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In an ever-changing, connected, and globalized world, organizations increasingly rely on data to evaluate performance and identify opportunities for improvement. The Smart Immersive Modeling Lab develops predictive analytics using machine learning and deep learning, and prescriptive analytics using simulation (discrete-event, agent-based, physics-based, and immersive) and optimization modeling to create practical solutions for real-world challenges.
We also leverage VR/AR/MR to build controlled, measurable environments that support rich behavioral data collection and real-time performance feedback—enabling deeper study of perception, decision-making, and human-in-the-loop systems.
Data-driven modeling, immersive simulation, and digital-twin approaches to improve training, quality, productivity, and human–system performance in modern manufacturing environments.
Predictive and prescriptive analytics to support operational decisions, patient flow, resource allocation, and training—bridging real-world data with simulation and decision support.
Human-centered autonomy, simulation, and immersive evaluation tools to study behavior, safety, decision-making, and performance in complex transportation systems.
Digital twins, sensing, and analytics for controlled environment agriculture and smart farming—supporting resilient operations, learning, and data-informed decision-making.
We create models and tools that connect data to decisions—ranging from predictive models and performance analytics to simulation-based decision support and immersive (VR/AR/MR) environments for training and evaluation. Our goal is to deliver solutions that are both scientifically grounded and directly usable by stakeholders.