ATLAS researchers presented 10 published works and one special interest group at the 2021 Human Factors in Computing Conference, the world’s preeminent forum for the field of human-computer interaction. The conference, commonly referred to as CHI, was held virtually May 8-13, 2021. 

Researchers affiliated with VisuaLab authored four of the nine ATLAS papers admitted to the conference, two of which received awards, including "Best Paper" and "Honorable Mention."  The Unstable Design Lab had two papers accepted, while the THING, Emergent Nanomaterials, Superhuman Computing, and Living Matter labs each had one. An additional paper was co-authored by alumna Andrea DeVore TAM '18, who is not associated with an ATLAS lab.

In all, 2,844 papers were submitted to CHI 2021, 28 of which were selected for the "Best Paper" award and 114 received "Honorable Mention."  In 2020, CHI accepted nine ATLAS papers, including four from the Unstable Design Lab and one each from the Superhuman Computing, Living Matter, VisuaLab, ACME and IRON labs.
 

CHI 2021 papers, position papers and workshops by ATLAS faculty and students

VisuaLab

. [Best Paper Award].  
Keke Wu (PhD student, ATLAS), Emma Petersen, (CTD MS student, ATLAS), Tahmina Ahmad, (Computer Science BS student), David Burlinson (PhD Computer Science, University of North Carolina), E. S. Tanis (faculty, ŷ���ڱ���Ƶ Denver–Anschultz), and Danielle Szafir (faculty, ATLAS/Computer Science)
Researchers conducted a web-based mixed-methods experiment with 34 participants with and without Intellectual and Developmental Disabilities (IDDs) to identify their differences in reading data and summarized the findings into four accessible visualization design guidelines. 

Immersive Design Reviews through Situated Qualitative Feedback (workshop paper)
M. Whitlock (PhD student, Computer Science) and Danielle Albers Szafir (faculty, ATLAS/Computer Science)
This paper on Immersive Design Reviews through Situated Qualitative Feedback was accepted to the Evaluating User Experiences in Mixed Reality Workshop at CHI 2021.

VisuaLab Collaborations

Grand Challenges in Immersive Analytics 
Danielle Szafir (faculty, ATLAS/Computer Science), Matt Whitlock (PhD student, Computer Science) and 22 other international experts.
A diverse group of 24 international experts developed 17 key research challenges, providing a systematic roadmap of current directions as well as the impending hurdles to facilitating productive and effective applications for Immersive Analytics.

 [Best Paper Honorable Mention]
Willie Payne (BS/MS alumnus Computer Science/Music Composition), Mary West (PhD student, Computer Science), Carlie Charp (CTD BS student, ATLAS), Ben Shapiro (faculty, Computer Science),  Edd Taylor (faculty, Education).

Dance provides opportunities for embodied interdisciplinary learning experiences that can be personally and culturally relevant. danceON's system supports learners to leverage their body movement as they engage in artistic practices across data science, computing and dance. It allows users to bind virtual shapes to body positions in under three lines of code, while also enabling complex, dynamic animations that users can design working with conditionals and past position data. The work identifies implications for how design can support learners' expression across culturally relevant themes and examines challenges from the lens of usability of the computing language and technology.

Unstable Design Lab

Laura Devendorf (faculty, ATLAS/Information Science), , (faculty, Eindhoven University of Technology/Department of Industrial Design), , (faculty, Virginia Polytechnic Institute and State University/Computer Science).
Parent-focused smart devices and data-tracking platforms frame the responsible parent as one who evaluates, analyzes and mitigates data-defined risks for their children and family. In this article, the researchers turn away from self-improvement narratives to attend to their own experiences as mothers and designers through creating Design Memoirs, speaking directly to the HCI community from their positions as both users and subjects of optimized parenting tools.

Late-breaking work
From The Art of Reflection to The Art of Noticing: A Shifting View of Self-Tracking Technologies’ Role in Supporting Sustainable Food Practices
Janghee Cho, (PhD student, Information Science), Laura Devendorf (faculty, ATLAS/Information Science) and Stephen Voida (faculty, Information Science).
This paper explores using self-tracking technologies that might help people draw attention to the impact of their food practices on the environment and promote sustainable food habits.

Living Matter Lab 

Self-deStaining Textiles: Designing Interactive Systems with Fabric, Stains and Light
Fiona Bell, (PhD student, ATLAS), Mirela Alistar (faculty, ATLAS/Computer Science),  and Laura Devendorf (faculty, ATLAS/Information Science) 
More information
While staining happens unintentionally (e.g., spilling coffee), this paper introduces “destaining” as an intentional design tool that can be used by HCI practitioners and designers alike to selectively degrade stains on textiles in aesthetic ways. 

Superhuman Computing Lab 

Vinitha Gadiraju (PhD student, Computer Science),  Olwyn Doyle (BA Computer Science and Political Science '20) and Shaun K. Kane (faculty, ATLAS/Computer Science)
This work explores how classroom technology design can imitate the instructional strategies educators use to teach visually impaired students the academic and behavioral skills outlined by the Expanded Core Curriculum.

THING Lab & Laboratory for Emergent Nanomaterials

Soft Electrohydraulic Actuators for Origami Inspired Shape-Changing Interfaces 
Purnendu (PhD student, ATLAS),Eric Acome (Keplinger Research Group), Christoph Keplinger, (faculty, Mechanical Engineering), Mark D. Gross (faculty, ATLAS/Computer Science), Carson Bruns (faculty, ATLAS/Mechanical Engineering) and Daniel Leithinger (faculty, ATLAS/Computer Science).  
This work introduces electrohydraulic actuators capable of producing sharp hinge-like bends that can be used to actuate existing objects or fold origami creases.

