The Computer Scientist Who Builds Big Pictures From Small Details
An editorially independent publication supported by the Simons Foundation.
As a teenager in the Czech Republic, Lenka Zdeborová glimpsed her future in an Isaac Asimov novel. A character in Asimov’s “Foundation” series invents a mathematical method for predicting the path of an entire civilization by averaging out the haphazard behavior of billions of individuals. The concept gave her a “mesmerizing feeling,” Zdeborová recalls — one that returned when she later encountered a method that she could actually apply to make sense of huge numbers of unpredictable elements.
“I realized, ‘Oh my God, Asimov was just describing statistical physics,’” she said, referring to a discipline that describes the big-picture properties of matter by using the rules that apply to individual molecules. As a physics master’s student at Charles University in Prague, she reveled in its predictive power. Then, while she was pursuing her doctorate, Zdeborová’s adviser showed her a paper that applied the techniques of statistical physics to theoretical computer science — the mathematical study of computation and how algorithms behave. The familiar feeling returned with a vengeance.
“I was completely mesmerized by that paper,” Zdeborová said. “I had always had this impression that to do computer science, you had to be a hacker and know everything about Linux. I realized that theoretical computer science was as fascinating as theoretical physics, and I said, ‘OK — this is what I want to do.’”
