Hey this is Simarjeet 👋

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WHO AM I

I'm a masters student looking for Full-Time Software Development opportunities.

MORE ABOUT ME

Hi 👋 I am currently a Masters student in Computer Science at Washington State University, prior to this I completed my bachelors in Computer Science as well.

Besides this, I am also passionate about music and enjoy playing various musical instruments. In my free time, I love creating Rap/Trap/RnB beats and producing music.

Technical Skills

Software Developer with primary skills in Backend Development Download Resume

  • Java
  • Spring Boot
  • Python
  • C#
  • .NET
  • REST APIs
  • Azure
  • GCP
  • Docker

Check out my recent projects

project
FlavorBlend - Fusion of Cuisines

Our app harnesses the power of Generative AI and multimodal large language models to create unique, fusion-style recipes tailored to your taste. Simply input two cuisines, dietary preferences, and the type of meal—whether it’s a main course, appetizer, or dessert—and our AI generates a completely new recipe with a detailed ingredient list and step-by-step cooking instructions. To bring your dish to life, the app also creates an AI-generated image of the final dish. If you love the creation, you can share it within the app, inspiring a global community of food lovers to explore new flavors and cultural connections.

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Personal Spotify Data Analysis

The Personal Spotify Data Analysis project involved analyzing 20,000+ JSON entries from Spotify's streaming history. Using R scripts, the project applied data cleaning techniques to structure the dataset and created artist transition networks to detect listening patterns. Key metrics like degree centrality, closeness, and betweenness were used for an in-depth exploration of user behavior. Additionally, Spotify Web API was integrated for large-scale data handling and analysis, while signed network analysis provided unique insights into music preferences and transitions.

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Bullet Hell Shooting Game and Level Interpreter

The Bullet Hell Shooting Game was developed in Java using the LibGDX framework, featuring dynamic enemy waves, mid-bosses, and multi-phase final bosses. Essential design patterns like Factory, Observer, and State were used to ensure a modular and extensible architecture. A JSON-based level interpreter was implemented to allow customization of enemy types, spawn patterns, and bullet behaviors. The game's user interface was designed using LibGDX's UI toolkit, enhancing the overall user experience and aesthetics.

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Media Sharing Service

The Media Sharing Service was built using C# and .NET Core, providing a platform for users to create accounts, upload, download, and share media files. The service used Azure Cloud Services, with App Service for hosting, CosmosDB for storing metadata, and Blob Storage for media file handling. A search feature was implemented, allowing users to quickly locate media files by filename, file type, or user tags. The project demonstrated proficiency in cloud-native development, microservice architecture, and full-stack implementation.

Face Recognition-Based Image Separator

The Face Recognition-Based Image Separator project utilized Python, OpenCV, and dlib to classify and segregate images based on facial recognition. It implemented one-shot learning for identifying individuals with minimal data samples and automatically sorted images into individual, group, and unknown categories. The system processed datasets ranging from 35 to 10,000 images, achieving a recognition rate of up to 96.5%. It also optimized encoding techniques for handling large-scale datasets and visualized recognition rates using Matplotlib to provide insights into performance trends and scalability.

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