Genesis Lab is a research and development laboratory dedicated to the advancement of Generative Systems Engineering and the emerging field of Generative Sciences. Its work develops physical, mathematical, and computational modules for reasoning about form, configuration, and system behaviour through the lens of computational geometry, computational topology, and Spectral Graph Theory. The lab’s mission is to build and share open-source methods and tools that enable systematic exploration, analysis, and synthesis of complex spatial and multi-agent systems.Genesis Lab investigates generative systems through three complementary modes of inquiry: 1) Scientifically deducing designs from given functional requirements, using principled modelling, geometric logic, and computational reasoning 2) Systematically exploring discrete and modular configuration spaces, through combinatorial representations, topological structures, and rule-based generative grammars 3) Devising generative design game sets, where designers, cyber-physical modules, and users co-create configurations through algorithmically structured multi-agent interactions.These three modes provide a unified framework for studying how designs and configurations emerge from constraints, rules, interactions, and mathematical structures. The lab develops open-source platforms for combinatorial design, topological modelling, generative form-finding, configuration logic, and multi-agent decision processes. Modular building systems and dry-assembly logics serve as testbeds for demonstrating and validating broader theoretical contributions, while the core research agenda remains focused on the mathematics and computation of generative systems rather than any specific application domain.Genesis Lab’s educational mission is to train students in computational geometry, computational topology, and algorithmic modelling for generative systems. Teaching emphasises geometric reasoning, discrete representations, graph- and mesh-based models, and Python-based computational toolmaking. Students learn to construct and analyse algorithmic models of spatial configurations, explore design spaces systematically, and build their own computational frameworks for understanding and structuring complex systems.Committed to the values of Open Science and Open Education, Genesis Lab welcomes interdisciplinary collaboration and provides academic and industrial consultancy on developing bespoke computational methods and generative workflows for analysing configurations, exploring multi-agent systems, or supporting computational decision-making.
C# (Mat.NET, Meta.Numerics, Accord.NET), Python (NumPy, SciPy, NetworkX, Scikit-Learn, TensorFlow, OR-Tools, PyTorch, topoGenesis, COMPAS), MATLAB
Linear Algebra, Spectral Graph Theory, Calculus, Statistics and Probability, Control Theory
Shape Recognition, Manifold Learning, Natural Language Processing
Computer Graphics, Computer Aided Design, Computational Topology, Computational Geometry
Simulation Modelling, Differential Equations, Data Management, Data Modelling, Data Visualization, System Dynamics, Control, Agent-based Modelling
Open-Source Development, Version Control, Source Code Management
