Design Mining the Web
The means and methods designers employ to draw on prior work, however, remain mostly informal and ad hoc. How can content producers find relevant examples amongst hundreds of millions of possibilities and leverage existing design practice to inform and improve their creations? My research explores data-driven techniques for working with examples at scale during the design process, automating search and curation, enabling rapid retargeting, and learning generative probabilistic models to support new design interactions. Knowledge discovery and data mining have revolutionized informatics; in this talk, I'll discuss what we can learn from mining design.
Ranjitha Kumar is a PhD candidate in the Computer Science Department at Stanford University, where she builds principled, data-driven tools for amplifying human creativity in design. Her work has received best paper awards or nominations at both of the premiere HCI conferences (CHI and UIST), and been recognized by the machine learning community through invited papers at IJCAI and ICML. She is the recipient of the 2011 Google PhD Fellowship in Design Development, and holds a BS in Computer Science from Stanford.