Postdoctoral Scholar, Stanford University
Developing assessment and intervention technologies to support personal health and well-being
Today we face a healthcare system in crisis — a growing prevalence of chronic disease, disparate patient outcomes, anticipated physician shortages, and unsustainable economic costs. To address such public health challenges, the medical domain is primed for a shift towards a more preemptive, personalized, and patient-driven model of care where innovative, accessible services empower individuals to proactively manage their daily lifestyle choices and long-term wellness. Technology has the potential to support this revitalization of health care solutions by fundamentally transforming how we conceptualize, monitor, and attempt to positively influence behavior on a broad scale. However, to ensure the relevance, appropriateness, and impact of such technologies on clinical, contextual, and personal levels, it is crucial to undertake human-computer interaction research and user-centered design approaches.
My research is aimed at developing such human-centered systems, including software and devices for capturing data manually or passively, lightweight algorithms for user modeling and health assessment, and interactive interfaces to deliver tailored feedback and interventions — all the while accounting for and designing around idiosyncratic backgrounds, abilities, contexts, needs, and goals. In exploring this design space, I create systems that support use over various time scales, including tools that promote healthy daily routines (e.g., improving sleep habits or enhancing creativity), facilitate behavior change endeavors (e.g., quitting smoking or increasing exercise), and assist in long-term management of chronic conditions (e.g., pain, serious mental illness, and neurodegenerative diseases). Working in these application areas also enables a breadth of design research across behavioral, cognitive, physical, and psychological aspects of our wellness and with a variety of user groups (e.g., from toddlers to older adults, drivers to astronauts).
Altogether, my research style involves taking data-driven, evidence-based, and participatory approaches that mix quantitative and qualitative methods to (a) increase our fundamental scientific understanding about behavior, health, and technology use in real-world settings; (b) gain a deep empathy for the role of technology in a given context; (c) use such insights to inform the design of novel personalized systems that can better target significant health determinants for assessment and intervention; and (d) build, deploy, and evaluate these tools with diverse populations. In this way, I strive to make methodological, empirical, and HCI contributions — and, importantly, have a concrete positive impact on people’s lives and overall well-being.
Elizabeth Murnane is a Postdoctoral Scholar in the Computer Science department at Stanford University. Broadly speaking, Elizabeth’s research interests lie in human-computer interaction, personal informatics, recommender systems, social computing, and personalization. Her overarching goal is developing technologies that are aware of idiosyncratic user needs and empower people in managing various aspects of their daily lives and wellness. She is particularly compelled by applications in the domains of personal information management, civic participation, and medicine. Currently, she is most focused on the health domain — building tools that capture and analyze personal data to support self-management of physical, cognitive, and mental health.
In 2017, Elizabeth received her Ph.D. in Information Science from Cornell University, where she was supported by an NSF Graduate Research Fellowship. Before graduate school, Elizabeth co-founded and was the lead engineer of an MIT CSAIL spin-off that built interactive visualization tools to help software developers make sense of and share important aspects of source code. Prior, she received her Bachelor of Science in Mathematics with Computer Science from MIT, where her undergraduate research focused on information visualization and conversational agents.