77: Machine learning and the future of teaching with Siddharth Misra episode artwork

EPISODE · Apr 7, 2020 · 31 MIN

77: Machine learning and the future of teaching with Siddharth Misra

from Seismic Soundoff

In this episode, host Andrew Geary highlights Sid Misra's course on Machine Learning Techniques for Engineering and Characterization. Sid provides a great background on machine learning and the value it brings to geophysics, why the coding language Python is essential (and easy-to-learn), one action you can take today to succeed in the field, and the advantages of virtual courses over in-person events. If you want to understand machine learning better and its impact on geophysics - listen to this episode! Visit https://seg.org/podcast/Post/8995 for the complete show notes. Note: Sid's tour is currently canceled due to COVID-19 coronavirus concerns. Sid and SEG are actively working on a virtual course to take its place. Visit https://seg.org/Education and scroll to the bottom of the page where you can sign up for the latest SEG educational opportunities by email to know when the course is ready! BIOGRAPHY Professor Siddharth Misra is an Associate Professor in the Harold Vance Department of Petroleum Engineering at Texas A&M University. Misra holds a Ph.D. in Petroleum Engineering from The University of Texas at Austin. Prior to that, from 2007 to 2010, he worked as a Wireline Field Engineer in Saudi Arabia, Egypt, and the USA with Halliburton. He received his undergraduate degree in Electrical Engineering from the Indian Institute of Technology Bombay, India, in 2007. Recently, he was awarded the prestigious Department of Energy Early Career Award, American Chemical Society New Investigator Award, and SPE Mid-Continent Formation Evaluation Award. His research interest includes subsurface characterization, machine learning, sensing and sensors, and inverse problems. CREDITS Original music by Zach Bridges. This episode was hosted, edited, and produced by Andrew Geary. Thank you to the SEG podcast team: Jennifer Crockett, Ally McGinnis, and Mick Swiney.

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