Areas of specialization: Human-computer interaction · Interactive programming tools · Reading tools · Applications of AI.

My research group studies how computers can help us comprehend complex texts—like science papers, source code, clinical notes, and mechanized proofs. We develop new interaction mechanisms by which people can inquire about the meanings of these texts.

For example, could reading interfaces help people understand equations in math texts? In one project, we explore just this question. We characterized how authors already augment formulas to explain them, developed tools to help them do it more easily, and integrated these explanations into an interactive reading application.

We have a heavy systems-building focus—we build our ideas into usable systems in order to refine those ideas, and test out their effect on users. Our systems often incorporate empowering techniques from text processing and program analysis. We ground our ideas in careful formative observations and interviews with prospective users.

Projects in our group are led by Ph.D. students Alyssa Hwang, Litao Yan, Hita Kambhamettu, Jeff Tao, Harry Goldstein, and Jessica Shi and master’s student Zed Wu.

Ph.D. student applicants: I will not be taking on new students in fall 2024. I encourage your application to Penn, though I myself will not be able to consider you as a prospective advisee.
Penn master's and bachelor's students: If you are interested in the work that our group does, I encourage you to take Penn's class in human-computer interaction—CIS 4120/5120—to learn the essential skills we bring to our research, and then to apply to do research with our group here.

Some recent news

September 2023: Our paper on Formula Formatting Language will be presented at UIST '23. Read it here. Also see Harry Goldstein's demo of an interactive property-based testing tool at the demo session.

July 2023: Alyssa Hwang presented a paper on designing audio instructions for tasks like following recipes at DIS '23. Read the paper here.

March 2023: I gave invited talks to MIT and Stanford' HCI groups on "Designing the Interactive Paper." Watch the Stanford talk here.

Selected recent publications

This list of publications represents some research directions I have been thinking about a lot lately. A full, up-to-date list of my publications and accompanying resources appears in the publications section of my CV.
Math Augmentation: How Authors Enhance the Readability of Formulas using Novel Visual Design Practices
Andrew Head, Amber Xie, and Marti A. Hearst
ACM Conference on Human Factors in Computing Systems, 2022

Describes how authors alter the presentation of math formulas to make them more approachable, from colorization to labels, layout, and beyond. Recommendations are provided for designing more expressive, efficient math presentation tools.

Best Paper Award

Augmenting Scientific Papers with Just-in-Time, Position-Sensitive Definitions of Terms and Symbols
Andrew Head, Kyle Lo, Dongyeop Kang, Raymond Fok, Sam Skjonsberg, Daniel S. Weld, and Marti A. Hearst
ACM Conference on Human Factors in Computing Systems, 2021

Presents ScholarPhi, a reading interface for scientific papers that reveals definitions of terms and symbols. The design is grounded in an observational study and 4 pilot studies. A controlled study with 27 researchers showed the tool is useful and desired.

Composing Flexibly-Organized Step-by-Step Tutorials from Linked Source Code, Snippets, and Outputs
Andrew Head, Jason Jiang, James Smith, Marti A. Hearst, and Björn Hartmann
ACM Conference on Human Factors in Computing Systems, 2020

Presents Torii, a new kind of computational notebook for authoring programming tutorials. The design is grounded in interviews with authors and a content analysis of 200 tutorials. In a lab study, 12 tutorial authors created flexibly-organized tutorials with the tool.

Nominated for Best Paper Award

Managing Messes in Computational Notebooks
Andrew Head, Fred Hohman, Titus Barik, Steven M. Drucker, and Robert DeLine
ACM Conference on Human Factors in Computing Systems, 2019

Presents code gathering tools, interactive extensions to computational notebooks that help analysts find, clean, recover, and compare versions of code. In a lab study, 12 data analysts quickly appropriated the tools to support exploratory data analysis.

Best Paper Award

Teaching

Spring 2023: CIS 3990: Introduction to Human-Computer Interaction (syllabus)

Fall 2022: CIS 7000-001: Designing Programming Environments: Live and Literate Programming (syllabus)

Spring 2022: CIS 700-003: Human-Computer Interaction.

Summer 2019: CS160, User Interface Design and Development (co-taught with Sarah Sterman, @UC Berkeley)