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Elvio Santangelo

Projects

Professional Projects
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Arcas Champions
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Arcas Champions logo
Arcas Champions

A Multiplayer 3D platformer third-person shooter hybrid where you play as an ape jumping and bouncing across the jungle whilst blasting your enemies with fruit guns. I implemented player-like AI bots and enemy NPCs, leveraging advanced behavior trees, perception systems, and gameplay abilities in Unreal Engine 5. Developed core gameplay systems combining C++ logic and flexible, designer-friendly Blueprint scripting to foster prototyping and faster iteration.

I have also been responsible for the level design process, from initial grayboxing and iterative playtesting through to final visual polish and optimization.

I created and maintained custom build pipelines utilizing Unreal Build Tool (UBT) and Unreal Automation Tool (UAT), significantly streamlining project builds and the deployment processes on Steamworks.

Finally, I have acted as an internal project manager, aware of the project’s state at all times.

Community Projects
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Black Mesa - Italian Translation and Proofreading
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Volunteer Community Project, Crowbar Collective

  • Technologies used: CrowdIn, String Localization in .xml datasets
  • I was annointed by the Crowbar Collective as the official Italian Localization Proofreader
  • I was responsible for the translation of many in-game strings from English, ranging from dialogue to HUD and menus, and espedcially for the final proofreading process.

    • Personal Projects
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    Interloping Habitat
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    Black Mesa custom level

    I built a complete Source Engine level mod from grayboxing through final polish, crafting layouts and the overall experience, as well as the new features present in the Black Mesa engine branch (which, at the time, had little documentation).

    Technologies used: Source Engine, Hammer Map Editor, Miro

    Machine Learning project
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    GitHub Repository Thumbnail
    Darakuu/LIS-Project

    Machine Learning project, a CNN model capable of recognizing the LIS alphabet, made for UniCT’s LM-18 Machine Learning Course.

    Python
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    I implemented a CNN model to recognize the LIS sign‐language alphabet by designing custom and AlexNet‐based architectures, training them on MNIST and custom‐acquired datasets, and building a data‐acquisition and engineering pipeline.

    Technologies used: Python, PyTorch, OpenCV2, Torchvision, TensorBoard, NumPy.

    Multimedia project
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    GitHub Repository Thumbnail
    Darakuu/Multimedia-VectorView

    A simple python project that calculates and visualizes any kind of video’s motion vectors. Made for UniCT’s LM-18 Multimedia Course

    Python
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    I created a Python application that computes and overlays video motion fields using EBMA and Three‐Step Search (with MSE/MAD) and tracks user‐defined ROIs via Oriented FAST, Rotated BRIEF, and a Multiple‐Instance Learning tracker, all wrapped in a PyQt5 GUI

    Technologies used: Python, OpenCV, Pillow, NumPy, PyQt5