Principal Scientist
CurrentMy research is in the intersection of AI, game theory, and cognitive science. These days, I'm particularly interested in the following challenges:1. Hybrid AI design: Existing approaches are limited because they don't combine context and common sense with contemporary machine learning techniques. And in human cognition, emotions are a feature, not a bug - how do we integrate emotions into our cognitive designs?2. Design principles for human-machine teams: How can we conceptualize and instantiate "machine ethics"? Can machines have a theory of mind that allows them to reason about such concepts as trust and moral responsibility? What are the principles needed to design congruence between humans and machines when working in teams?3. Game Theory: How can techniques from epistemic game theory be applied to effectively reason about adversarial actions and intentions in cybersecurity scenarios, especially when deception is ubiquitous. 4. Judgment & Decision-making under Uncertainty: I'm researching techniques to apply Friston's "Free Energy Principle" (loosely speaking, "Brains as Prediction Machines) to the design of inference engines that demonstrate flexible and adaptive decision-making in situations of extreme uncertainty. In addition to Bayesian methods, I've been investigating alternative inference frameworks such as Dempster-Shafer theory.
