Rui Xie

A data-driven statistical learning framework on streaming data

My research lies at the intersection of statistics, biostatistics, machine learning, and public health. My main field of interest is the development of statistical sketching and sampling methods for large-scale streaming dependent data. The methods I have developed have been applied to various fields, ranging from streaming online learning and sampling to spatial pattern reconstruction with sketching and decentralized computing. I collaborate with researchers from several disciplines outside of statistics, including nursing science, psychology, computer science, geophysics, electrical and computer engineering, and mechanical engineering, to tackle data science problems

• Randomized sketching and sampling
• Large-scale data normalization
• Statistical learning algorithms for Internet of Things (IoT)
• Transfer learning in Smart Manufacturing
• Data fusion, sample selection and streaming sensor data modeling
• Technology-based adaptive interventions in Mobile Health
• Simultaneously features selection and sample size reduction