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Human-AI Interaction — Doctoral Research

Research

My NSF-funded doctoral research on modeling dynamic cognitive state to make AI systems more context-aware and trustworthy — with two applied systems as evaluation environments.

Threads4
FocusHuman-AI Interaction
FellowshipNSF CSGrad4US
Featured — Doctoral Research

Modeling Dynamic Cognitive State Profiles for Trustworthy AI

Stephen Pettus

Doctoral research proposal — Stephen Pettus, NSF CSGrad4US Fellow (Information Science, Drexel University).

Problem Framing & Proposed Research Opportunity

Large language models are increasingly embedded in reflective tools, learning platforms, and decision-support systems. These systems demonstrate remarkable generative capabilities and provide assistance in education, ideation, problem-solving, and emotional reflection. As AI becomes integrated into everyday workflows, a large opportunity and need emerges: designing systems that respond not only to textual input, but to the evolving cognitive states of the individual interacting with them.

Current AI systems largely treat prompts as isolated events. Yet interaction patterns, engagement trajectories, and behavioral traces contain meaningful signals about user condition. Incorporating dynamic representations of user state into model conditioning offers a pathway to improving trust, alignment, sustained engagement, cognition, and digital-wellness outcomes.

FeaturedDoctoral Research
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Research Threads
2025
Doctoral Research

Modeling Dynamic Cognitive State Profiles for Trustworthy AI

Stephen Pettus

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2025
Research Thread

Explicit Indicators + Latent Embeddings: A Hybrid State Model

Stephen Pettus

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2025
Research Thread

Generative Conditioning for Cognitive Alignment

Stephen Pettus

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2025
Evaluation

Human-Centered Evaluation Across Reflective & Learning Systems

Stephen Pettus

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