24: The Future of Machine Learning in Materials Science (ft. Chris Borg)

Machine Learning and Artificial Intelligence are buzzwords that have infiltrated the materials science space, as many believe these tools will change the field as we know it. We’ve seen previous guests strongly recommend learning about ML models in order to become more efficient materials scientists, but with that, we have to realize the limitations of ML and AI as well.

Before we introduce today’s guest, check out our free professional development guide for materials scientists and engineers!

Today’s guest is Chris Borg, Research Scientist at Citrine Informatics. In this episode, he explains materials informatics and applications of machine learning in MSE.

In this conversation, we discuss the following topics:

• What is materials informatics?
• The limitations of machine learning and artificial intelligence
• How ML can facilitate improved materials selection
• Will machine learning ever fully replace materials scientists?
• The challenge of differentiating “good” and “bad” data points
• The process of using AI in MSE-related applications
• Machine learning advice for future materials engineers

Reach out to Chris: 

• https://www.linkedin.com/in/ckborg/

Special thanks to Matmatch for sponsoring this episode! Visit their website at www.matmatch.com. 

 

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Disclaimer: Any opinions expressed by either guests or hosts in this show are their own, and do not represent the opinions of the companies or organizations for which they are affiliated.