Expertise and Research Interests:

Daniel X. Le received the BS degree summa cum laude in Electrical and Computer Engineering from California State Polytechnic University, Pomona, in June 1986 and the MS and PhD degrees in Computer Science from George Mason University, Fairfax, Virginia, in January 1993 and February 1997, respectively.

From June 1986 to April 1989, he was a software engineer at the Jet Propulsion Laboratory, Pasadena, California. From April 1989 to September 1990, he was a system engineer at Science Applications International Corporation, McLean, Virginia. Since September 1990, he has been an electronics engineer here at the Lister Hill National Center for Biomedical Communications, the research and development arm of the National Library of Medicine.

Dr. Le's research interests are in document analysis and understanding, neural networks, optical character recognition, image quality and image processing. Dr. Le holds one US patent on automated portrait/landscape orientation detection in binary document images.

Publications:

Le DX, Mork JG, Antani S. Hybrid Ensemble-Rule Algorithm for Improved MEDLINE® Sentence Boundary Detection. AMIA Annual Symposium Proceeding 2021;2021:677-686.

Rae A, Kim J, Le DX, Thoma GR. Main Content Detection in HTML Journal Articles. DocEng ’18: ACM Symposium on Document Engineering 2018, August 28–31, 2018, Halifax, NS, Canada. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3209280.3229115

Kim I, Le DX, Thoma GR. Automated method for extracting "citation sentences" from online biomedical articles using SVM-based text summarization technique. Proc. the 2014 IEEE Int'l Conf. on Systems, Man, and Cybernetics (SMC 2014), pp. 2006-2011, San Diego, October, 2014

Kim J, Le DX, Thoma GR. Identification of Investigator Name Zones Using SVM Classifiers and Heuristic Rules. 12th international Conference on Document Analysis and Recognition (ICDAR). Washington D.C., August 2013.

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