Research Areas

Exploring critical sub-sections of AI alignment and safety research.

Ensuring AI systems (individually and in groups) reliably understand and act on human intentions.

Understanding the biases language models absorb and the personas they adopt, and how both shape model behavior.

Studying the policy, legal, and institutional frameworks needed to govern AI safely and responsibly.

Reverse-engineering the internal mechanisms of neural networks to predict, verify, and steer their behavior.

Investigating whether models know what they know, and why they confidently state things that are false.

Probing and hardening AI systems against adversaries — from prompt injection and red-teaming to adversarial robustness.