Link to Talk Video: https://mediaspace.illinois.edu/media/t/1_5noscnjc
Abstract: Finding a good computational representation for a problem allows us to map high level objectives to low level details and select the appropriate set of algorithmic tools. Choosing – and in some cases designing – such representations is critical not only in domains with a long history of computational support but also in those that are in the early days of embracing such tools. In this talk I will discuss my work on building design and media authoring tools based on representations that align with expert thought and practice. As two different examples of this approach, I will discuss my work on text-based video editing and quilt design tools. In both of these cases, I will describe how developing a strong understanding of the application domain helps us to offload tedious steps to computation and guide users' attention toward the more creative, open-ended decisions.
Bio: Mackenzie Leake is a METEOR postdoctoral fellow at MIT CSAIL. She received her PhD and MS in computer science from Stanford University and a BA in computational science and studio art from Scripps College. Her research focuses on designing computational tools for various creative domains, including textiles and video. Her research has been supported by Adobe Research, Brown Institute for Media Innovation, and Stanford Enhancing Diversity in Graduate Education (EDGE) fellowships. In 2022 she was named a Rising Star in EECS and a WiGraph Rising Star in Computer Graphics.
Part of the Illinois Computer Science Speakers Series. Faculty Host: Colleen Lewis.
