At an upcoming Data Science Community event, two Penn State researchers will discuss two vastly different applications of data science: to model architectural knitting and global models of ice sheet changes. The talks, scheduled for 10 a.m. on Nov. 2, are part of the Data Science Community’s lecture series that are open to the Penn State community. Advance registration is required.
Farzaneh Oghazian, a doctoral candidate working with Felecia Davis, associate professor of architecture and Carey Memorial Early Career Professor in the Arts, will start the event by discussing their team’s work exploring machine learning models for architectural knitting. Architectural knitting is a method of designing building structures that use fewer resources or have enhanced properties compared to traditional building materials, but creating them is a highly complex process. The team hopes that machine learning modeling will provide tools that allow architects and architecture students to more easily leverage architectural knitting.
Shujie Wang, assistant professor of geography, will discuss the development of data science tools specifically for investigating ice sheet loss in Greenland and Antarctica by integrating data from multiple physical science models. By developing better ways to forecast ice sheet loss, Wang hopes to improve the accuracy of sea level rise projections.
The Data Science Community is a grassroots initiative supported by Penn State's Teaching and Learning with Technology, Institute for Computational and Data Sciences and University Libraries. To learn more about Data Science Community events or to join the community mailing list, visit https://datascience.psu.edu.