Grace Guo
Hello, I'm Grace. I am a Postdoctoral Fellow at the Visual Computing Group at Harvard, working with Professor Hanspeter Pfister. My research looks at building human-centered explainability tools for AI, particularly in the biomedical and healthcare domains.
I received my PhD in Human-centered Computing from Georgia Tech, where I was part of the Visual Analytics Lab, advised by Professor Alex Endert. I previously completed my bachelor's in Human-computer Interaction and Cognitive Science at Carnegie Mellon University, and interned at PNNL and IBM Research. I am honored to be a recipient of the 2023-2024 IBM PhD Fellowship.
Selected Publications
2025
Is What You Ask For What You Get? Investigating Concept Associations in Text-to-Image Models
Salma Abdelmagid, Weiwei Pan, Simon Warchol, Grace Guo, Junsik Kim, Mahia Rahman, Hanspeter Pfister
Transactions on Machine Learning Research (TMLR), 2025
SEAL: Spatially-resolved Embedding Analysis with Linked Imaging Data
Simon Warchol, Grace Guo, Johannes Knittel, Dan Freeman, Usha Bhalla, Jeremy L Muhlich, Peter K. Sorger, Hanspeter Pfister
IEEE VIS, 2025
Grace Guo, Subhajit Das, Jian Zhao, Alex Endert
To appear in IEEE Transactions of Visualizations and Computer Graphics (TVCG)
The State of Single-Cell Atlas Data Visualization in the Biological Literature
Mark S. Keller, Eric Mörth, Thomas C. Smits, Simon Warchol, Grace Guo, Qianwen Wang, Robert Krueger, Hanspeter Pfister, Nils Gehlenborg
To appear in IEEE Computer Graphics and Applications (CGA)
2024
Situating Datasets: Making Public Eviction Data Actionable for Housing Justice
Anh-Ton Tran, Grace Guo, Jordan Taylor, Katsuki Andrew Chan, Elora Lee Raymond, Carl DiSalvo
ACM CHI, 2024
2020-2023
Causalvis: Visualizations for Causal Inference
Grace Guo, Ehud Karavani, Alex Endert, Bum Chul Kwon
ACM CHI, 2023
video | paper | code
A Survey of Human-Centered Evaluations in Human-Centered Machine Learning
Fabian Sperrle, Mennatallah El-Assady, Grace Guo, Rita Borgo, Duen Horng Chau, Alex Endert, Daniel Keim
Computer Graphics Forum, 2021
video | paper | survey homepage | survey browser
VAINE: Visualization and AI for Natural Experiments
Grace Guo, Maria Glenski, ZhuanYi Shaw, Emily Saldanha, Alex Endert, Svitlana Volkova, Dustin Arendt
IEEE Information Visualization Short Papers, 2021
video | paper | demo
Florence: a Web-based Grammar of Graphics for Making Maps and Learning Cartography
Ate Poorthuis, Lucas van der Zee, Grace Guo, Jo Hsi Keong, Bianchi Dy
Cartographic Perspectives, Issue 96, 2020
Teaching
CS 1710: Visualization
Harvard SEAS
Fall 2025 | Teaching Fellow
EC 2135: Data Visualization for Analysis and Communication
Harvard Business School
Spring 2025 | Teaching Fellow
CS4460: Introduction to Information Visualization
Georgia Tech
Spring 2023 | TA
CS7450: Information Visualization
Georgia Tech
Fall 2020 | Head TA
15-112: Fundamentals of Programming and CS
Carnegie Mellon University
Fall 2015, Spring 2016 | TA
Open Source
A collection of my open source libraries and repos. I am always looking for contributors to document, maintain and implement new features for these libraries. Please reach out if you might be interested in doing so.
Auteur is a front-end JavaScript toolkit designed to help with adding augmentations to web-based D3 visualizations and visualization systems to convey statistical and custom data relationships. To get started using Auteur, check out our documentation and examples.
Causalvis is a python library of interactive visualizations for causal inference, designed to work with the JupyterLab computational environment. Read our paper here.