Our Vision

We believe AI should illuminate human thought—not replace it. By embedding cognitive scaffolds into algorithms, we keep users engaged, informed, and in control.

Rigorous user studies and prototypes guide our frameworks, ensuring technology enhances critical thinking in real-world applications.

Published Research

Cognitive-Aware Design (CAD) (April 2025)

A ten-principle framework we developed to prevent cognitive offloading and boost user critical thinking in AI-driven interfaces.

  1. Active Engagement
  2. Transparent Reasoning
  3. Deliberate Friction
  4. Agency Primacy
  5. Comparative Insight
  6. Uncertainty Visibility
  7. Preserve the Process
  8. Scaffolded Learning
  9. Collaborative Language
  10. Reflective Review
Explore CAD →

CATCH with LVC (June 2023)

“CATCH with LVC: Solution for Enhanced Contextual Association in Conversational AI Models”— introduces a vector-based method for preserving long-form context in dialogue systems.

  • Enhanced context retention across multi-turn conversations
  • Integrates Long-term Vector Cache (LVC) for memory persistence
  • Open-source implementation on GitHub
Read the CATCH Paper →

Human-Computer Interaction

AI Systems

Ongoing & Future Research