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madhukar6143/README.md

Hi, I'm Madhukar 👋

Software engineer and M.Eng. Computer Science student at the University of Cincinnati (graduating Dec 2026), currently building AI-assisted engineering tooling as a Software Developer Intern at Analysis Express. I work across the full stack — Java/Spring Boot, React/Node.js, Python — with a growing focus on applied AI and computer vision.

🌐 Portfolio  ·  💼 LinkedIn  ·  📧 madhukar.eppalapelly@gmail.com


About Me

  • 📍 SanJose, california, USA
  • 🎓 M.Eng. Computer Science @ University of Cincinnati (Aug 2025 – Dec 2026)
  • 💼 Software Developer Intern @ Analysis Express, Inc.
  • 🎯 Open to New Grad / SWE / AI Engineer roles

🛠️ Skills

Languages: Python · Java · C++ · C# · JavaScript · TypeScript · SQL

Frameworks & Libraries: Spring Boot · React · Node.js · Angular · Flask · Redux Toolkit · Jest

AI / ML: PyTorch · TensorFlow · Keras · OpenAI API · Claude API · Computer Vision · YOLO · NLP

Databases: PostgreSQL · MongoDB · DynamoDB · Redis · Firebase · Kafka · Spark

Tools & Cloud: Docker · Kubernetes · GitHub Actions · ArgoCD · Jenkins · AWS · Azure · OCI


🎓 Education

M.Eng., Computer Science — University of Cincinnati  ·  Aug 2025 – Dec 2026


💼 Experience

Software Developer Intern — Analysis Express, Inc.  ·  May 2026 – Present

  • Developing AI-assisted engineering drawing analysis features on the IrisX platform, including a dynamic Excel export engine with template-driven generation for FAI/PDM reports.
  • Implemented GD&T validation against rule catalogs to automate compliance checks previously done manually.
  • Built a revision comparison pipeline using anchor-transform matching to detect geometric changes across drawing versions; investigated YOLO/OCR approaches for drawing extraction.
  • Contributed to UI redesign and ongoing model-training workflows for production deployment.

Associate Software Engineer — Jaguar Software India  ·  Feb 2024 – Jul 2025

  • Developed and maintained Java microservices with Spring Boot — modular service layers and RESTful APIs for account services, fund transfers, and transaction history across banking modules.
  • Built responsive front-ends with AngularJS, JavaScript, and modern CSS, improving cross-browser consistency across the client-facing banking app.
  • Designed and optimized PostgreSQL schemas, queries, stored procedures, and indexing for high-availability transaction processing.
  • Deployed Spring Boot services on Azure via App Services and Azure DevOps CI/CD, with JUnit/Mockito testing in an Agile/Scrum workflow.

Technical Associate Software — Eron Infoways  ·  May 2020 – Feb 2024

  • Architected scalable microservices with Node.js, Express, and TypeScript on AWS (EC2, S3, Lambda), decomposing legacy monoliths into containerized Docker services.
  • Built and migrated responsive React interfaces using Hooks and Redux Toolkit, integrating REST APIs with Redis caching to cut latency for 1,000+ daily users.
  • Designed secure backend APIs connecting client portals to PostgreSQL and enterprise workflow systems (ServiceNow), using JWT/OAuth 2.0 and role-based access control.
  • Engineered CI/CD pipelines with GitHub Actions and automated testing via Jest and React Testing Library, integrating Stripe payment APIs.

🚀 Featured Projects

🤖 Gmail-to-Telegram Agentic Workflow

An agentic pipeline that ingests Gmail notifications via Google Pub/Sub webhooks, uses Claude AI to score emails 1–10 with smart filtering (penalizing no-reply senders, unsubscribe links, and promotional content), and autonomously forwards high-signal messages to Telegram via a Flask webhook server deployed on Render. Python Claude API Flask Google Pub/Sub

🏥 RE-MEDI — Cloud-Native Healthcare App

A React + Spring Boot + PostgreSQL application deployed on Oracle Cloud Infrastructure using Kubernetes, Docker, and Infrastructure-as-Code across on-prem and multi-cloud (AWS, Azure) environments, with CI/CD through GitHub Actions and ArgoCD. React Spring Boot Kubernetes ArgoCD PostgreSQL

🖼️ Old Photo Restoration — Dual Variational Autoencoders

A dual-VAE system in PyTorch that restores aged photographs by removing scratches and dust and reconstructing missing regions, using two separate encoder-decoder paths to handle distinct degradation types and improve reconstruction quality over a single-model baseline. PyTorch Computer Vision Deep Learning


📊 GitHub Stats

Madhukar's GitHub stats

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