Jonsson School Researchers Named Most Influential in Field
Multiple Computer Science Department faculty from The Erik Jonsson School of Engineering and Computer Science have been named to the AMiner Most Influential Scholar Annual List, which recognizes the world’s top-cited research scholars – from both industry and academia – in the fields of science and engineering.
In the field of Natural Language Processing (NLP), the Department of Computer Science had three faculty recognized for their productivity and publication citations: Dr. Vincent Ng; Dr. Sanda M. Harabagi; and Dr. Dan Moldovan.
UT Dallas was ranked fourth overall in the field of NLP behind Google, Johns Hopkins University, and IBM.
The Department of Computer Science has prioritized research in the area of intelligent systems (IS), a field which involves several aspects of artificial intelligence and focuses on natural language processing, and speech and machine learning.
“Our faculty have expertise in several areas of IS, allowing them and their students to generate original and valuable research with many applications,” said Dr. Gopal Gupta, department head of computer science and holder of the Erik Jonsson Chair. “This ranking is a good indicator of the productivity and impact our faculty are making in the advancement of their respective fields.”
Within the IS track of the Department, many faculty and students are involved in the Human Language Technology Research Institute (HLTRI), which involves research that requires a broad spectrum of disciplines such as natural language processing, machine learning, and speech recognition and synthesis. HLTRI is one of the very few Institutes in the world dedicated to the study and research of language and its automatic processing. With the Institute’s cross-disciplinary approach, researchers from several schools and departments at UT Dallas tackle real-life problems together.
Also recognized in the rankings within the field of software engineering was Andrian Marcus, professor of computer science.
Marcus’ research focuses on software evolution and program comprehension. He is best known for his work on using information retrieval and text mining techniques for software analysis to support comprehension during software evolution.