Understanding Semiconductors | Episode 6
Understanding Semiconductors
Modern metrology from Lab to Fab by Rigaku.
A podcast for engineering leaders in characterization, metrology, process, and analytics, looking for discussion around semiconductor metrology challenges.
In this episode, Dr. Diebold Returns! A Deep Dive INTO his thoughts on Near Fab, Lab to Fab, and Artificial Intelligence
Markus speaks with Dr. Alain Diebold. This time, he deep dives into Lab to Fab, Near Fab artificial intelligence.
They discuss:
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Examples of Lab to Fab Transitions
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Machine Learning – How to Deal with Big Data
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Key Takeaways from the 2022 Frontiers Conference: Machine Learning vs., Regular Algorithms.
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How to address the talent gap in the semiconductor industry
Reach out to Markus Kuhn on LinkedIn for any potential guest requests or episode ideas.
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Ph.D. in Chemistry, University of Western Ontario, Canada BS Honors, University of Western Ontario, Canada. Markus is a semiconductor technology expert with a proven track record in developing, managing, and implementing novel metrology strategies and programs in support of advanced semiconductor process and architectural technology development. During a 25-year career with Intel and Digital Equipment Corporation, Markus was responsible for the development and implementation of a broad range of analytical capabilities to help meet semiconductor technology goals and was a key technical contributor to Intel's breakthrough strain, high K/metal gate, FinFET, and advanced memory programs. Currently, he is a Senior Director for Semiconductor Technology and a Fellow for Rigaku Corporation. His interests include the advancement of analytical capabilities for nanoscale devices, and he has a broader interest in the synergies between analytical characterization methods, machine learning, and process metrology to help enable emerging nanoscale device technologies. He has published 100+ refereed papers and holds 30+ patents relating to semiconductor technology.