Stanford’s Polly Fordyce on microfluidic platforms and machine learning
Polly explains how microfluidics allow bioengineering researchers to create high throughput data, and shares her experiences with biology and machine learning.
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Polly Fordyce is an Assistant Professor of Genetics and Bioengineering and fellow of the ChEM-H Institute at Stanford. She is the Principal Investigator of The Fordyce Lab, which focuses on developing and applying new microfluidic platforms for quantitative, high-throughput biophysics and biochemistry.
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Topics Discussed:
0:00 Sneak peek, intro
2:11 Background on protein sequencing
7:38 How changes to a protein’s sequence alters its structure and function
11:07 Microfluidics and machine learning
19:25 Why protein folding is important
25:17 Collaborating with ML practitioners
31:46 Transfer learning and big data sets in biology
38:42 Where Polly hopes bioengineering research will go
42:43 Advice for students
Transcript:
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4 years ago 00:45:55 4
Stanford’s Polly Fordyce on microfluidic platforms and machine learning