Cornelia Caragea | Adjunct Associate Professor
Michelle Munson-Serban Simu Keystone Research Scholar
Ph.D. - 2009, Iowa State University
B.S. - University of Bucharest
Cornelia Caragea is an Associate Professor of Computer Science and the Lloyd T. Smith Creativity in Engineering Chair at Kansas State University, where she directs the Machine Learning group. Previously, she was an Assistant Professor of Computer Science and Engineering at the University of North Texas. She received her Ph.D. in Computer Science from Iowa State University in 2009 and her B.S. in Computer Science from the University of Bucharest in 1997. At Iowa State University, she was honored with a Premium for Academic Excellence Award for her doctoral work.
She is a member of the Association for Computing Machinery and the Association for the Advancement of Artificial Intelligence.
Cornelia Caragea’s research interests include artificial intelligence, machine learning, information retrieval, and natural language processing. The overarching goal of her research is to improve people’s ability to effectively and efficiently mine and discover knowledge from large amounts of digital data.
Several projects that she currently works on include: the design of accurate approaches for information extraction and scientific data analysis, which can foster knowledge discovery and organization; the development of supervised and semi-supervised learning approaches to handle today’s very large collections of data from many data mining applications; the design of privacy analysis technologies that can help users to maintain control of their privacy in online environments, while allowing users to increase their online social capital without leading to overexposure; and the investigation of accurate approaches to establishing trustworthy-citizen-created data for disaster response and humanitarian action, which can potentially improve the speed, quality and efficiency of emergency response during critical times of disaster events.
Cornelia Caragea has received an NSF CAREER award for her work in machine learning, information retrieval, and natural language processing – the most prestigious recognition offered by NSF for young researchers. Caragea’s NSF CAREER project is aimed at designing solutions that will make information more accessible and comprehensible to scholarly web users, helping them discover knowledge more effectively and efficiently. She plans to develop an integrated framework that focuses on the extraction and utilization of scholarly knowledge graphs in online environments.
Caragea has received more than $2M in NSF funding for her research initiatives, including seven NSF grants as the PI. Her research resulted in 70+ peer-reviewed publications in highly competitive venues such as ACM Transactions on the Web; the American Association for Artificial Intelligence; International Joint Conference on Artificial Intelligence; International World Wide Web; and Empirical Methods in Natural Language Processing. One of the papers that she co-authored received the “Most Innovative Application of AI” award at the Conference on Innovative Applications of Artificial Intelligence in 2014. Caragea has served on many program committees and NSF review panels and organized several workshops on “AI perspectives on Scholarly Big Data.”