Binquan Wang
About Binquan Wang
Binquan Wang is an MRI Data Analyst at the National Institutes of Health, where he has worked since 2013. He holds a Ph.D. in Applied Physics and has extensive experience in medical imaging and image processing.
Work at National Institutes of Health
Binquan Wang has been employed at the National Institutes of Health (NIH) as an MRI Data Analyst since 2013. In this role, he focuses on the analysis of MRI data, contributing to various research projects within the institution. His tenure at NIH spans over 11 years, during which he has developed expertise in medical imaging and image processing techniques.
Education and Expertise
Binquan Wang holds a Doctor of Philosophy (Ph.D.) in Applied Physics from the Shanghai Institute of Optics and Fine Mechanics. He also earned both a Bachelor of Science (BS) and a Master of Science (MS) in Applied Physics from Huazhong University of Science and Technology. His educational background provides a strong foundation in physics, statistics, and medical imaging.
Previous Experience at Vanderbilt University
Prior to his current position at the NIH, Binquan Wang worked as an Image Analyst at Vanderbilt University for a period of 10 months from 2008 to 2009. In this role, he contributed to the analysis of imaging data, further enhancing his skills in image processing and analysis.
Technical Skills and Proficiencies
Binquan Wang is skilled in various operating systems, including Unix, Linux, Windows/NT, and Mac. He is proficient in neuroimage processing software such as FSL, SPM, Freesurfer, and AFNI. Additionally, he has programming experience in languages including C/C++, Matlab, Python, and SAS, which supports his work in developing image processing algorithms for MRI and PET studies.
Background in Medical Imaging and Image Processing
With over 10 years of experience in 2D/3D, optical, and medical image processing, Binquan Wang possesses a strong background in medical imaging and image processing. His expertise includes the development of image processing algorithms tailored for MRI and PET studies, making significant contributions to the field of neuroimaging.