I am a Master’s student in Computer Science at Stony Brook University, passionate about building intelligent, scalable, and user-centric software systems. My interests span AI, full-stack engineering, backend systems, and accessibility engineering, where I focus on creating technology that bridges the gap between humans and machines.

I have hands-on experience developing solutions across the stack - from cloud-native backend systems and REST APIs to AI-powered applications and mobile accessibility tools. Recently, I’ve been exploring AI infrastructure, distributed systems, and cloud architectures, working on projects that combine deep technical rigor with human-centered impact.

Some of my recent work includes a Braille-to-Speech using CNN that converts Braille images into text and audio, a Fetal Heart Rate Analysis LLM project leveraging LangChain, OpenAI API, Gemini API and UMLS for medical NLP, and a full-stack food ordering app that served over 500 users at my undergraduate university.

I enjoy collaborating on projects that push the boundaries of AI and software scalability. Feel free to reach out about Python, Java, REST APIs, full-stack development, mobile app development, cloud, or AI systems.

📫 Email: [email protected]
🌍 LinkedIn: adityaupadhye47

Languages:
Python · Java · C · JavaScript · SQL · Bash

Core CS:
Data Structures · Algorithms · System Design · Object-Oriented Design · Design Patterns

Web & App Development:
Next.js · React.js · Node.js · Flask · Django · REST APIs · TailwindCSS · React Native · Flutter · Kotlin · Android AccessibilityService API

Databases & Cloud:
PostgreSQL · MySQL · MongoDB · SQLite · AWS · GCP · Docker · Linux · Git · CI/CD · Kubernetes

🔹 Fetal Heart Rate Analysis - LLM – AI-assisted clinical NLP pipeline using LangChain and MediTron
🔹 Braille-to-Speech using CNN – Deep learning system converting Braille characters into English speech using TensorFlow & Flask
🔹 SIST Canteen App – Full-stack food ordering app (React Native + Node.js + MongoDB)