John Cunningham

machine learning, artificial intelligence, and computational neuroscience

My research group studies machine learning and its application to science and industry, including in particular using the tools of artificial intelligence to understand biological intelligence and other complex processes. I am a Professor of Statistics at Columbia University and an investigator at the Zuckerman Mind Brain Behavior Institute and Center for Theoretical Neuroscience. Prior to Columbia I was a research fellow in the Machine Learning Group at Cambridge. I have a Ph.D. in electrical engineering from Stanford and an undergraduate degree in computer science from Dartmouth. I have also worked with and advised a number of companies.

Learn more about our research, Machine Learning at Columbia, the Data Science Institute, the Grossman Center for the Statistics of Mind, the Zuckerman Mind Brain Behavior Institute, and the Center for Theoretical Neuroscience.

2022 Fall Term; STAT GR5242: Advanced Machine Learning (Section 002); Columbia University.
20202 Fall Term; STAT GR5242: Advanced Machine Learning (Section 001); Columbia University.
2020 Fall Term; STAT GR5242: Advanced Machine Learning (Section 002); Columbia University.
2020 Fall Term; STAT GR5242: Advanced Machine Learning (Section 001); Columbia University.
2019 Fall Term; STAT GR5242: Advanced Machine Learning (Section 002); Columbia University.
2019 Fall Term; STAT GR5242: Advanced Machine Learning (Section 001); Columbia University.
2019 Spring Term; STAT GR8201: Deep Generative Models; Columbia University.
2018 Fall Term; STAT GR5242: Advanced Machine Learning (Section 002); Columbia University.
2018 Fall Term; STAT GR5242: Advanced Machine Learning (Section 001); Columbia University.
2017 Fall Term; STAT GR5242: Advanced Machine Learning (Section 002); Columbia University.
2017 Fall Term; STAT GR5242: Advanced Machine Learning (Section 001); Columbia University.
2016 Fall Term; STAT UN1201: Introduction to Probability and Statistics with Calculus (Section 003); Columbia University.
2016 Fall Term; STAT UN1201: Introduction to Probability and Statistics with Calculus (Section 001); Columbia University.
2016 Spring Term; STAT W4400: Statistical Machine Learning; Columbia University.
2015 Fall Term; STAT G8325: Gaussian Processes and Kernel Methods; Columbia University.
2015 Fall Term; STAT W4400: Statistical Machine Learning; Columbia University.
2015 Spring Term; STAT W4400: Statistical Machine Learning; Columbia University.
2014 Fall Term; STAT W4400: Statistical Machine Learning; Columbia University.
2014 Fall Term; STAT W4700: Probability and Statistics; Columbia University.
2014 Spring Term; STAT W4240: Data Mining; Columbia University.
2013 Fall Term; STAT W4700: Probability and Statistics; Columbia University.
2011 Easter Term; Engineering Maths IB: Probability; University of Cambridge.
2011 Lent Term; Engineering Maths IB: Linear Algebra; University of Cambridge.
2010 Michaelmas Term; Engineering Maths IB: Vector Calculus; University of Cambridge.

Teaching

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Teaching