David I. Inouye
Assistant Professor
School of Electrical and Computer Engineering (ECE)
Purdue University
WANG 3063
Biography
I have recently joined the School of Electrical and Computer Engineering at Purdue University.
Previously, I was a postdoc at Carnegie Mellon University working with Prof. Pradeep Ravikumar. I completed my Computer Science PhD at The University of Texas at Austin in 2017 advised by Prof. Inderjit Dhillon and Prof. Pradeep Ravikumar. I obtained my B.S. in Electrical Engineering from Georgia Institute of Technology with a minor in Computer Science. I was awarded the NSF Graduate Research Fellowship (NSF GRFP).
My research interests include machine learning, probabilistic models, and deep learning with an emphasis on unsupervised learning and density estimation. Currently, I am focused on creating the foundations for destructive deep learning, which is a general approach to deep learning similar in concept to reverse engineering. I am also working on model explanations via the notion of counterfactuals, i.e., what would the model predict if the input was changed in interesting ways?
Interests
- Deep density estimation / Deep generative models
- Explainabilty and interpretability of models
- Probabilistic graphical models
- Learning with label noise
- Visualization of models
Education
-
PostDoc in Machine Learning, 2019
Carnegie Mellon University
-
PhD in Computer Science, 2017
The University of Texas at Austin
-
MS in Computer Science, 2015
The University of Texas at Austin
-
BS in Electrical Engineering, 2012
Georgia Institute of Technology
-
BA in Natural Sciences, 2011
Covenant College
