Hi, I'm Fred Hohman

I’m a Ph.D. candidate in the College of Computing at Georgia Tech advised by Polo Chau and Alex Endert.

My research applies a human-centered approach to designing and developing interactive scalable interfaces that help people understand and explain machine learning models. I also write, design, and build explorable explanations and interactive data visualizations to simply communicate complex ideas.

I have worked at Apple, Microsoft Research, NASA Jet Propulsion Lab, and Pacific Northwest National Lab.

My research is supported by a NASA Space Technology Research Fellowship.

Here's my CV.
Featured Research Publications
Summit
Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations
TVCG 2020
Project Demo PDF Video Recording Code Slides
Gamut
A design probe to understand how data scientists understand machine learning models
CHI 2019
Project PDF Blog Video Preview Slides
Visual Analytics in Deep Learning
An interrogative survey for the next frontiers
TVCG 2018
Project PDF Blog Video Code Slides
Featured Interactive Articles
Parametric Press
A born-digital magazine showcasing the expository power of the web
Present —
Project Code
Dimensionality Reduction
Explore the methods data scientists use to visualize high-dimensional data
July 2018
Project Code Slides
The Math of Card Shuffling
Riffling from factory order to complete randomness
June 2018
Project Code
Featured Parametric Press Articles
The Myth of the Impartial Machine
Can we free machine learning models from bias and prejudice?
May 2019
Project Code
On Particle Physics
A CERN particle physicist walks us through the history and science of particle physics
May 2019
Project Code
Data Science for Fair Housing
In Atlanta, a nonprofit seeks to resist housing displacement—but how effective is the project?
May 2019
Project Code

Everything Else

Including a list of projects, the blog, monthly music playlists, stuff I use, and the archive.