Lectures

Three lecture series at graduate level, written as original Quarto textbooks. Each series is self-contained and targets a distinct set of ideas. The research notes library sits alongside these and covers adjacent topics in shorter, blog-style form.

Lectures on causal inference

Twelve chapters from Neyman-Rubin potential outcomes to Double Machine Learning, causal forests, and Bayesian causal inference. Built around three identifying strategies (randomization, unconfoundedness-via-observables, and instruments) and four estimation paradigms (regression, weighting, matching, and ML-augmented doubly-robust methods).

Lectures on quantum computing

Three chapters on quantum algorithms, optimization, and the limits of quantum advantage. From Shor and Grover to QAOA and variational quantum eigensolvers; from claimed supremacy experiments to classical dequantization. The emphasis is on what is provable vs. what is hoped.

Lectures on AGI foundations

Four chapters on the mathematical and computational foundations of general intelligence. Gödel-Löb theorems and their implications for self-referential AI; Hutter’s AIXI and universal intelligence; world-models and planning-by-imagination; computational irreducibility and why “smarter” does not imply “faster.”

Research notes covering adjacent shorter topics are at research-notes.