Qin lands early stage NSF grant for transfer learning project

Hantang Qin, an assistant professor of industrial and systems engineering at the University of Wisconsin-Madison, has received an Early-Concept Grant for Exploratory Research (EAGER) from the National Science Foundation to bridge the gap between on-ground experimental data and in-space manufacturing possibilities.

Qin, whose lab develops 3D printing systems for future in-space manufacturing of electronic components, will use the funding to continue work applying a machine learning technique called transfer learning to use data from on-ground experiments to predict performance in a zero-gravity environment. Validating experimental results in zero-gravity requires costly parabolic test flights.

The EAGER program funds early stage work on potentially transformative research.