Drew's current projects include AI Beatmap Generation for Rhythm Games. This project aims to develop an AI-driven system capable of generating beatmaps that are virtually indistinguishable from those created by humans. The current implementation leverages a Convolutional Neural Network (CNN), and achieved a nearly 50% pass rate in tests with human subjects. Moving forward, the primary objectives are to enhance the AI by transitioning to a modern Generative Adversarial Network (GAN). This update is expected to improve the quality and realism of the generated beatmaps. Additionally, expanding the model's compatibility to include other rhythm games is a key priority, broadening the application's utility and impact in the rhythm game community.
Interests: Artificial Neural Networks, Rhythm detection and beat placement, and Generative Adversarial Networks.