Research

My research explores the evolving intersection of human behavior, technology, and decision-making. Across both academic and applied settings, I’ve worked to understand how emerging technologies like AI and machine learning can support meaningful human experiences, while also advancing psychological theory and practice.

What connects my work is a curiosity about how people think, choose, and grow — and how we can design tools, environments, and experiences that help them do so more effectively.

Current Focus Areas

AI in Higher Education

I’m leading qualitative and quantitative research on how AI tools can enhance student learning, faculty engagement, and institutional support structures. This includes exploring ethical integration, reducing barriers to adoption, and developing AI-powered learning supports alongside platforms like Canvas and Google LearnLM.

Human Decision-Making & Goal Setting

Through my research on personality predictors of self-selected goals, I explore how traits like conscientiousness and self-control shape the way people pursue their ambitions. I use advanced statistical modeling and machine learning techniques to map these behavioral patterns and improve predictive accuracy.

AI & Human Collaboration in Research Processes

I’ve been investigating how large language models can assist in research workflows, including evaluating AI tools as viable alternatives for coding qualitative data. This work bridges human expertise with computational power, asking: When can AI meaningfully reduce researcher burden, and where do humans remain indispensable?

Psychometrics & Measurement Innovation

I have developed new tools to better capture complex psychological constructs, including a facet-level analysis of conscientiousness and new self-report instruments for affective forecasting and self-control. I continue to refine these tools using both classical and modern psychometric methods.