Professor Elizabeth Qian has received the National Science Foundation’s (NSF) Faculty Early Career Development Program Award (CAREER). This five-year award, totaling over $599,000, will support her group’s work developing new computational methods to support engineering design, as well as educational efforts to train engineers at Georgia Tech and beyond in these cutting-edge methods. 

Qian leads the Aerospace Computational Engineering (ACE) Group where her research focuses on developing faster computational methods for engineering decision-making, including model reduction, scientific machine learning, and multi-fidelity methods. These approaches strive to create efficient and trustworthy computational tools that can help engineers understand the impacts of different design choices in a variety of applications. Qian’s proposal, Multifidelity Scientific Machine Learning for Design, specifically aims to help engineers combine results from different simulation models when making design decisions. 

“Engineers often have multiple different models available to them, each with different strengths and weaknesses in terms of how accurately they capture certain physical phenomena and how much they cost to run,” said Qian. “The goal of this research is to use machine learning methods to efficiently unite the strengths of all of the models available to you.”

Qian hopes to develop general frameworks that can be used across diverse applications and design contexts. For example, a manufacturing firm may use a model to estimate impacts of manufacturing variations on the performance of a product, but can also use the same model to optimize for new, more efficient designs. 

The award will also support educational initiatives for both Georgia Tech students as well as professional engineers that will offer opportunities to learn cutting-edge computing and machine learning skills. The NSF CAREER award is unique among federal grants in emphasizing education activities that are integrated with the research project. 

“NSF’s support of STEM education is so impactful in enabling students and professionals to keep their skills up to date, which enables the US to maintain its position as the world’s leader in science, technology, and innovation,” said Qian. “Teaching modern computational skills is a passion of mine, and I’m grateful for NSF’s support of these efforts.”