A paper by Associate Professor Halil Kilicoglu and Informatics PhD students Haoyang Liu and Janina Sarol received the Best System Paper Award at the 15th International Workshop on Semantic Evaluation (SemEval-2021). SemEval, which was held on August 5-6, is a series of natural language processing (NLP) research workshops whose mission is "to advance the current state of the art in semantic analysis and to help create high-quality annotated datasets in a range of increasingly challenging problems in natural language semantics."
"Participants were expected to develop NLP models to automatically extract and structure scholarly contributions of publications in the NLP field. The ultimate goal is automatic knowledge curation from the scientific literature to facilitate better information access," said Kilicoglu. "The system we developed combined well-established ideas from Information Extraction with a cascade of neural network models, achieving the top performance at SemEval."
The resulting paper, "UIUC-BioNLP at SemEval-2021 Task 11: A Cascade of Neural Models for Structuring Scholarly NLP Contributions," received the Best System Paper Award out of 175 papers.
Kilicoglu's research interests include biomedical informatics, natural language processing, computational semantics, literature-based knowledge discovery, scholarly communication, science of science, and scientific reproducibility. He holds a PhD in computer science from Concordia University.
Liu's research interests include representation learning in NLP, information retrieval, knowledge engineering, and their applications in the biomedical domain. He earned his bachelor's degree in telecommunications engineering from Beijing University of Posts and Telecommunications.
Sarol is interested in using text mining, natural language processing, and network analysis to develop tools that enhance the productivity of researchers. She holds an MS in information management from the University of Illinois and BS in computer science from the University of the Philippines.