Mathematics
Mathematics as the language in which the universe is written. Linear algebra as the grammar of neural computation, algebraic theory as the architecture of thought, and higher-dimensional mathematics as the terrain yet to be mapped.
Mathematics is the language I use when reality becomes too complex for intuition alone. It turns invisible structure into something precise enough to reason about, simulate, and build from.
What structures stay the same when everything else changes?
How do high-dimensional systems become legible through projection, symmetry, and transformation?
Where do biological systems, computation, and physical theory share the same formal skeleton?
Studying linear algebra, algebraic theory, computation, quantum systems, and game theory.
Thinking about neural populations through vectors, manifolds, dynamics, and transformations.
Using mathematical structure as a bridge between biology, software, hardware, and intelligence.
Linear algebra is the hidden language of neural computation, from the dot products in artificial neurons to the eigenmodes of biological neural populations. Understanding computation means understanding linear transformations.
Algebraic theory and category theory provide the most general framework for understanding structure and transformation across mathematical domains. Functors between categories are the deepest form of analogy.
Biophysical mathematics demands bridging discrete molecular descriptions and continuous field descriptions, the same mathematical challenge as neural decoding. This is where differential equations meet stochastic processes.
Game theory reveals the formal structure of strategic interaction, from evolutionary biology to economic systems to multi-agent AI alignment. The Nash equilibrium is a fixed point of rational behavior.
Higher-dimensional geometry trains the same cognitive muscles needed to think about high-dimensional neural representations and state spaces.