The Statistical, Inferential Designer
Time and again, I am struck by the significance of knowledge, how it was obtained, why it is inspired and how much more there is to know. In this presentation, I offer a glimpse into how statistical and inferential models can be used to help designers create more functional and aesthetic designs. To do this, we will journey through distinct research endeavors that can guide us toward creating places to improve memory, engage the affective senses, relay complex information and most importantly think about how we design and plan our future. Be ready to be immersed in visuals from the 2D mundane to the symphonic of bizarre VR. Whether you are aware of how (the lack of) inference does or does not influence your creative process, I hope this will inspire an approach toward generating and using knowledge in design.
I am an Associate Professor in Landscape Architecture and Environmental Planning at Utah State University. Previously I was an Assistant Professor at Kansas State University and a Postdoctoral Scholar at the University of British Columbia with joint appointments in the Institute for Resources, Environment and Sustainability, Computer Science and Faculty of Forestry. I have degrees in Business Administration, Computer Science and Forestry. As a scholar with a diverse academic background, I identify primarily as a computational environmental planner. My research spans a variety of scales, topics and disciplines. However, my primary foci are along three areas of expertise: 1) visualization and spatial data science, 2) applied computational approaches (including optimization and artificial intelligence), and 3) environmental perception and affect related to built and natural environments. I am passionate about science and planning and how we can use technology to increase our understanding of the world we live in and create.
Utah State University
Landscape Architecture | Urban, Community and Regional Planning
Chamberlain, Brent, "The Statistical, Inferential Designer" (2021). Speaker Series. 32.