Complexity Labs runs a working research arm on fundamental questions in computer science: learning theory, complexity, cryptography, boolean function analysis. We pick the questions whose answers change what we can ship.
Machine Learning
From learning theory to deployed models: what can be learned, what can be verified, what can be trusted, and at what cost.
Cryptography
Getting ahead of the quantum deadline: exposure audits, migrations to ML-KEM and ML-DSA, and crypto-agility so the next migration is cheap.
Sublinear Algorithms
Streaming and sketching: rigorous answers from data too large to read end-to-end.