Siyuan Chen
Dr. Siyuan Chen joined the Communications Engineering Branch of U.S. National Library of Medicine as a postdoctoral fellow since December 2006. He works with Dr. Song Mao on the project of the System for Preservation of Electronic Resources (SPER) for metadata extraction from historical documents.

Dr. Chen earned his M.S. and Ph.D. degrees in Electrical Engineering from the State University of New York at Buffalo in 2003 and 2006, respectively. He earned his bachelor degree in Electrical Engineering from the Dalian University of Technology, China, in 2000. His research interests include handwriting recognition, document image analysis and various topics on pattern recognition and machine learning.

Haiying Guan
Haiying Guan joined the Communications Engineering Branch, the Lister Hill National Center for Biomedical Communications at the National Library of Medicine (NLM) as a postdoctoral fellow in April 2008. She works with Dr. Sameer Antani on multiple imaging projects. Her work mainly focuses on learning-based retrieval algorithms for Content-based Image Retrieval, and Image and Text Integration (ITI).

Dr. Guan earned her Ph.D. degrees in Computer Science from University of California, Santa Barbara, in 2007. She received the M.S.degree from Nanyang Technological University, Singapore, in 2000, and her bachelor's degree in Beijing Jiaotong University, Beijing, China, in 1994, respectively. Her research interests include computer vision and image understanding, medical image processing, machine learning, pattern recognition, intelligent user interface, and human computer interaction.

Szilard Vajda
Dr. Vajda, joined Lister Hill National Center for Biomedical Communications, an intramural R&D division of the National Library of Medicine (NLM), at the National Institutes of Health (NIH) in April 2012 as research fellow, and concentrates his research on pattern recognition, machine learning with special application to document analysis, handwriting recognition, face detection/recognition and related topics such as classification, supervised/unsupervised/semi-supervised learning, clustering methods, automatic feature learning strategies and human-computer interaction. Previously, he was affiliated with Robotics Research Institute, Technical University of Dortmund (Dortmund, Germany), Furukawa Electric Institute of Technology (Budapest, Hungary), and Loria Research Center (Nancy, France).

Dr. Vajda holds a B.S. in Computer Science from Babeș-Bolyai University, (Cluj-Napoca, Romania, 1999) and a Ph.D. in Computer Science (2008) from Henri Poincaré University, (Nancy, France, 2008).

He is currently working with Dr. George Thoma and Dr. Sameer Antani on multiple research aspects concerning face detection and face recognition using state-of-the-art technologies. Over the course of his doctoral and post-doctoral research, he published articles in several journals, such as International Journal of Document Analysis and Recognition, International Journal of Pattern Recognition and Artificial Intelligence, Journal of Universal Computer Science, and presented his works in numerous conferences and workshops, such as, ICDAR, ICPR, ICFHR, CBDAR, MOCR, DAS, ICAPR, etc.