[CCoE Notice] Dr. David Mayerich's talk on Monday, N355, Engineering Building I

[Grayson, Audrey A]

High Performance Imaging Systems for Full-Scale Brain and Cancer Phenotyping
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New imaging technologies make it possible to collect three-dimensional images of tissue samples at with extremely high data rate. Prototype Knife Edge Scanning Microscopes (KESMs) are capable of imaging a cubic centimeter at sub-micrometer resolution in less than two days, producing over 30 terabytes of data. This opens the door for new research into tissue structure and the mechanisms of disease. However, there are still significant computational challenges to overcome. Full-scale images of tissue phenotypes produce massive amounts of data that is difficult to interpret directly, requiring high-performance algorithms for analysis, modeling, and visualization.

In this talk, I will discuss recent developments in phenotype imaging for both brain and cancer tissues. This includes methods for structural and molecular imaging and computational techniques for analyzing these massive data sets. In particular, I will focus on brain and cancer imaging, which represent the current grand challenges for basic research and clinical applications.
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David Mayerich received his Ph.D. in Computer Science at Texas A&M University, where he was awarded the Graduate Assistance in Areas of National Need (GAANN) Fellowship. His work focused on developing prototype instrumentation and algorithms for full-scale brain imaging at subcellular resolution.

David is currently a Postdoctoral Fellow with the Beckman Institute for Advanced Science and Technology.  He is the recipient of both the Beckman Fellowship and an NIH K99/R00 award. His current research focuses on both mid-infrared imaging for cancer diagnosis and high-performance modeling of optical systems to improving image quality and develop new instrumentation.

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