Previously a PhD student at the BITLab at Michigan State University where I worked with Rick Wash.
Master's degree in HCI (UX design and research) from University of Michigan School of Information and Bachelor's in human factors engineering from University of Utah Dept. of Psychology
Intelligent Systems and Decision Making
Research to understand how the user experience and interface design of intelligent systems (e.g. recommender systems, tools for analytics and data science, expert systems etc.) influences the decisions people make. Active
How do people allocate their attention across the many different actors who influence their interaction with a computer (e.g. the computer itself, software, servers, other users, programmers, companies etc.)
People's health information is scattered across fragmented systems, making it hard to get the right info at the right place and time in order to make good health decisions. I am designing and studying a platform that emulates sites like ifttt.com and Microsoft Flow (which currently have very little integration with health systems) to see whether this style of end-user-programmed integration of different systems and personal informatics automation can help people fill gaps in functionality and improve overall access and usability of health IT, and ultimately make better health decisions.
Working with Dr. Sameer Saini at the Ann Arbor VA, I have designed and developed an online decision aid to help clinicians decide whether the benefits of a colonoscopy are worth the risks for a patient given some individual characteristics. This aid can help clinicians make more personalized decisions about screening and highlights some particular examples of patients whose risk and benefit from screening runs counterintuitively from established guidelines.
I currently work on an AHRQ-funded grant
My dissertation research looked at the ways that the design of intelligent decision aids (decision aids that use artificial intelligence or similarly sophisticated computation to make recommendations to decision makers) can create decision making biases.
I found that the customizability of the system, the transparency, and users expectations of its efficacy can cause users to agree with system recommendations regardless of what recommendations are given.
Going forward, I plan to extend this research to the design of tools for data science. How can we design tools that enable data scientists to both uncover important insights and make good decisions from data?
I have worked with Rick Wash to study how the design of crowdfunding platforms influences users' ability to coordinate their collective efforts and successfully fund projects.
Our research has mainly involved controlled lab experiments that simulate crowds on a crowdfunding site, where we have found that the style of crowdfunding (All-or-nothing vs. Keep-it-all) and the timing of donations have important consequences for project outcomes.
I have studied the design of Online Communities with my PhD advisor Rick Wash, where have found that early contributions to online communities set an expectation for newcomers about what is required, and that if new users do not see the existing content on a site they are likely to contribute more.
We have also found that communities should be designed to attract members rather than content, as communities such as WikiProjects on Wikipedia will have more long-term growth if they attract many new people rather than getting a smaller number of people to contribute more content.
I did UX design and usabilty testing for OERca, a tool that allowed users to clear educational content of copyright restrictions so it can be openly published. More info about this tool is available on Github
Privacy and Behavioral Advertising
A project with Yvette Wohn, Dan Sarkar, and Kami Vaniae looking at people's attitudes and beliefs about behavioral advertising.