Building better coronavirus databases with automatic quality checks
Amid a growing coronavirus crisis, experts in all fields have begun compiling massive datasets to track the impact of the contagion. To make constructing these datasets as accurate and timely as possible, Michael Cafarella, professor of computer science and engineering, is leading an NSF-funded project that will build high-quality auxiliary datasets to enable automatic quality checking and fraud… Read More »