croll down to the bottom of Constantinos Daskalakis’ web page— past links to his theoretical computer science papers and his doctoral students at the Massachusetts Institute of Technology — and you will come upon a spare, 21-line poem by Constantine Cavafy, “The Satrapy.”
Written in 1910, it addresses an unnamed individual who is “made for fine and great works” but who, having met with small-mindedness and indifference, gives up on his dreams and goes to the court of the Persian king Artaxerxes. The king lavishes satrapies (provincial governorships) upon him, but his soul, Cavafy writes, “weeps for other things … the hard-won and inestimable Well Done; the Agora, the Theater, and the Laurels” — all the things Artaxerxes cannot give him. “Where will you find these in a satrapy,” Cavafy asks, “and what life can you live without these.”
For Daskalakis, the poem serves as a sort of talisman, to guard him against base motives. “It’s a moral compass, if you want,” he said. “I want to have this constant reminder that there are some noble ideas that you’re serving, and don’t forget that when you make decisions.”
The decisions the 37-year-old Daskalakis has made over the course of his career — such as forgoing a lucrative job right out of college and pursuing the hardest problems in his field — have all been in the service of uncovering distant truths. “It all originates from a very deep need to understand something,” he said. “You’re just not going to stop unless you understand; your brain cannot stay still unless you understand.”
Today, Daskalakis’ contributions have been recognized with the Rolf Nevanlinna Prize, which is awarded every four years and is considered one of the highest honors in theoretical computer science. The award cites his “powerful body of results” that explicate core questions in economics about how rational players behave in games and markets, as well as his more recent work in machine learning.
“I really can’t think of anyone else who has been a leader and influencer in so many areas,” said Éva Tardos, a computer scientist at Cornell University. “It’s amazing and it’s impressive.”
Daskalakis is interested only in problems that will be “wildly impactful,” said his former doctoral student Matthew Weinberg, now a professor at Princeton University. Daskalakis’ attitude, Weinberg said, has always been: “Here’s all these unsolved problems that are crazy hard and will be really impactful to solve; someone has to do it, so let’s make it be us.”
Daskalakis’ work sits at the interface between mathematics and the study of human behavior, and this is no accident. The son of two high school teachers in Athens — his father taught mathematics and his mother Greek literature and history — he spent his childhood steeped not just in science but also in the deeply human-centric mindset of the ancient Greek philosophers and playwrights.
“That’s a super important heritage that I carry,” he said. “It’s inspiring, it’s humbling, it’s a big responsibility, it’s a challenge.”
Rejecting the Satrapy
Athenians never say they’re from Athens unless their family has been there for many generations, said Daskalakis, who was born there. Instead, they say where their grandparents are from. For Daskalakis, that was Crete.
Constantinos (or “Costis,” as most people call him) spent his childhood summers there, soaking up the island’s distinct culture. Cretans have always been “troublemakers” when their freedom was taken away, Daskalakis said — they fought back vigorously against occupation by the Ottoman Empire and later the Nazis.
These heroic stories deeply influenced the young Daskalakis. “It’s not just the tales of the culture but also, like, feeling it in the atmosphere,” he said. “The proud mountains of Crete … this beautiful color and sea and landscape.”
Daskalakis is something of a proud mountain himself, with imposing features and an unruly mane of black hair atop a powerfully built 6-foot-1 frame. But his face is softened by his mild, dark eyes. He and his younger brother, Nikolaos, both consider him to be the “calm” one. “He’s a very sweet person… a very peaceful type of character,” Nikolaos Daskalakis said.
But that serene nature didn’t stop him from defending Nikolaos with his fists on more than one occasion when they were beset by bullies on the streets of Athens as teenagers. “He was very protective of me,” Nikolaos said.
Daskalakis could easily have landed a well-paying job after college, as most of his classmates did. It was 2004, and the Greek economy was booming: The nation had adopted the euro a few years earlier and was now gearing up to host the summer Olympics. But Daskalakis never considered seeking such a job. “I was looking for opportunities to do something creative,” he said.
He had found his undergraduate studies mostly uninspiring, but a 2003 summer program organized by the Onassis Foundation had given him a glimpse of a very different approach to learning. The program centered on the relationship between computer science and economics, and the foundation had attracted several luminaries to deliver lectures. “I didn’t have access to this kind of people,” Daskalakis said. “It was an eye-opening experience.”
One lecture by the theoretical computer scientist Christos Papadimitriou made an especially deep impression on him. It discussed, among other things, the problem of computing a Nash equilibrium, one of the central concepts in game theory and economics. “Little did I know that this would be my Ph.D. dissertation,” Daskalakis said.
Originated by the mathematician John Nash, the subject of the best-selling book and feature film A Beautiful Mind, the Nash equilibrium represents the most stable (and in some ways the most sensible) behavior players in a strategic game can choose. Players are at a Nash equilibrium if they’ve each chosen a strategy and none of them could have improved their lot by switching to some other strategy, given what the other players chose to do. In 1950, Nash proved that every game has a Nash equilibrium.Nash’s theorem launched the modern field of microeconomics “by allowing any economist, when contemplating some institution or market or mechanism, to sit back and think, ‘OK, let’s see what happens at equilibrium,’” said Papadimitriou, now a professor at Columbia University.
But while Nash could prove that an equilibrium always exists, his proof gave no way to find it. For complicated games, finding a Nash equilibrium might be an enormous computational challenge — and if a Nash equilibrium is impossible to compute for all practical purposes, does it even make sense to envision players finding and using its strategies? “If [a Nash equilibrium] requires the lifetime of the universe to solve, you cannot claim that you have it,” Papadimitriou said.
In the decades after Nash’s proof, researchers tried but failed to find an efficient algorithm that would compute Nash equilibria for all possible games. By the time Papadimitriou gave his lecture at the Onassis Foundation, he was convinced that the reason for this failure was that no efficient algorithm exists.
Papadimitriou had been studying the problem of computing Nash equilibria for two decades, but he couldn’t prove this conjecture. “Frankly, deep down, I didn’t expect to solve it,” he said.
“Many people viewed it as the biggest open question in algorithmic game theory,” said Tim Roughgarden, a computer scientist at Stanford University.
Fascinated by Papadimitriou’s lecture, Daskalakis ultimately decided to apply for graduate school at the University of California, Berkeley, Papadimitriou’s institution at the time. A few hours after he dropped his application in the mailbox, he ran into Papadimitriou on the street in Athens — the first time they had seen each other since the summer lectures half a year earlier. “It was very crazy,” Daskalakis said. “What’s the chance of that?”
The pair exchanged little more than a nod of greeting, but it felt like a “fateful moment,” Papadimitriou said. “We looked at each other, and I think we both knew that he would be admitted [to Berkeley] and he would be my advisee.”
“I’m not sure I believe in signs,” Daskalakis said. “But it was a very important encounter.”
