Research & Publications

Peer-reviewed work published at international conferences. Research focus: procedural terrain generation for games using GPU computing, neural style transfer, and evolutionary algorithms.

WiP 2025 · Salvador, Brazil Research Poster

Terrain Generation using Neural Style Transfer and Fractal Brownian Motion Noise with Constraints

Simpósio Brasileiro de Games — Work in Progress Track, 2025

Hybrid terrain generation method combining neural style transfer with fractal noise (Fractal Brownian Motion) and user-defined constraints to produce realistic, visually controllable terrains for games and simulations. The system integrates a multi-criteria fitness function including NavMesh connectivity as a playability metric, validated across four terrain archetypes.

Neural Style Transfer Fractal Brownian Motion Genetic Algorithms Unity NavMesh GPU PyTorch
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CSCI 2024 · Las Vegas, USA Conference Paper

Simplified 3D Terrain Meshes using Poisson Disk Sampling and Perlin Noise on GPU

International Conference on Computational Science & Computational Intelligence, 2024

GPU-accelerated terrain generation combining Poisson Disk Sampling for point distribution with Perlin Noise for height synthesis, producing simplified 3D terrain meshes with significantly reduced polygon complexity while maintaining visual quality. The approach leverages parallel GPU computation to achieve real-time generation speeds suitable for game engines.

Poisson Disk Sampling Perlin Noise GPU / CUDA C++ OpenGL Mesh Simplification Real-Time Rendering
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