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Evan Ott

Data is my passion. Whether it's , , or , I love connecting data with people and real-world problems. To that end, I've created this website to bring the data to you.

How to use this site

The section is a catalog of larger-scale projects I've worked on. The section is a jumping-off point for shorter (readable in 5 to 10 minute) escapades into topics I find interesting. If you'd like to read about me, rather than my work, then read on below!

Research Interests

I'm a third-year statistics doctoral student at UT-Austin in Sinead Williamson's lab. My interests are primarily in Bayesian deep learning, applying approximate Bayesian inference methods to neural networks. Specifically, I'm working on extending Probabilistic Backpropagation and investigating a Bayesian interpretation of transfer learning.

From Fall 2016-Summer 2018, I have been very fortunate to be an NIH Biomedical Big Data Science Fellow through a T32 grant at UT as part of the BD2K (Big Data to Knowledge) initiative. I have participated in research rotations in Alex Huk's lab in neuroscience, analyzing electrophysiological data from a novel visual stimulus.

Education

UTStatistics PhD Student (Fall 2015 — Present)
The University of Texas at Austin

UTB.S. Computer Science, B.S. Physics (Fall 2011 — Spring 2015)
The University of Texas at Austin
Turing Scholars and Dean's Scholars Honors Programs

TAG LogoHigh School (Fall 2007 — Spring 2011)
School for the Talented and Gifted (TAG Magnet)
Co-Valedictorian, Senior Class President


Contact Information

Facebook:         GitHub: 
Twitter:         Email:  evan.ott@utexas.edu
Website: