Research
Our work at the intersection of cognitive science, neuroscience, and machine learning
Our research program focuses on building the foundational models for AI-augmented learning. We are particularly interested in:
Pedagogical Orchestration
How do we decide what to present to a learner, when to present it, and in what sequence? We're developing computational models that optimize learning trajectories based on cognitive science principles.
Adaptive Assessment
Traditional testing measures what a learner knows at a single point in time. We're building systems that continuously model learner knowledge and predict future performance.
Socratic AI
The best teachers don't give answers—they ask questions. We're exploring how language models can engage in genuine Socratic dialogue that promotes deep understanding.
More details coming soon.