Missing data imputation is a critical process in data analysis, enabling researchers to infer plausible values for absent observations. Over recent decades, a variety of methods have emerged, ranging ...

Haewon Jeong, an assistant professor in UC Santa Barbara’s Electrical and Computer Engineering (ECE) Department, experienced a pivotal moment in her academic career when she was a postdoctoral fellow ...

A new review published in Artificial Intelligence and Autonomous Systems（AIAS） highlights how artificial intelligence can tackle the pervasive problem of missing traffic data in intelligent ...

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...