I am a second year PhD student at Princeton advised by Ryan P. Adams. I am particularly interested in machine learning and its applications to problems in science and engineering.

Previously, I was a Google AI Resident, working in the intersection of applied information theory and machine learning.

I did my BS and MEng in Computer Science at MIT, where I worked with Carl Vondrick and Antonio Torralba.

Publications:

Randomized Automatic Differentiation
Deniz Oktay, Nick McGreivy, Joshua Aduol, Alex Beatson, Ryan P. Adams
Preprint [Link]

Scalable Model Compression by Entropy Penalized Reparameterization
Deniz Oktay, Johannes Ballé, Saurabh Singh, Abhinav Shrivastava
ICLR 2020 [Link]

On Predictive Information in RNNs
Zhe Dong, Deniz Oktay, Ben Poole, Alex Alemi
NeurIPS 2019 Workshop on Information Theory and Machine Learning [Link]

Predicting Motivations of Actions by Leveraging Text
Carl Vondrick, Deniz Oktay, Hamed Pirsiavash, Antonio Torralba
CVPR 2016 [Link]

Industry Experience:

I have also spent time at Hudson River Trading, Google X on Project Loon, and Yelp working on MOE. Check out my LinkedIn for my full industry experience.