Teaching

MIT Deep Learning

For the past five years, I have been a lead lecturer and organizer for MIT 6.S191: Introduction to Deep Learning, MIT’s official introductory course on deep learning foundations and applications.

5.3M+
lecture views
1200
MIT students
31K
global students
50+
countries


Together with Ava Soleimany, I organize the course from scratch; including developing the curriculum, teaching the lectures, designing software labs, publishing the content online, and handling sponsorship from industrial partners.

We cover a wide range of deep learning methods with applications to machine translation, image recognition, game playing, image generation and more. The course incorporates labs in TensorFlow and peer brainstorming along with lectures. We conclude with project proposals and feedback from the staff and a panel of our industry sponsors.

2021 MIT enrollment of 650 students; enrollment of 300+ students per year in each of 2018, 2019, 2020. Over 30,000 registered students globally and over 5 million lecture views.

The entire course is open-sourced and available on http://introtodeeplearning.com.



Research Advising and Mentorship

I am fortunate to advise many amazing undergraduate and masters research students. I was awarded the 2020 MIT Outstanding Mentor Award for Undergraduate Researchers to recognize an individual research mentor for exceptional guidance and teaching in a research setting.

Masters (M.Eng.):

Undergraduate (B.Sci. - UROP or SuperUROP):