Protecting the Country with Physics
November 19, 2021
If you read Ben P.’s long list of college degrees, you might guess he’s either a physics professor or a rocket scientist at Cape Canaveral.
Only one of those answers is correct, and only partially correct, at that.
Ben simply calls himself a scientist. And although he has taught data science to grad students at the University of Maryland, Baltimore County (UMBC), his full-time gig is behind the gates of the National Security Agency.
That’s where he puts his Ph.D. in physics to work, transforming real-life problems into mathematical models to uncover answers to some of the world’s most challenging problems.
The problems are sometimes unique to the agency, but more often unique to the upper domain of high-performance computing – think NSA, Google, Facebook or Amazon.
For instance, how do you efficiently power an enormous, high-performance data center? Most people don’t realize it, he says, but large data centers use about as much power as a small city.
Modeling these problems and others, Ben helps to improve the agency’s infrastructure, which then empowers others to advance the agency’s mission, which is ultimately the safety and security of the United Sates.
“We are able to apply data science to non-mission problems and obtain significant benefit to the mission,” he says.
Even in this one example, however, it can’t be said that NSA’s approach is exactly like that of the big tech giants. When you’re employed by the private sector, time is money, and the freedom to explore is limited by the tolerance for financial loss.
Ben says he doesn’t face that obstacle at NSA.
“The stability of the work environment enables risk taking that might not be accessible if short-term profit were the driver,” he says. One other big difference, although not one of process or resources, is the ability of NSA to retain the best minds in the business to tackle those problems, because the heavy weight of burnout doesn’t lay upon NSA professionals as it often does in profit-driven industries.
“It’s amazing,” Ben says. “Being restricted to only 40 hours per week, with flexible work hours and credit hours, enables a long-term career.
Another key to the puzzle is collaboration with world-class experts, a part of the job that Ben cites as highly appealing. He works with electrical engineers, computer engineers, mechanical engineers and mathematicians, among others, expanding his understanding of how his discipline intersects with other domains.
His work has also broadened his own palette of skills and abilities. With a background in computational physics (as opposed to theoretical or experimental physics), he was already exposed to programming, but NSA has taught him new programming languages and unique computational best practices.
All of this adds up, he says, to a culture of “advanced research with tangible impact,” a place where both experienced professionals and recent graduates can learn and grow.
He recalls a data science student he taught at UMBC who is now flourishing at NSA.
“You don’t have to be some kind of wizard,” he says. “You just need the confidence to gain skills and be productive.”