Haotian Ma PRO

My goal is to explain AI behavior from the bottom up, starting with learned features and building toward abstract concepts. To pursue this goal, I develop methods to understand how learned representations shape model behavior across interventions, combinations, and changing contexts. My research combines theory, method development, controlled interventions, and large-scale evaluation across mechanistic interpretability, LLM reasoning, AI safety, and AI for scientific discovery.