Professional Faculty and Postdoctoral Scholar
- B.A., anthropology, Brown University
- Master of Information Management & Systems, UC Berkeley
- Ph.D., human centered design and engineering, University of Washington
I've previously conducted research at Lawrence Berkeley National Lab on the use and design of energy-saving devices, and at the University of Washington's Human-Centered Data Science Lab on tools for scientific collaboration and learning. Prior to working in academic and government research, I founded and ran a digital media start-up for several years in Austin, Texas.
- Human Centered Design & Engineering Graduate Innovation Award, University of Washington, 2015
- Graduate School Presidential Dissertation Fellowship Award, University of Washington, 2014–15
- Best Paper Award: Education Outreach and Training, Extreme Science & Engineering Discovery Environment (XSEDE) Conference, 2013
- James R. Chen Award in Analysis of Information Systems, Information School, UC Berkeley, 2011
I focus on data visualization, human-computer interaction, game-based learning, and analytics.
In my research, I design games and software tools that inspire playfulness and engagement with data for diverse groups, ranging from seasoned scientists to youth. My work focuses on two interrelated areas: the design and evaluation of games for data science learning and discovery, and research on data visualization and collaboration in science.
I'm driven by issues of data access and thinking about how data exploration can be made more accessible to many types of audiences, ranging from career scientists to youth in the most diverse school districts in the country. I think fun is key here. While many people might not immediately associate the term "data" with "fun," I aim to change this perception and show how fun and enjoyment are important to the design of the next generation of data analytics and visualization tools.
The multidisciplinary nature of I School is really fantastic. The fact that a range of experts, from software developers and political scientists to sociologists and machine learning specialists, are all collaborating and talking with one another really elevates the thinking and experience here. Data exists within very human contexts and processes, and the Berkeley I School is a place that really celebrates these many contexts.
Data science as a field continues to reinvent itself. The astonishing growth of data collected hasn't been able to solve the world's toughest challenges by sheer size alone. I'm excited to see the increased value placed on understanding the human context in which the data lives and how this shapes the types of questions we ask.
An understanding of people and practices is equally valuable for data scientists, along with the skills you might expect in programming, data analytics, statistics, and machine learning. The more you can understand about organizational contexts, value systems, and political structures, the better the questions you'll be able to ask about your datasets and the more effectively you'll be able to communicate your findings.
I love to be outdoors whenever possible, whether it's hiking or being out on the water. I've done Hawaiian outrigger canoeing for many years, and I actually started out paddling on the Hudson River when I was living in New York City, which might seem an unlikely place for the sport. I definitely appreciate the accessibility of nature here on the West Coast.
I'm currently reading The Form Within by Karl Pribram. It chronicles his life's research as a leading brain scientist and the starting point of such theories as the holographic brain. Also on my Kindle nightstand is Augustus by John Williams. Long before there were terabyte electronic databases and email, there were letters, journal entries, and paper archives. Williams weaves these older forms together into a compelling and at times brilliantly conceived fictional narrative of the first Roman Emperor.
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