Assistant Professor at Parsons School of Design. Formerly director of the Master of Science in Data Visualization. I teach courses in data visualization, statistics, machine learning, data structures, and programming. My research interests include graphical perception and the visual display of uncertainty and measurement error. Previously a Research Associate at MDRC.
Although there are many statistical conventions for the mathematical expression of uncertainty in data, there are far fewer graphical methods and techniques. My research and practice seeks to explore new ways to render representations of uncertainty in data visualization and make connections to the fine arts. Many data visualizers ignore uncertainty, which has made it especially interesting for me and worthy of urgent pursuit. Without an expression of uncertainty, consumers of data visualization may interpret more confidence in the data than is warranted. My primary scholarship focuses on this problem, informed by my background and experiences as a statistical analyst, researcher, and technologist. With collaborators, I have recently presented this work at IEEE VIS in the Visual Arts Program in Berlin (2018), the American Association for Public Opinion Research in Denver (2018), and the European Survey Research Association in Lisbon (2017).
At the interdisciplinary intersection of the arts and sciences, my courses address analytical methodologies (e.g., statistical analysis, natural language processing, data science) and command of technology and computing (e.g., database design, cluster computing, statistical computing). In every course I teach, methodological and technological rigor are cornerstones of an integrated design practice and important lenses for design critique. All my courses, regardless of domain, address data fluency, methodological rigor, computational sophistication, and a deep connection to art and design. I value harmony between mastery of skill and deep critical thinking. In the 20/21 academic year, I am teaching Data Structures and Machine Learning.
I was the inaugural director of the M.S. Data Visualization program at Parsons, 2015 to 2019. I led the working group in the Provost's office that proposed the program, developed the curriculum, and submitted for accreditation by the Middle States Association of Colleges and Schools and the National Association of Schools of Art and Design. I have delivered multiple talks and workshops, including engagements at South by Southwest, Visualized, and the Cannes Lions International Festival of Creativity. I currently sit on the committee for research, scholarship, and creative practice.