Warren Davis, received his award during the conference in Washington, D.C., Feb. 7-9, 2019. The annual meeting recognizes black scientists and engineers and is a program of the national Career Communications Group, which advocates for corporate diversity.
This scientist wants to help you see like a computer.
If you saw all the aquariums that fill Davis’ home, you might think he was a pet lover. But you’d be wrong. Davis just has a passion for recreating things.
“I’ve got a sand bed that does denitrification in a certain layer,” mimicking a natural aquatic ecosystem, Davis said. “I’ve got animals that sift the sand bed so it doesn’t become anoxic. I have things that eat uneaten food particles that get trapped under the rocks.” It’s not a perfect model, he said, but it’s close.
Davis is also adept at recreating natural, mechanical processes to solve problems in engineering. In these cases, he takes natural phenomena — like air flowing over a surface or a person taking a step — and uses machine learning to explain them mathematically with an equation, also called a function. Machine learning can approximate complex processes much faster than they can be numerically solved, which saves companies time and resources if, for example, they want to predict how well a proposed aircraft design would hold up in flight. These savings compound when designers want to simulate multiple iterations.
“That’s what I do. I try to learn the functions that we care about,” Davis said.
He also has taken a leadership role helping Sandia and its business partners incorporate machine learning into their own research and development programs. On multiple occasions, he says, this addition has transformed the way they work, making their research more efficient and agile long after his project with them has ended.
The technique sometimes delivers unexpected solutions, too.
“When I’m able to take a data set and come up with something people haven’t seen before or some underlying function it is truly an amazing, almost magical feeling,” he said.
Davis’ work earned him a Research Leadership award.
Sandia news media contact: Troy Rummler, trummle@sandia.gov
Paper was published in the Journal of Policy and Complex Systems. L. W. E. Epifanovskaya, K. Lakkaraju, J. Letchford, M. C. Stites, J. C. Reinhardt, and J. Whetzel. Modeling economic interdependence in deterrence using a serious game. Journal on Policy and Complex Systems, 4(SAND-2018-7419J), 2018.
