David I. Inouye
Assistant Professor
School of Electrical and Computer Engineering (ECE)
Purdue University
EE 332
Biography
I am an assistant professor in the School of Electrical and Computer Engineering at Purdue University. I lead the Probabilistic and Understandable Machine Learning Lab. 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 was awarded the NSF Graduate Research Fellowship (NSF GRFP). My research interests are in machine learning focused on the fundamentals of generative probabilistic models and explainable AI. More recently, I have focused on explaining and mitigating dataset shift and incorporating explanation mechanisms directly into the model itself rather than relying on post-hoc techniques.
Interests
- Generative probabilistic models
- Invertible deep learning
- Explainable AI
- Dataset shift
Education
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PostDoc in Machine Learning, 2019
Carnegie Mellon University
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PhD in Computer Science, 2017
The University of Texas at Austin
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MS in Computer Science, 2015
The University of Texas at Austin
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BS in Electrical Engineering, 2012
Georgia Institute of Technology
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BA in Natural Sciences, 2011
Covenant College
