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Lunch and Learn - November 2016 - Download Presentation! - Deep Learning Platform for Seismic Data Analytics

11 Nov 2016 4:06 PM | SHPCP (Administrator)

The Geophysical Society of Houston and 
The Society of HPC Professionals

A Lunch & Learn Round Table Discussion Meeting

Deep Learning Platform for Seismic Data Analytics

Abstract: The Cloud Computing Research Lab at Prairie View A&M University has been working on developing a scalable cloud platform for seismic data analytics to facilitate a variety of interpretation scenarios. The recognition of 3D complex geological features in noisy seismic datasets is a daunting challenge in pattern recognition. Early experience shows that traditional machine learning techniques such as Support Vector Machines (SVMs) and Logistic Regression may be insufficient for this task. We will present our experience of building a deep learning based seismic data analytics platform on top of Apache Spark and Google TensorFlow, and demonstrate the early results of applying Convolutional Neural Networks (CNN) on a geological fault detection case study. Moreover, we will also present the collaborative work with FEI on applying remote visualization technology to large seismic datasets that are distributed in the Spark environment. The work is sponsored by National Science Foundation. 

Presenter’s Bio: Dr. Lei Huang is an Assistant Professor at Prairie View A&M University (PVAMU), where he is leading research at the Cloud Computing Research Lab. He also serves as Associate Director of Research in the Center of Excellence in Research and Education for Big Military Data Intelligence at PVAMU. He currently has several active research projects sponsored by NSF and DOD in Big Data Analytics, Cloud Computing and High Performance Computing areas. He joined the university in 2011 having previous experience in HPC research at the University of Houston. Huang has a Ph.D. from the Computer Science department at University of Houston in 2006.