Hello! I'm a recent computer science PhD graduate specialized in human-computer interaction at the Paul G. Allen School of Computer Science & Engineering. I'm advised by James Fogarty and Sean Munson. I received my undergraduate degree in computer science from Pomona College. I'm currently a Senior Research Scientist at Evidation Health.
My research focuses on designing, developing, and evaluating tools that can help people and their health providers better understand and manage their personal health. I have extensive experience in conducting formative studies to identify needs and opportunities; iterative design and development of novel methods and tools to support those needs; and evaluations to examine usage and develop design implications for future tools. Throughout my PhD, I have surveyed more than 1,100 people; interviewed more than 100 people; developed interactive visualizations and mobile applications to better support personalized health; and conducted quantitative and qualitative analyses of survey, interview, and app usage data.
My multidisciplinary research has been supported by a National Science Foundation Graduate Research Fellowship; received a Best Paper Award (CHI 2017) and two Best Paper Honorable Mentions (CHI 2017, DIS 2018); and directly informed grants from both the National Science Foundation (IIS-1813675) and the National Institutes of Health (R01-LM012810).
More details on my research and approach can be found on:
My research focuses on helping individuals and their health providers better understand and manage their health. My general approach includes:
Formative Work through surveys and interviews to identify needs, challenges, and opportunities
Iterative Design and Development through prototypes and implementations to create tools that support people and providers
Evaluations through deployments with pre- and post-interviews to examine how those tools could be used
I have applied this approach to myriad health contexts, consulting and collaborating with health professionals throughout the process to draw on existing expertise within each context.
Download my research statement for a more in-depth summary of my projects.
My current research focuses on supporting self-tracking by people with migraine. People often track migraine-related data for a number of different goals (e.g., identifying migraine triggers, predicting future migraines, sharing data with health providers), but current tools do not explicitly support the goals people want to pursue. I am currently investigating goal-directed self-tracking, a new approach for supporting every stage of self-tracking. I aim to help people: track exactly and only what they need to achieve their goals; appropriately interpret and act on their data with respect to those goals; and share their data with their health providers. This work is being done in collaboration with the UW Headache Clinic.
My investigation of supporting goal-directed self-tracking for migraine management has included the following projects:
As an intern at Microsoft Research, I worked with Mary Czerwinski and a team of HCI experts, clinical psychologists, and mobile app designers and developers to develop and evaluate Pocket Skills, an app designed to provide holistic support for Dialectical Behavioral Therapy (DBT). DBT is a type of behavioral therapy designed to treat complex, difficult-to-treat disorders and suicidal ideation. We aimed to support people in learning, practicing, and implementing DBT skills to help them solve problems, maintain relationships, and navigate negative events and emotions.
My investigation of supporting behavioral therapy has included the following projects:
My earlier work focused on supporting IBS trigger identification. People with IBS experience gastrointestinal symptoms that are often caused by personalized food triggers (i.e., different foods are more or less problematic for different individuals). Providers often advise people with IBS to record their food and symptoms in journals to attempt to find correlations, but lack the time and tools necessary to interpret the resulting data. I worked with a multidisciplinary team of health and technology researchers to investigate how to help people with IBS and health providers identify personalized IBS triggers. We aimed to support lower-burden data collection; actionable data interpretation; and patient-provider collaboration.
My investigation of supporting trigger identification has included the following projects: