Polly Fordyce — 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. ---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.Twitter: https://twitter.com/fordycelab​Website: http://www.fordycelab.com/​---Topics Discussed:0:00​ Sneak peek, intro2:11​ Background on protein sequencing7:38​ How changes to a protein's sequence alters its structure and function11:07​ Microfluidics and machine learning19:25​ Why protein folding is important25:17​ Collaborating with ML practitioners31:46​ Transfer learning and big data sets in biology38:42​ Where Polly hopes bioengineering research will go42:43​ Advice for studentsTranscript:http://wandb.me/gd-polly-fordyce​Links Discussed:"The Weather Makers": https://en.wikipedia.org/wiki/The_Wea...​---Get our podcast on these platforms:Apple Podcasts: http://wandb.me/apple-podcasts​​​Spotify: http://wandb.me/spotify​​Google Podcasts: http://wandb.me/google-podcasts​​​YouTube: http://wandb.me/youtube​​​Soundcloud: http://wandb.me/soundcloud​​Join our community of ML practitioners where we host AMAs, share interesting projects and meet other people working in Deep Learning:http://wandb.me/slack​​​Check out Fully Connected, which features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, industry leaders sharing best practices, and more:https://wandb.ai/fully-connected