OTHER

Junnan Yu (INFO PhD Candidate), Andrea DeVore (ATLAS Undergrad Alumna), Ricarose Roque (INFO Faculty)

Special Interest Group

Microbe-HCI: Introduction and Directions for Growth
Raphael Kim (Queen Mary University), Pat Pataranutaporn (MIT), Jack Forman (MIT), Seung Ah Lee (Yonsei University), Ingmar Riedel-Kruse (University of Arizona), Mirela Alistar (faculty, ATLAS/Computer Science),  Eldy S. Lazaro Vasquez (UC Davis), Katia Vega (UC Davis) Roland van Dierendonck (Studio Roland van Dierendonck), Gilad Gome (The Interdisciplinary Center (IDC) Herzliya), Oren Zuckerman (The Interdisciplinary Center (IDC) Herzliya), Angela Vujic (MIT), David Sun Kong (MIT), Pattie Maes (MIT Media Lab), Hiroshi Ishii, (MIT), Misha Sra (UCSB), Stefan Poslad (Queen Mary University).  

Microbes bring a distinct set of functional, practical and ethical ramifications in interaction design. This special interest group addresses the various forms that microbial integration in human-computer interaction can take.  The sessions are engaging, focused and orientated conversations around microbes acting as agents of interaction.

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[video:https://www.youtube.com/watch?v=nYl0ss1oJAE&feature=emb_imp_woyt]

In a world where decisions of all kinds are based on information derived from large datasets, ensuring people have access to information and understand its implications is more important than ever. The way most statistical information is made accessible is visually using charts and graphs, and the choice of which visualization to use is generally guided by the nature of the data to be communicated. However, research led by ATLAS PhD student Keke Wu finds that for those with intellectual or developmental disabilities (IDD), some kinds of data visualizations are harder to interpret than others. 

“Keke's work is really the first in the visualization community to explore the idea of cognitive accessibility,” says Wu’s advisor, Danielle Szafir, an assistant professor of computer science with ATLAS and director of the institute’s VisuaLab. “It was previously an invisible disability to the community; we were completely unaware that common best practices were creating barriers for a large number of people.”

For this , Wu and her co-authors earned a Best Paper award from the 2021 ACM CHI Conference on Human Factors in Computing Systems, the premier international conference on Human-Computer Interaction, which took place this week.

Approximately one in six children in the US has one or more developmental disabilities or other developmental delays, according to the Centers for Disease Control and Prevention. People with intellectual and developmental disabilities (IDD) may struggle with abstract thinking and spatial reasoning and, historically, have had limited exposure to mathematical and statistical training at school. 

But despite the large number of people with IDD, visualizations such as pie charts and line graphs are typically provided without consideration for the population with whom they wish to communicate. As a result, those with IDD may struggle to make sense of some kinds of visualized data, says Wu. 

The project is a collaboration with ŷ���ڱ���Ƶ’s Coleman Institute for Cognitive Disabilities, which is particularly interested in how visualizations can support people with IDD in decision-making around financial self-advocacy. In addition to Szafir, Wu's co-authors on the paper include Emma Petersen, who graduated this spring from the ATLAS Creative Technology and Design master’s program; Tahmina Ahmad, an undergraduate majoring in computer science; David Burlinson, a post-doc; and Shae Tanis, co-director of the Coleman Institute and on the faculty of the ŷ���ڱ���Ƶ Anschutz Medical Campus.

Data and social equality

At the start of her research, Wu identified three visualization design elements that could improve data accessibility: chart type, chart embellishment and data continuity. 

Together, the team conducted a web-based mixed-methods experiment with 34 participants with and without IDD over Zoom. They gave data visualization tests to both populations, measured their test completion times and accuracy, and conducted interviews with the participants about the strategies they use to make sense of data. Wu then summarized the findings into four accessible visualization design guidelines.

The researchers concluded that the best chart type differs for people with and without IDD and that pie charts should be avoided for those with IDD; that discrete data representations, such as using isotype visualizations–where discrete objects are stacked together– instead of bar graphs will lead to more accurate performance for people with IDD; that semantically meaningful chart embellishments (such as using dollar signs with charts with financial information or stick figures to represent people) will enhance data interpretation for people with IDD; and that the visual complexity of the visualization would need to be managed.

Wu says future research will include a remote participatory design workshop “to see through the eyes of people with IDD” so as to better understand how they approach data.

“It’s not just to come up with hypotheses or just do a test with people, but really engage them in this process,” Wu says.

And she says her research may benefit others, even those without IDD. “Data can be intimidating even to people without disabilities. Our project starts with a particular population and has the potential to go to a broader one.”

ŷ���ڱ���Ƶ their Best Paper award, Wu says, “CHI confirmed our vision and the potential broader impact of our work, not just for a particular population, but for social equality.”

An imaginative journey to informatics

“I care about people,” says Wu. “And I care about society.”

Realizing that technology could be a gateway to helping others, Wu applied to ATLAS Institute’s MS-Creative Technology and Design (CTD) program to hone her technical and user-centered design skills. Soon after joining ATLAS, she met Danielle Szafir and joined Szafir’s VisuaLab, where Wu pivoted her academic focus to researching how people with IDD perceive data visualizations. She subsequently joined the ATLAS doctoral program. 

“When I came to ATLAS, I  didn’t have a very heavy technology background,” said Wu, who was also recognized this year as an Adobe Research Fellowship finalist. “This project and Danielle led me to become a researcher.”

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