience building production systems across Python, TypeScript, and AWS.

I specialize in AI-orchestrated pipelines and agent-driven workflows — from LangGraph-powered LLM systems and RAG pipelines to event-driven distributed architectures using RabbitMQ, SQS/SNS, and Lambda. I've shipped across healthcare AI, government compliance platforms, and national rail booking systems.

Currently at Infosys Public Services (DOL – New Jersey), where I own the backend for a statewide wage compliance platform and am building an ML-based job recommendation engine end-to-end as the sole developer.

I hold a Master of Engineering in Computer Science from the University of Connecticut (GPA: 3.81), where my work at UConn Health produced an autonomous image classification pipeline with 95% accuracy on AWS Lambda.

Stack: TypeScript · Python · FastAPI · React · Next.js · AWS (Lambda, SQS/SNS, DynamoDB, Terraform) · LangGraph · LangChain · RAG · PostgreSQL · Docker

Featured Projects

A selection of things I've built — from ML models to full-stack apps.

AI Finance Tracker

AI Finance Tracker

HuggingFace smolLM2 integrated Finance Tracker to track finances by just typing a message to bot.

View on GitHub
Dog Breed Detector

Dog Breed Detector

A simple web app that uses a pre-trained model to detect dog breeds from images. The model is trained on the Stanford Dogs Dataset, which contains over 20,000 images of 120 breeds of dogs.

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 Cyberinfrastructure Competition

Cyberinfrastructure Competition

GIS-integrated AI dashboard predicting high-demand Citibike stations across NYC using LSTM model, optimizing bike placement with spatial analytics; awarded First Prize in NSF competition. Led an interdisciplinary team of 5 members from statistics and geography domains.

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NFL Outcome Prediction

NFL Outcome Prediction

ML model for predicting NFL game outcomes using datasets spanning the last 20 years. Boosted model accuracy by 40% by integrating curated datasets, with a specific focus on player injury information.

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Refugee & Immigrant Transitions Surveyor Form

Refugee & Immigrant Transitions Surveyor Form

Attended AI for Good Hacakthon at San Francisco, We have developed a Full-stack application to detect data from Handwritten survey Form using Gemini Flash 2.0 and keep them in structured data xlsx format

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LFT Lens

LFT Lens

Developed a Native Mobile Application to detect Test and control lines from LFT strips and generate Garphs based on pixel intensity

View on GitHub

Get in Touch

Have a question or want to work together? I'd love to hear from you.

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