Genesis Lab is a research and development laboratory dedicated to advancing Generative Systems and the emerging field of Generative Sciences. The lab investigates how architectural and spatial configurations emerge from constraints, rules, and interactions across multiple scales. Its work integrates mathematical reasoning, discrete geometry, topology, and Spectral Graph Theory to study form, configuration, and system behaviour in both building and urban contexts. Genesis Lab approaches generative systems through three complementary modes of inquiry: 1) Deriving structured designs from functional requirements, using principled modelling, geometric reasoning, and formal logic. 2) Exploring discrete and modular configuration spaces, through combinatorial representations, topological structures, and rule-based generative grammars. 3) Developing generative design game sets, where designers, users, and cyber-physical components co-create spatial configurations within carefully structured multi-agent environments.Together, these modes form a unified framework for understanding how architectural and infrastructural systems can remain adaptable, legible, and rigorously structured over time. Modular building systems and dry-assembly logics serve as experimental testbeds, while the broader research agenda addresses the mathematics of generative spatial systems beyond any single application domain.Genesis Lab’s educational mission emphasizes geometric thinking, discrete representations, graphs, raster, and mesh-based reasoning, and algorithmic modelling as instruments of architectural inquiry. Students are trained to analyse configuration spaces, formalize design logics, and construct their own generative frameworks for reasoning about complex spatial systems. Committed to Open Science and Open Education, Genesis Lab fosters interdisciplinary collaboration and engages with academic and professional partners interested in advancing structured yet open approaches to spatial design.
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
