Research on human-AI interaction and AI interface design, with a focus on how information visualization choices shape people's cognition, perception, and trust when interacting with AI systems
Cross-domain data analysis (e.g., vehicle, customer, sales, production), metrics development, dashboard visualization
Optimization and automation of ML models and data pipelines for scalable deployment
Large-scale in-vehicle infotainment (IVI) data analysis for modeling user behavior and metrics development
Machine Learning model and Human-Machine Interface design for personalized IVI recommendation systems
Visual complexity of automotive head-up displays and attentional tunneling in driving
Exploration for reward information in modulating Value-Driven Attentional Capture (VDAC)
Computational simulation of associative learning models in VDAC
Behavioral experiments (keypress, mouse-tracking, neuroimaging), statistical analysis
Company-wide data analysis to support HR and operations decisions
