Speaker: Ahmad Tafti, PhD
Event Date: 1/4/2017
Event Times: 12:05pm-1:00pm
Ahmad P. Tafti is a postdoctoral scholar in the Biomedical Informatics Research Center (BIRC) at Marshfield Clinic Research Foundation. He completed his Ph.D. in Computer Science Department at University of Wisconsin-Milwaukee, where he was extremely working on several computational methods including machine learning, computer vision, and optimization algorithms to tackle the problem of 3D microscopy vision in an accurate fashion. He was a visiting student in the Computational Visualization Center at the University of Texas at Austin during May 2016. In the third year of his graduate study (Summer 2015), he worked as a research intern in the Center for Human Genetics (CHG) at Marshfield Clinic Research Foundation. His scientific publications have been published in prestige journals (e.g., Micron, CMBBE, PLOS ONE), and he was recently awarded the best reviewer award by SDIWC for the year 2016.
Structural analysis of microscopic objects is a longstanding topic in many scientific disciplines, including biological, mechanical, and materials sciences. The scanning electron microscope (SEM), as a promising imaging equipment has been around for decades to determine the surface properties (e.g., compositions or geometries) of specimens by achieving increased magnification, contrast, and resolution greater than one nanometer. While SEM micrographs still remain two-dimensional (2D), many research and educational questions truly require knowledge and facts about their three-dimensional (3D) structures. 3D surface reconstruction from SEM images leads to remarkable understanding of microscopic surfaces, allowing informative and qualitative visualization of the samples being investigated. In this scientific talk, we integrate several advanced computational technologies, such as computer vision, machine learning, and projective geometry to design and develop a novel and efficient method namely 3DSEM++ for multi-view 3D SEM surface reconstruction in an intelligent, adaptive, and optimized fashion.
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