Hello, I'm Rupam Sadhukhan

Final Year Undergraduate Student

About Me

      Hello everyone,

      I am Rupam Sadhukhan, a Computer Science and Engineering student at Jalpaiguri Government Engineering College (JGEC) with a strong academic record (CGPA: 9.14). I am passionate about building inclusive, intelligent, and impactful technologies that solve real-world problems.
    
      My journey spans across AI/ML, Data Science, and Full-Stack Development, enabling me to work at the intersection of research and practical application. I was selected among the top 3000 students (top 2.5%) out of 1 lakh+ participants in Amazon ML Summer School 2025 as an ML Trainee, which strengthened my foundation in applied machine learning. 
    
      Some highlights of my work include: 

      • Augmaze – A VR-powered educational platform (in progress) designed to empower specially-abled children through AI-driven personalized learning. 

      • Namma Food – A full-stack food and services platform built with Java, Spring Boot, React, MongoDB, and AWS, featuring both an admin panel and user-facing interface. This gave me strong exposure to the end-to-end software development lifecycle.
    
      I was a Finalist at Smart India Hackathon 2024 and Semi-finalist at BuildWithIndia Hackathon 2025. I have actively contributed to open-source programs like GSSOC and SWOC, and led teams in the Google AI Solutions Challenge and ISRO Hackathon 2025. Beyond tech, I also led my college’s Quiz Club during inter-college events, sharpening my analytical and leadership skills.
    
      With a strong foundation in software engineering principles, data-driven modeling, and scalable system design, I bring versatility across Software Development, Machine Learning, and Data Science roles. I am eager to contribute to innovation-driven teams and collaborate on impactful projects that push the boundaries of technology.

Technical Skills

Languages: C/C++, Java, Python, JavaScript, SQL
Web/Cloud: Spring Boot, React.js, Vue.js, Firebase, Vercel, AWS EC2
Data/AI: Pandas, NumPy, Scikit-learn, LangChain, LLaMA, RAG, Matplotlib
Tools: Git, Docker, Postman, VS Code, Android Studio, Jupyter
Database/Backend: PostgreSQL, MongoDB, MySQL, REST API, JWT

Projects

Kshitij

Finalist project at Smart India Hackathon 2024 (SIH1656), under the Ministry of Earth Sciences. Kshitij is an Android app designed to provide real-time data on the recreational suitability of Indian beaches.

🔹 Integrated real-time weather and oceanographic data to analyze beach conditions such as tides, UV index, wave height, and wind speed.
🔹 Implemented safety alerts for high tide, extreme weather, and dangerous currents using location-aware notifications.
🔹 Developed personalized leisure recommendations (e.g., swimming, sunbathing) based on weather and user preferences.
🔹 Built using Java and Kotlin in Android Studio, with Firebase for backend and Google Maps for geo-tagging.
🔹 Modular architecture allows for future expansion (e.g., pollution monitoring, crowd density).
🔹 Contributed to safer tourism, better disaster preparedness, and smart coastal resource management.
🔹 Contributed to GIS-based waste detection via satellite imagery and implemented real-time alert triggers using database events for environmental monitoring and public safety.

GitHub Repo
UI Prototype

Namma Food

Namma Food is a scalable food and service delivery platform built using a robust Spring Boot (Java) backend. The system features dual frontends—React.js for users and Vue.js for the admin dashboard—offering seamless interaction and management.

🔹 Developed a scalable backend using Spring Boot and implemented dual frontends: React.js for users and Vue.js for admin, improving system usability.
🔹 Integrated secure JWT authentication and role-based access control, enhancing overall data privacy and operational security.
🔹 Currently learning and integrating Docker to containerize other services for better scalability.
🔹 Deployed on AWS with Docker containerization and integrated CI/CD pipelines for streamlined deployments.

GitHub Repo

Sorting Visualizer

Developed an interactive web application that visually demonstrates classic sorting algorithms like Bubble Sort, Merge Sort, and Quick Sort, aimed at improving algorithmic understanding for students and enthusiasts.

🔹 Implemented real-time visual comparison of sorting methods using intuitive bar animations.
🔹 Showcased time and space complexity dynamically to enhance educational value.
🔹 Built with modern JavaScript, ensuring responsive design for smooth cross-device performance across all major browsers.

GitHub Repo

Resume

You can view or download my resume below:

Email: rsadhukhan859@gmail.com
Phone: +91 8335974336

Contact Me

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