Data Science Fellow
Michigan Institute for Data Science
Intelligent systems behaviors, usually concealed, are almost everywhere nowadays: human-like virtual interactions, responsive financial systems, flexible traffic allocation, and more. Beneath the surface, intelligent systems encompass the developments of learning, abstraction and inference, of which large amounts of data are the core. My research focuses on developing online-data-driven approaches to support theoretical and algorithmic foundations of real-time intelligent behaviors of systems. Directions include safe planning, robust operation and as well as reliable anomaly detection.