Robert Stephany is Computing’s eighth Sidney Fernbach Postdoctoral Fellow in the Computing Sciences. Named for a former LLNL Director of Computation, this competitive fellowship is awarded to exceptional postdocs who demonstrate the potential for significant achievements in computational mathematics, computer science, data science, or scientific computing. Fellows work in the Computing Principal Directorate on their own research agenda and with a mentor’s guidance.

Robert joined the Lab in August after completing his Ph.D. in applied mathematics at Cornell University. His fellowship is just the latest step in a journey that started at an early age. Robert tinkered with computers in middle school and began participating in robotics competitions in high school, even reaching and placing in the robotics world championship multiple times.

“My biggest weakness—ironically—was code,” Robert says. “I didn’t really know how to write code and relied on friends or teammates to program my robots.” That all changed as an undergrad at the University of Texas, when Robert set out to start his own robotics team. “I wanted more direct control over the code that went on my robots. I taught myself C, and then took a course in C++. Not only did learning those skills allow me to program my own robots (and go on to win an award specifically for our robot’s code), it also shifted my attention to areas like applied math, simulation, computer science, and numerical analysis.”

Robert developed a particular interest in high-performance computing, scientific computation, and code optimization, and in graduate school he shifted his focus again to machine learning—the basis of his research today.

While at the Lab, Robert will be mentored by Youngsoo Choi in the Center for Applied Scientific Computing (CASC). Robert’s research focuses on automating the process of scientific discovery through specialized algorithms. Specifically, he aims to develop algorithms that use data to discover differential equations that describe the natural world and its physical systems. 

Robert is no stranger to LLNL. He was part of the Data Science Summer Institute in 2022, and returned a year later as a Computing intern working with CASC’s Timo Bremer. The Lab’s emphasis and opportunity for practical application and collaboration are aspects Robert finds appealing. “My Ph.D. work was very isolating,” he says. “I appreciate the collaborative aspect of the work here.”

With an eye toward collaboration, Robert is looking forward to working with scientists and domain experts to develop tools and algorithms that can address problems that real scientists face in the field. He plans to collaborate with CASC’s Stefanie Guenther and the quantum computing testbed team, as well as physicist Ben Zhu and a group working on Tokamak fusion reactors.

“Finding a governing equation for a physical system allows you to understand exactly what makes that system work,” Robert says. “Once you have such a model and a way to use it, you can simulate that system, see how it behaves in strange circumstances, and develop tools to control and manipulate it. You are literally learning how the world works, and I think that is very exciting.”

—Deanna Willis