I am a researcher. My research looks at cognitively accessible ways to visualize data through the lens of multimedia design & storytelling. I use a combination of quantitative & qualitative research methods to solve real-world problems. (Google Scholar)
Accessible Visualization for People with IDD
2018.10 - current
Keke Wu | Shea Tanis | Danielle Szafir
In this project, we collaborate with the Coleman Institute for Cognitive Disabilities to design accessible visualization for self-advocates and stakeholders among the IDD (Intellectual and Developmental Disabilities) community to explore and interact with budgetary data. We hope to support their decision making and aid their family improvement through effective visual analysis.
Publications:
Empowering People with Intellectual and Developmental Disabilities through Cognitively Accessible Visualizations - IEEE VIS for Social Good Workshop 2023
Data Data Everywhere: Uncovering Everyday Experiences for People with Intellectual and Developmental Disabilities
- ACM CHI 2023
Understanding Data Accessibility for People with Intellectual and Developmental Disabilities
- ACM CHI 2021 (Best Paper Award)
Designing Communicative Visualization for People with Intellectual Developmental Disabilities
- IEEE VisComm Workshop 2019
Color Crafting
2018.5 - 2019.10
Steve Smart | Keke Wu | Danielle Szafir
In this project, we leverage sampling-based models to better understand and predict how color manifests in different types of visualization. We seek to empower designers to craft effective color encodings through machine-learning method. We also explore general visualization color encoding principles and evaluate our auto-generated color ramps in a crowdsourcing approach. Our model aims to encourage more effective visualization by designing tools that pair perception and automation.
Publications: Color Crafting: Automating the Construction of Designer Quality Color Ramps
- IEEE VIS 2019
FieldView
2017.10 - 2019.03
Matt Whitlock | Keke Wu | Danielle Szafir
This project looks at how people perceive and interact with visual information with different display technologies, such as HMDs, mobile phones, etc. We develop guidelines, techniques, and tools that effectively leverage the capabilities of these technologies to enhance the ubiquity, accessibility, and effectiveness of data analytics and immersive visual applications. We provide a novel system to improve the collection and integration of data into fieldwork in collaboration with earth scientists and emergency responders.
Publications: Designing for Mobile and Immersive Visual Analytics in the Field - IEEE VIS 2019
Happy Ivy
2017.10 - in development
Keke Wu
This project seeks to address mental health issue like bipolar disorder(BD) with a mobile application solution, aka Happy Ivy, which is an easy-to-use daily task reminder aiming at helping BD and broad users to live a regular and healthy life. Happy Ivy is designed in a plant growing context, where the growing status of the flower is up to how the user finish scheduled tasks in the app. Finishing tasks on time will increase points in corresponding attributes. Once a flower is grown up, the user could choose to either start over with an unknown new type or grow the unlocked one again.
Hap App
2016.10 - 2017.5
Keke Wu | Pete Herzfeld
This project is a preliminary work towards mental health research. Our work focus on depression, which is prevalent among various ranges of ages, nationalities, and genders. We provide a mobile design solution to help depressed people release their pressure and have fun. We introduce a virtual guide panda to help with users’ emotion management and mood track. In the app, users have different relaxing options like listening to music, reading a joke, playing a game, or “chatting“ with the animated guide. Besides, nine basic emotion icons will be mapped with nine different funny selfie filters and the camera will get triggered when tapped by the user.
Publications: Hap App: A Mobile Design For Depression
- 2nd Symposium on Computing and Mental Health at CHI 2017
