Abstract: Today, elicitation of human preferences has become a hot topic and its development has contributed significantly to the bloom of e-commerce. Design researchers have a particular interest in this topic, as good preference modeling is critical to user needs discovery, market prediction, and above all, rigorous design decision making. This talk will focus on three topics: (1) Adaptive interactions for preference elicitation, (2) feature learning for market prediction and (3) linking engineering knowledge with preference elicitation. We will show applications in interactive 3D vehicle modeling and optimal product design. Challenges in handling noisy responses from anonymous crowd will also be discussed.

Short bio: Dr. Yi Ren is a postdoctoral fellow at the Optimal Design Lab, University of Michigan, and will become an Assistant Professor at Arizona State University starting 2015. He earned his PhD in Mechanical Engineering from the University of Michigan in 2012 and his Bachelor’s in Automotive Engineering from Tsinghua University in 2007. His dissertation led to a three-year NSF grant on collaborative human-machine interactions for creative design using crowdsourcing. His current research interests include continuous and discrete optimization, statistical learning and product and system design.