I'm a postdoctoral scholar at the University of California, Irvine, advised by Anne Marie Piper and Erik Sudderth. My research in human-computer interaction and machine learning aims to develop systems that make accessing visual information interactive and more reliable for blind and low-vision people.
I completed my Ph.D. in Technology and Social Behavior (TSB) at Northwestern University, advised by Haoqi Zhang and Darren Gergle. My dissertation argued that the next generation of workers must develop effective work practices for self-directing their work process, not just domain- or job-specific skills. I conceptualized and built Situated Practice Systems that provide workers with practice support that help them understand issues in their work practice and scaffolds opportunities to devleop effective practices, which existing workplace systems largely lack in favor of task support (e.g., task tracking; resource management). Technically, my research introduces computational abstractions to model situated work practices which help workers specify how a machine should track and surface tailored practices to workers in the relevant contexts across a workplace (e.g., at weekly planning meetings).
My research draws from the fields of Human-Computer Interaction (HCI), Social Computing, the Learning Sciences, Management and Organizational Sciences, and Artificial Intelligence. I take a socio-technical approach to system design, where I consider how new technologies reflect an organization's work processes and social structures, and study how they are affected by the introduction of the technology. I leverage a variety of methods, including design research, UX methods (e.g., ethnography, large-scale surveys, prototype testing, etc.), qualitative analysis (e.g., thematic analysis), and quantitative analysis (e.g., factor analysis, regression, multilevel models).