An in silico framework for multi-scale modeling and analysis of in vivo neuron-network mechanisms

Multi-scale bioinformatics pipeline for patient-specific drug screening via computational simulation of patient-derived organoids. Integrates U-Net segmentation, agent-based cell simulation, QSAR drug modelling and PDE diffusion.

Open research-code package for exploring CNRS: complex-base representation, CNRS-float, branch-aware complex-state workflows, and CNRS-H scale-law calculus. Part of a broader research programme on scale, representation, and complex-state preservation.

Emergentia is a neural-symbolic discovery engine that extracts parsimonious physical laws from noisy particle trajectory data. It combines deep learning to model complex forces with symbolic regression to rediscover human-readable, mathematically interpretable equations of motion.

LAMMPS-based framework for large-scale Parallel Replica Dynamics simulations of ablative thermal protection materials.

🧬 Explore biological AI systems designed for reasoning through DNA-encoded logic, advancing insights from quantum scales to ecosystems.