PCGEx is a free (libre) Unreal 5 plugin that expands PCG capabilities. It offers a variety of high-performance nodes; with an edge for building relational graphs (Freeform, Delaunay, Voronoi, MST etc), advanced pathfinding; graph theory and much more.

Develop an cheap Multimodal Cardiovascular Monitoring System for detecting PPG, PCG and ECG signal using MAX30102, INMP441 and AD8232 with STM32 ARM-Cortex MCU

Optimal circulant graphs generating results dataset

Minecraft mod that implements an HTTP interface for reading and writing blocks (and more) by an external program or script. Intended for use in the GDMC competition.

Procedural texture generation package.

SMB FinSight is a Python-based financial dashboard & analysis application designed for small and medium-sized businesses (SMEs).

MSc thesis Prototype: Quality Diversity (MAP‑Elites) for procedural racing tracks. Voronoi/Convex Hull generators → spline tracks → headless TORCS sims → UMAP‑guided behavior space → web visualizer.

Numpy-compatible bit generators and add some random variate distributions missing from NumPy.

🎲 Lightweight subset of pcg-cpp random number generators

💀 A high-performance, zero-dependency Go library for generating random data. Provides fast, ergonomic alternatives to `math/rand` and `crypto/rand`, featuring a powerful, configurable templating engine for complex data generation.

Unreal PCG ⇋ Houdini Engine: Seamless Integration

Publish some small parts in my personal daily-used Houdini accessories

Biosignal Processing in Python

Modifications to TypeChat to support iterative prompt-driven refinement with translate / modify / repair fns

A modern PCG64DXSM PRNG for JavaScript - reproducible, high-quality random numbers for Node.js and browsers.

A wrapper around C++ FastNoiseLite library for CUDA

A WebGL game with a custom procedural city generation algorithm, full Yandex.Games SDK integration (Cloud Saves, IAP), and Rigidbody-based tank physics.

Final year capstone project for heart disease detection using a multi-modal approach. We trained separate ML models on ECG, PCG, and PPG signals and fused their confidence scores using a mathematical method to provide a more accurate and holistic risk assessment. Project Members: Anandakrishnan A and Aryan Matte

HAMC (Hierarchical Adaptive Model Collapse) is an implementation of procedural content generation that combines different texture generations methods.