Ping-Chang Lin
Ping-Chang Lin is a Computational Scientist at the Research Computing Center (RCC) at the University of Chicago with expertise in medical imaging and spectroscopy analysis, conventional machine learning implementation, and deep learning architecture implementation and development. Prior to joining the RCC team, Ping-Chang was a research track faculty scientist at Georgia Cancer Center, Augusta University in Georgia and a research track assistant professor at Department of Radiology, Howard University in Washington, DC. During his working in Georgia and DC, he focused on designing convolutional neural network models to improve the tumor image segmentation in MRI, developing recurrent neural network algorithms to predict the clinical efficacy of a protocol used to manage inpatient hyperglycemia of hospitalized patients, and constructing MRI sequences to shorten the diffusion tensor imaging acquisition in MRI, and participating in several NIH research projects. Ping-Chang received a Ph.D. in Biophysics at University of California, Davis.
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