Research Statement

Overview

My research and professional work reside at the intersection of Cognitive Science, Human-Computer Interaction (HCI), and Systems Architecture As a Senior Research Software Developer at the Institute for Intelligent Systems, I focus on translating complex interdisciplinary theories into scalable, AI-informed software that prioritizes transparency and user agency.

Cognitive Modeling & Multimodal Learning

My current academic research investigates the integration of multimodal data streams to enhance the predictive accuracy of Intelligent Tutoring Systems (ITS). By synthesizing high-fidelity behavioral metrics (such as mouse kinematics) with physiological signals (EEG), I aim to develop more nuanced models of learner cognitive states.

Key areas of focus include:

• Memory Modeling: Utilizing Half-Life Regression (HLR) and ACT-R frameworks to track declarative knowledge stability.
• Biometric Integration: Exploring how non-intrusive signals, like Total Normalized Jerk (TNJ) and Event-Related Potentials (ERPs), can index cognitive load and retrieval fluency.
• Adaptive Scaffolding: Moving beyond traditional accuracy metrics to create responsive instructional environments that adapt to the learner's near-instantaneous state.

Applied AI & Systems Design

Professionally, I serve as a technical architect for large-scale AI initiatives. My work involves the modernization of machine learning diagnostic platforms and the development of specialized tools for:

• Computational Linguistics: Building platforms for natural language processing and historical manuscript analysis.
• Decision Support: Designing assessment frameworks for high-stakes environments, including military mission readiness and recidivism reduction.
• Interactive Visualization: Creating spatial and temporal data analysis tools that support complex research workflows.

AI Ethics & "Candid AI"

Grounded in a background in interactive design and AI ethics, I advocate for Candid AI—an architectural philosophy that builds transparency directly into automated systems. My work examines how humanity offloads agency to algorithms, seeking to prevent "learned helplessness" by ensuring AI remains a supportive scaffold rather than a cognitive crutch.

By bridging the gap between aesthetic storytelling and rigorous systems engineering, I strive to create technology that supports cognitive autonomy and enhances the human experience.