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_Weather_Makers --- 🎙 Get our podcasts on these platforms: Soundcloud: http://wandb.me/soundcloud Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/gd_google YouTube: http://wandb.me/youtube Join our community of ML practitioners where we host AMAs, share interesting projects and meet other people working in Deep Learning: http://wandb.me/fs 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