Table of Contents
Blood Blade - GAM200/250
Blood Blade is an exciting, fast-paced, adrenaline-filled side-scroller where players slash and dash their way through challenging encounters to fight the boss. This project was developed as part of GAM200/250, a 6-month module spanning two trimesters that required building both a complete game engine from scratch and a fully functional 2D game using that engine.
The technical scope included creating all fundamental engine systems including rendering, physics, input handling, resource management, and audio processing. The custom engine needed to support complex 2D animations, particle effects, and responsive combat mechanics while maintaining stable performance throughout intense action sequences.
My role was as Engine Programmer specializing in scripting systems and audio integration. I designed and implemented the complete Lua scripting system, enabling rapid gameplay iteration and providing designers with powerful tools for content creation. I integrated ZeroBrane IDE support with custom intellisense and autocomplete functionality, significantly improving the development workflow and reducing scripting errors. I developed the comprehensive audio engine using FMOD, implementing dynamic audio mixing, spatial sound effects, and seamless music transitions. I worked closely with our game designer to ensure audio perfectly complemented gameplay moments, creating immersive soundscapes that enhanced the overall player experience.
Cards and Caverns - GAM300/350
Cards and Caverns is a strategic turn-based, deck management, dungeon-crawler where players navigate treacherous dungeons using cards as their abilities. As players progress through challenging environments, they discover treasure chests containing upgrades to enhance their deck’s power and versatility, building toward climactic boss encounters that test their strategic planning and deck optimization skills.
This project was developed for GAM300/350, the advanced 3D game development module that required creating both a sophisticated 3D game engine and a complete game experience. The technical challenge involved building advanced rendering systems, 3D physics simulation, and complex game logic while maintaining the performance standards necessary for smooth 3D gameplay.
My role was as Graphics Programmer and Rendering Specialist, a challenging position I deliberately chose to push my technical boundaries. I designed and implemented the complete graphics engine using OpenGL as the primary API, with experimental Vulkan integration for exploring industry-standard rendering techniques. I developed the skinned animation system supporting complex character rigs with smooth bone transformations and blend shapes. I created a comprehensive Physically Based Rendering pipeline with real-time material editing capabilities, allowing artists to modify surface properties and see changes instantly during development. I integrated MP4 video support for cutscenes and UI elements, handling video decoding, playback synchronization, and seamless integration with the rendering pipeline.
AR Android Camera Vision Game - Assignment
An innovative educational AR application developed using Kotlin and Android Studio that gamifies object recognition through an engaging alien visitor narrative. Players use their device’s camera to identify various household objects, helping an extraterrestrial explorer learn about Earth’s everyday items. This assignment specifically required demonstrating proficiency in Kotlin and SQLite database integration within the Android development environment.
The application required integrating multiple complex systems including real-time camera processing, machine learning inference, local database management, and intuitive user interface design. The primary technical challenge involved optimizing deep learning models for mobile hardware constraints while maintaining responsive user experience and accurate object detection across diverse household environments.
My role was as Computer Vision Developer focusing on the most technically complex aspect of the project. I implemented the complete computer vision pipeline using ResNet architecture for robust image classification, ensuring accurate recognition across diverse lighting conditions, object orientations, and camera angles. I integrated the machine learning model with the Android application, handling real-time inference while maintaining smooth UI responsiveness and providing immediate visual feedback during object scanning processes.