Regularly publishes research at top-tier HCI and IR venues (e.g., ACM CHI, UIST, CSCW, CHIIR, SIGIR). Notable works include: CoNotate (CHI 2021) - Suggesting queries based on notes; InterWeave (UIST 2022) - Presenting suggestions in context; Sensecape (UIST 2023) - Enabling multilevel exploration and sensemaking with LLMs; Relatedly (CHI 2023) - Scaffolding literature reviews with existing related work sections.
Research Experience
Senior Research Scientist at Tableau Research. Focuses on intelligent computational and interaction techniques to augment exploration, sensemaking, and creativity.
Education
Received her doctorate and master's degrees from the University of California, San Diego, where she worked at The Design Lab. Before her PhD, she graduated summa cum laude with a double major in Computer Science and Psychology (specializing in Cognitive Neuroscience) from Mount Holyoke College.
Background
Research areas include Human-AI Interaction, Cognitive Science, Intelligent Information Retrieval, and Human-Centered AI. Conducts mixed-methods studies to deepen the understanding of how people search, synthesize, and create using large amounts of disparate information on the Web and with Large Language Models. Based on this understanding of user behaviors and challenges, designs and develops interactive intelligent systems that augment human cognitive abilities, particularly in discovery, sensemaking, and creativity.
Miscellany
Actively contributes to establishing diversity and inclusion programs to overcome stereotype bias and make tech more diverse; teaches computational and design thinking courses. In free time, loves playing squash and going for runs with her dog.