# Projects

Things I do, including research, academic course projects, and miscellaneous interests.

## PhD Dissertation

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

Scaling deep learning interpretability by visualizing activation and attribution summarizations

TVCG
2020

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

CHI
2019

An interrogative survey

TVCG
2018

## Research

Research publications for fans of human-computer interaction, data visualization, and machine learning.

Interactively evaluating efficiency and behavior across ML model compression experiments

TVCG, 2025

Apple Intelligence Foundation Language Models

arXiv, 2024

Scaffolding LLM-Generated Code with Ephemeral UIs in Computational Notebooks

VL/HCC, 2024

Lessons learned from practitioners creating on-device machine learning experiences

CHI, 2024

Interactively optimizing machine learning models for efficient inference

CHI, 2024

Scalable interactive visualization for exploring large machine

ACL, 2023

Collaborative machine learning model building with families

IDC, 2023

Helping machine translation practitioners prioritize model improvements

CHI, 2023

Proactive data collection and iteration for machine learning using reflexive planning, monitoring, and density estimation

AI&HCI, 2023

Composing interactive interfaces for machine learning

CHI, 2022

Generalizing confusion matrix visualization to hierarchical and multi-output labels

CHI, 2022

Scalable automatic visual summarization of concepts in deep neural networks

TVCG, 2022

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

Distill, 2020

Learning convolutional neural networks with interactive visualization

TVCG, 2021

Interactively deciphering adversarial attacks on deep neural networks

VIS, 2020

Fluid moves between code and graphical work in computational notebooks

UIST, 2020

Understanding and visualizing data iteration in machine learning

CHI, 2020

The future of notebook programming is fluid

CHI, 2020

Interactive visual learning for convolutional neural networks

CHI, 2020

Interactive interpretation of adversarial attacks on deep learning

CHI, 2020

Scaling deep learning interpretability by visualizing activation and attribution summarizations

TVCG, 2020

Visual analytics for discovering intersectional bias in machine learning

VAST, 2019

Combining visualization and verbalization for interpretable machine learning

VIS, 2019

Scaling deep learning interpretability by visualizing activation and attribution summarizations

VIS, 2019

Launching an interactive digital magazine

VisComm, 2019

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

CHI, 2019

Managing messes in computational notebooks

CHI, 2019

Discovery of intersectional bias in machine learning using automatic subgroup generation

Debug ML, 2019

Exploring and understanding neural networks by comparing activation distributions

PacificVis, 2019

Local graph exploration in a global context

IUI, 2019

Scalable k-core decomposition for static graphs using a dynamic graph data structure

Big Data, 2018

An interrogative survey

TVCG, 2018

The beginner's guide to dimensionality reduction

VISxAI, 2018

Fast, practical defense and vaccination for deep learning using JPEG compression

KDD, 2018

Compression to the rescue: defending from adversarial attacks across modalities

KDD, 2018

Interactive classification for deep learning interpretation

CVPR, 2018

Interactive visual exploration of graph query results

TVCG, 2018

3D exploration of graph layers via vertex cloning

VAST, 2017

Exploring entertainment video using color and dialogue

VIS4DH, 2017

A deep learning approach for population estimation from satellite imagery

GeoHum, 2017

mHealth visual discovery dashboard

Ubicomp, 2017

Visual graph query construction and refinement

SIGMOD/PODS, 2017

Towards understanding deep learning representations via interactive experimentation

CHI, 2017

Protecting and vaccinating deep learning with JPEG compression

arXiv, 2017

The effect of numerical parameters on eddies in oceanic overflows: a laboratory and numerical study

CMEM, 2019

Experimental and numerical comparison of oceanic overflow

APS DFD, 2014

## Interactive Articles

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

Visualizing the Apple Women's Health Study

2023

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

Distill
2020

## Apple Chart Design Guidelines

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

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

Apple Human Interface Guidelines
2022

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

Apple Human Interface Guidelines
2022

## Parametric Press Articles

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

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

2020

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

2019

## Undergraduate Thesis

3D Printing the Trefoil Knot and its Pages 2015

## REU

Math & Computational Science REU 2014

## Course Projects

## Other