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, 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: 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