Curtis G. Northcutt

cgn |AT| mit |DOT| edu

Resume | Google Scholar | GitHub

Photo of Curtis G. Northcutt, Ph.D. Candidate at MIT.

I am a sixth-year Ph.D. Candidate in Computer Science at MIT specializing in algorithms for robust learning with noisy labels and broad applications, especially in online education.


Theme adapted from orderedlist

Research – under construction (will update in 2020).

I am uniquely positioned between the MIT Office of Digital Learning and MIT EECS to solve problems using Artificial Intelligence in Online Education. For a tutorial-style framing of the field, including state-of-the-art AI solutions to important online education problems, as well as bits of my unpublished research, see these slides.

Rank Pruning is a state-of-the-art, robust, time-efficient, general algorithm for classification with noisy labels published at UAI ‘17.

Forum Ranking Diversification published at L@S ‘17.

CAMEO Cheating Detection in MOOCs and online courses published in Computers & Education ‘16.