Innovative Research in Morphogenesis

We specialize in computational models of biological morphogenesis, integrating advanced neural network frameworks with adaptive growth algorithms for dynamic structural adjustments during training, enhancing the capabilities of AI systems.

Intricate abstract structure composed of intertwined organic shapes with a smooth surface, resembling a network or mesh-like formation in varying shades of purple and blue.
Intricate abstract structure composed of intertwined organic shapes with a smooth surface, resembling a network or mesh-like formation in varying shades of purple and blue.
Our Research Approach
Transforming Neural Networks

Our work focuses on developing morphogenesis frameworks that simulate biological processes, enabling neural networks to evolve and adapt through innovative algorithms, enhancing their learning and performance in complex environments.

Morphogenesis Models

Developing computational models for biological morphogenesis and neural networks.

The image features a close-up view of a neuron cell with golden, branch-like extensions against a light background. The neuron is detailed, highlighting its intricate structure.
The image features a close-up view of a neuron cell with golden, branch-like extensions against a light background. The neuron is detailed, highlighting its intricate structure.
Adaptive Growth Algorithms

Integrating morphogenesis framework with GPT architecture for dynamic model adjustments.

A complex network of interconnected wires and nodes forms a geometric grid pattern against a bright background. The structure appears intricate and symmetrical, with intersecting lines creating diamond shapes.
A complex network of interconnected wires and nodes forms a geometric grid pattern against a bright background. The structure appears intricate and symmetrical, with intersecting lines creating diamond shapes.
Neural Network Triggers

Designing morphological triggers to initiate growth in neural networks.