At the University of Georgia, I lead and contribute to interdisciplinary research applying artificial intelligence, machine learning, and quantitative analysis to engineering education, technology adoption, and emerging engineering technologies. I use computational workflows to study empirical, survey, and scholarly datasets and evaluate predictive models.
My research has examined machine-learning-based sensitivity analysis for construction digitalisation, AI implementation in sustainable building projects, and barriers to robotics and automation. I translate complex research questions into analytical frameworks and peer-reviewed work; my publications have received approximately 2,500 citations.
I also supervise and mentor undergraduate and graduate researchers in research design, data analysis, model evaluation, and scholarly writing. I contribute to externally funded interdisciplinary research, including ongoing NSF-supported programs.
