The Human-centered Artificial Intelligence Laboratory (HAIL) focuses on real-time big data analytics and machine learning to improve human performance, decision-making, and training. HAIL’s research is supported by a team of data scientists, software engineers, and statisticians, whose work is dedicated to forging innovations in digital twin modeling, deep reinforcement learning, and simulations.

Data analytics, machine learning, and simulations are at the core of HAIL’s research endeavors. To facilitate its research, HAIL relies on its computing capabilities. First, HAIL has its own dedicated machine-learning cluster for data model development and rapid prototyping.  For more complex calculations, the lab uses UCF’s Advanced Research Computing Center (ARCC), which has two high-performance computing clusters: Stokes for general computing and Newton for GPU-based deep learning. Pooling these resources and other technologies, HAIL generates high-fidelity models, training platforms, and simulations.

Recent projects include digital twinning for semiconductor fabrication and planning, data mining for nuclear reactor operator training, predictive analytics for student performance and education, and developing automated attacking and defending agents for cybersecurity resiliency and training.