Xi Lu

Research Abstract:

Many complex health conditions—chronic diseases, serious mental health issues, and highly-infectious diseases—require people to monitor various health indicators and daily behaviors. Individuals and public health authorities recognize self-tracking technology’s value of collecting and reflecting on data to better understand and manage health. However, existing self-tracking tools typically concentrate on single data types, overlooking how conditions often require monitoring diverse data to uncover their interconnected effects. In addition, as people’s health journeys progress, their health needs and goals often evolve, resulting in new data needs. The lack of support for flexibly collecting multiple data types often leads to people abandoning or frequently switching self-tracking technologies. This disengagement may negatively impact health outcomes, resulting in people missing critical early signs of health issues and misinterpreting symptoms. My research explores how data-driven ecosystems can support complex and often-changing health needs from individual, interpersonal, and socio-cultural levels. Through understanding people’s experiences with and perceptions of how different technologies and approaches interact and intersect with one another to constitute an ecosystem for detecting, collecting, and reflecting on health data, I generate theoretical models and design insights around how to combine self-tracking technology with other technologies (e.g., social media) and human approaches to support health needs and goals. To date, I have empirically understood how people use or perceive technologies to support health needs and their pitfalls in three different health domains: food journaling, contact tracing, and pregnancy tracking. As a human-computer interaction (HCI) researcher, I utilize a mixed-method approach to qualitatively and quantitatively understand people's experiences and perspectives on how tracking technology and other approaches might support complex personal and public health needs.

Bio:

Xi Lu is an Informatics Ph.D. candidate at the University of California, Irvine, advised by Dr. Daniel Epstein. Xi received a bachelor’s degree in industrial design from Xi’an Jiaotong University, China, and a master’s degree in human-centered interaction/design from Indiana University Bloomington, United States. Her research interests lie at the intersection of human-computer interaction (HCI) and personal informatics, as she studies and designs self-tracking technology that improves people’s health and wellness. She also investigates technology beyond individual-level interactions, seeing how specific socio-cultural contexts influence people’s situated needs and uses of everyday technology. Xi publishes in top-tier HCI venues, such as ACM's CHI, CSCW, IMWUT, and DIS. Xi was awarded the ICS Steckler Family Endowed Fellowship for 2022-2023 due to her research passion for designing self-tracking technology for women’s health. Xi is currently working on her dissertation and plans to graduate at the end of her fifth year, around September 2024.