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Ritter earns $500,000 NSF CAREER Award

Assistant Professor of Computer Science and Engineering Alan Ritter has received a five-year, $500,000 Faculty Early Career Development (CAREER) Award from the National Science Foundation (NSF) for his research in natural language processing.

Alan RitterRitterThe CAREER award is NSF’s most prestigious award in support of junior faculty who exemplify the role of teacher-scholars through outstanding research, excellent education and the integration of both.

Ritter’s research focuses on getting computers to better understand natural language. His project, “Large-Scale Learning for Information Extraction,” will substantially advance the capability of machines to read large document collections and reason about the knowledge contained within them using minimal human effort. Doing so will help people overcome information overload and make better decisions by analyzing vital information that is locked away in unstructured text.

According to Ritter, there has been tremendous progress recently in speech recognition and machine translation by applying deep learning methods on massive, high-quality datasets; however, most available datasets for information extraction are either small or noisy, meaning they contain large amounts of meaningless data. His project will address these challenges by developing new methods that can learn more effectively from big, but noisy datasets that are constructed using distant supervision from an existing knowledge base. To demonstrate the new methods' effectiveness, they will be used to support several new applications, including the detection of cyber-threats reported online and the analysis of experts' opinions about their severity. Recent studies have found that 75-percent of software vulnerabilities are first reported online, giving attackers time to exploit the vulnerability. Systems that can automatically read computer security blogs and analyze new threats could help security practitioners track and prioritize them more effectively.

The project also includes a plan for integrating research and education. Outreach efforts aim to help attract a more diverse group of students to study computer science. These include hands-on workshops to expose first-year students to exciting natural language processing and artificial intelligence applications. Additionally, the project will help engage advanced undergraduate students in research through new course materials on cutting-edge information extraction techniques.

Ritter joined The Ohio State University College of Engineering in 2014. Prior to Ohio State, he was a postdoctoral fellow in the Machine Learning Department at Carnegie Mellon University. He earned his PhD in Computer Science from the University of Washington.