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“How can we improve the design of apps and devices to better acknowledge and account for the realities of everyday life?”

Tracking Life

Professor Daniel Epstein’s area of research — personal informatics — examines how people use devices and apps to track things about themselves, from their health and fitness to their finances and productivity. In analyzing how and why people track, he has found that user needs often vary and can differ from the technology’s intended use. For example, a food-tracking app aimed at weight loss could be used by a dieter or someone trying to identify migraine triggers. “I prototype new interfaces and designs to suggest how developers can better support different individuals’ tracking needs.”

Telling Stories

One aspect of tracking that Professor Epstein addresses is data sharing, and his prototype Yarn explores ways to improve that experience. “Right now, if you’re training for a race, you might use Strava and share that you went running,” he explains. “But what’s missing is the broader story.” Yarn exemplifies how apps could stitch together individual moments that are part of a journey, tying daily runs to an upcoming marathon or showing how tasks completed are part of a do-it-yourself project. “When you share these moments, Yarn guides you through adding context and explaining how the moment contributes to the overall story of what you’re doing.”

Putting Users First

Professor Epstein’s overall goal is to be an advocate for the people using these apps. “There’s friction in aligning what users want and what companies want.” For example, users sometimes want a break from fitness tracking, while companies push for continued use. Epstein has explored how apps can let users revisit data after they stop tracking or change visual representations to highlight different aspects of the data. “A part of being a user advocate is understanding when it’s okay to stop tracking or switch to tracking something different.”


Education

Ph.D., Computer Science & Engineering, University of Washington, 2018

M.S., Computer Science & Engineering, University of Washington, 2014

B.S., Computer Science, University of Virginia, 2012


Research Areas

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