Ian Li


Contact

UX Designer/Engineer

ianli [at] ianli [dot] com

Google
1600 Amphitheatre Parkway
Mountain View, CA 94043


About

I'm a UI designer/engineer at Google.

Before Google, I was a Ph.D. student in the Human-Computer Interaction Institute at Carnegie Mellon University. My advisors were Anind Dey and Jodi Forlizzi. My research was on personal informatics tools, tools that help people understand their own behavior. My dissertation explored how contextual information can improve self-knowledge in personal informatics systems.


Publications


Ian Li, Anind K. Dey, Jodi Forlizzi
ACM Transactions on Computer Human Interaction, vol. 19(1), pp. 1-21

Ian Li, Anind K. Dey, Jodi Forlizzi
Ubicomp 2011, pp. 405-414

Ian Li, Anind K. Dey, Jodi Forlizzi
CHI 2010, pp. 557-566

Ian Li, Jeffrey Nichols, Tessa Lau, Clemens Drews, and Allen Cypher
CHI 2010, pp. 723-732

Ian Li, Jodi Forlizzi, Anind Dey, and Sara Kiesler
DPPI 2007, pp. 194-208

Anind Dey, Raffay Hamid, Chris Beckmann, Ian Li, and Daniel Hsu
CHI 2004, pp. 33-40

Gary Hsieh, Ian Li, Anind Dey, Jodi Forlizzi, and Scott Hudson
Ubicomp 2008, pp. 164-167

Scott Davidoff, Carson Bloomberg, Ian Li, Jennifer Mankoff, and Susan Fussell
CHI 2005, pp. 1331-1334

Projects


My Ph.D. thesis explores the use of contextual information in personal informatics systems to help users understand the factors that affect their behavior. Most personal informatics systems only show one type of behavioral information, which makes it difficult to discover the factors that affect one's behavior. Supporting exploration of multiple types of contextual and behavioral information in a single interface may help.


This is a model of personal informatics systems that we hope would be valuable for research and development. It provides a common framework for describing, comparing, and evaluating the growing number of this class of systems. This model is composed of five stages (preparation, collection, integration, reflection, and action). These stages have four properties: barriers cascade to later stages; they are iterative; they are user-driven and/or system-driven; and they are uni-faceted or multi-faceted.


IMPACT

IMPACT, Improving and Motivating Physical Activity using ContexT, is a system that monitors and informs users about their physical activity and the context in which the activities happen. The system shows real-time information on a phone interface and historical information on a desktop and online interface. By contextualizing physical activity, the system increases users' awareness of their physical activity.


Presentations


Quantified Self 2011 Amsterdam

Quantified Self 2011 Amsterdam