Date Posted: 4/06/2020

CS Assistant Professor Immanuel Trummer's research has led to a new database—CoronaCheck—"an automated system that uses machine learning, data analysis, and human feedback to automatically verify statistical claims about the new coronavirus," as Melanie Lefkowitz reports in her profile in the Cornell Chronicle.

Trummer and his research team, which includes CS doctoral candidates Georgios Karagiannis and Saehan Jo, has been collaborating with a team led by Paolo Papotti at Eurecom, an engineering school in Biot, France.

The goal of the collaboration is to generate true and reliable information about the virus in the midst of a global onslaught of new data, including untested recommendations. “We’ve tried to automate the entire process, from the raw data to the text that we want to verify,” Trummer notes.

"CoronaCheck adapts “Scrutinizer,” a system Trummer developed with Eurecom for the International Energy Agency in Paris, a nongovernmental organization, to support human fact checkers in translating text summaries into equations the computer can understand and solve. To do this, Scrutinizer employs machine learning and natural language processing—a branch of artificial intelligence aimed at deciphering human language—as well as large datasets that help the system figure out how to approach each new claim, and feedback from human users."

"The database interface builds on Trummer’s related work, including AggChecker, the first tool to automatically verify text summaries of datasets by querying a relational database. AggChecker was presented at the Association for Computing Machinery’s Special Interest Group on Management of Data’s annual conference in 2019."

Trummer team has also "developed an “Anti-Knowledge Base” of common factual mistakes from Wikipedia in collaboration with Google NYC. The research behind CoronaCheck was partly funded by a Google Faculty Research Award."

Read more about the Cornell CS faculty members, including Trummer, who won Google Research Awards