Left to right: Department of Mathematics Professor Alan Edelman,

his co-instructor and family Corgi Philip, and visiting professor

and longtime Julia lab collaborator David Sanders have altered

their computational thinking course to encourage input on COVID-19

responses.

Nearly 300 students join an open course that applies data

science, artificial intelligence, and mathematical modeling using

the Julia language to study Covid-19.

When an introductory computational science class, which is open

to the general public, was repurposed to study the Covid-19

pandemic this spring, the instructors saw student registration rise

from 20 students to nearly 300.

Introduction to

Computational Thinking (6.S083/18.S190), which applies data

science, artificial intelligence, and mathematical models using the

Julia programming language developed at MIT, was introduced in the

fall as a pilot half-semester class. It was launched as part of the

MIT Stephen A. Schwarzman College of Computing’s computational

thinking program and spearheaded by Department of Mathematics

Professor Alan

Edelman and Visiting Professor David

P. Sanders. They very quickly were able to fast-track the

curriculum to focus on applications to Covid-19 responses; students

were equally fast in jumping on board.

“Everyone at MIT wants to contribute,” says Edelman.

“While we at the Julia

Lab are doing research in building tools for scientists, Dave

and I thought it would be valuable to teach the students about some

of the fundamentals related to computation for drug development,

disease models, and such.”

Sandi Miller | Department of Mathematics

April 7, 2020

MIT News