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