This research resulted in machine learning methods that leverage internet-based digital traces to anticipate sharp increases in COVID-19 activity in U.S. counties. “Whether using artificial intelligence to investigate and predict the spread of diseases or adapting advanced computational techniques to tackle relevant questions in biology, Dr. Stolerman’s research shows the wide applicability of mathematics and its deep connections with other sciences,” said Dr. Jay Schwieg, head of the Department of Mathematics. PONDERING THE PAST Dr. Howard Sanborn, professor and political science department head, received a grant through U.S. Department of State, U.S. Consulate General Hong Kong andMacau, Public collect legislative data and use machine learning models to assess government responses to crises in Hong Kong. While investigating legislative politics in Hong Kong, the 2019 Core Fulbright Scholar noticed a series of changes in how the city was managed based on the action and reaction to conflicts. China and most of the former and current British Commonwealth countries have comprehensive online databases in English, Chinese and Cantonese of their government documents, particularly legislative proceedings. This allows Sanborn and his team to study protests at discrete points in Hong Kong history, reaching as far back as the 1850s. The goal is to see what words and phrases appear in conversations frequently before, during and after these conflicts. However, combing through the database for government debates and deliberations could take years. “I applied for the grant to be able to deploy machine learning computing techniques to process a lot of documents all at once with the driving goal of trying to understand what the government responses are to crises,” Sanborn said. The initial grant assists with the hiring of students experienced in machine learning and political science. “Right now, we’re starting more with an unsupervised model where we’re picking out just a small period and looking at the government debates and essentially refining the modeling,” Sanborn said. Together, a statistics graduate student works on machine programming while a political science graduate student helps identify the context of the phrases for each date and session to see what generates from the unsupervised model. As the process continues the model refines. “Transdisciplinary research is a big deal. And I believe in it,” Sanborn said. “I think our math, computer science and statistics departments really have sciences, and so I’m hoping this is a step towards that.” STUDYING STRESS The U.S. has the world’s largest fedcattle industry and is the world’s largest consumer of beef. Dr. Lucas Stolerman Dr. Howard Sanborn Dr. Ashley Railey This figure from Dr. Ashley Railey’s research shows social media data of cattle producers (black squares) discussing information about feedlot management. The orange circles depict feedlots of varying size and the lines show the sharing of information. Producer A has more connections to other feedlots but Producer B receives more diverse information. OSU COLLEGE OF ARTS AND SC I ENCES 37
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