Hi, I'm Fred Hohman

I'm a Research Scientist at Apple

I design and develop interactive interfaces to help people understand machine learning models and data-driven systems. Besides building tools, I also create data visualizations and write interactive articles to simply communicate complex ideas.

I received my PhD from Georgia Tech where I worked with Polo Chau and Alex Endert. My dissertation on interactive interfaces for interpretability won the ACM SIGCHI Outstanding Dissertation Award and was supported by a NASA Space Technology Research Fellowship.

I have collaborated with designers, developers, artists, and scientists while working at

Apple,

Microsoft Research,

NASA Jet Propulsion Lab, and

Pacific Northwest National Lab.

Featured Research Publications

Latest research for fans of human-computer interaction, data visualization, and machine learning.

Model Compression in Practice

Lessons learned from practitioners creating on-device machine learning experiences

CHI 2024

Talaria

Interactively optimizing machine learning models for efficient inference

CHI 2024

Neo

Generalizing confusion matrix visualization to hierarchical and multi-output labels

CHI 2022

Featured Dissertation Publications

My dissertation contributed interactive interfaces to enable machine learning interpretability at scale and for everyone.

Interactive Scalable Interfaces for Machine Learning Interpretability

Fred Hohman

Dissertation, Georgia Tech, 2020.

Summit

Scaling deep learning interpretability by visualizing activation and attribution summarizations

TVCG 2020

Gamut

A design probe to understand how data scientists understand machine learning models

CHI 2019

Visual Analytics in Deep Learning

An interrogative survey

TVCG 2018

Apple Chart Design Guidelines

Guidance and best practices to help designers and developers create the best charts for Apple platforms.

Charting Data Patterns

Presenting data in a chart can help you communicate information with clarity and appeal

Apple Human Interface Guidelines 2022

Chart Components

A chart helps you communicate data in a graphical, approachable way

Apple Human Interface Guidelines 2022

Featured Interactive Articles

Enhanced reading experiences that demonstrate what's possible when dynamic media are effectively combined.

Machine Learning Research Articles

Interactively explore advancements in machine learning research at Apple

May 2021 — Present

Menstrual Cycle Length and Variability: A Visual Explanation

Visualizing the Apple Women's Health Study

2023

Communicating with Interactive Articles

Examining interactive article design by synthesizing theory from education, journalism, and visualization

Distill 2020

Parametric Press

A born-digital, experimental magazine dedicated to showcasing the expository power of the web.

Parametric Press: Issue 02

Interactively analyze and learn about our climate’s past, present, and future

2020

Parametric Press: Issue 01

Examine scientific and technological phenomena that stand to shape society at large

2019