LEAP Lab

Our lab sits at the intersection of Education and Technology, and we recruit two types of students. Students on the Education Track come with a background in education or the learning sciences, and teaching experience (e.g., K-12) is a plus. Students on the ML/Tech Track come with a background in machine learning, NLP, or software engineering, and work on LLM research (fine-tuning, alignment, knowledge tracing) and VLA research (embodied AI, educational robotics).

Regardless of your initial track, all members are expected to develop competency in both perspectives before graduation. Learn more →

Our research is interdisciplinary, bringing together AI and education. Some of our current focus areas include:

1. Generative AI in Education - designing and developing generative AI systems for teaching and learning.
2. Pedagogical Alignment - aligning large language models with pedagogical principles and educational goals.
3. Large Language Models - developing and fine-tuning LLMs for educational applications.
4. Knowledge Tracing - modeling student knowledge states using deep learning approaches.
5. Robotics (VLA) - Vision-Language-Action models for educational robotics and embodied AI.

More detail on each area is available on the Research page.