Satyam Shivam

Satyam Shivam

MCA'26 at VIT Bhopal

Former Programmer Analyst Trainee at CED Patna. AWS Cloud Foundation & AWS Generative AI Certified

E-mail Resume

About Me

I am a dedicated software developer with a passion for creating efficient and innovative solutions. My expertise spans across various technologies and frameworks, enabling me to tackle diverse challenges in software development.

With a strong foundation in computer science and hands-on experience in real-world projects, I strive to deliver high-quality code and exceptional user experiences.

My Skills

Programming Languages

Java, Python, JavaScript

Frameworks

HTML, CSS, React, Next.js, Node.js, Express.js, Spring Boot, Hibernate

Database

MySQL, MongoDB

Developer Tools

AWS Cloud, Git, GitHub, VS Code, RESTful APIs, Selenium, Maven, Apache Tomcat

Core Knowledge

Data Structures and Algorithms (DSA), Object Oriented Programming (OOP), Cloud Computing, AI, ML, GenAI

Soft Skills

Leadership, Teamwork, Organisation, Communication, Problem Solving

My Projects

Newssy Project

Newssy – Real-Time News Aggregator

  • Technologies: Next.js, JavaScript, Tailwind CSS
  • Build with React and Next.js, fetching real-time articles from 8+ categories using public APIs and SSR.
  • Implemented scroll and search filters, improving user content discovery by 40%.
GitHub Demo
Newssy Project

Swapify – Secondhand Marketplace

  • Technologie: Next.js, React, Tailwind CSS, Node.js, Express.js, MongoDB, RESTful APIs, Google OAuth
  • Applied OOP principles, SDLC, and System Design to develop the full-stack application.
  • Responsive Marketplace with real-time chat and geolocation, boosting user engagement by 40% across devices.
  • Engineered secure authentication (JWT, OAuth, bcrypt, rate limiting), cutting unauthorized access risks by 70%.
GitHub Demo
MoodTunes Project

MoodTunes – AI-Powered Music Recommender

  • Technologies: React (Vite), Tailwind CSS, Framer Motion, face-api, Radix UI, ESLint
  • Created with React, with 95%+ mood detection accuracy via selfie or manual input boosting user engagement 2x.
  • Suggest music across 5 emotions using real-time analysis, achieved less than 1 sec mood detection using face API.
GitHub Demo