For more than two decades Luciana Buriol has had a hand in building systems that impact our lives. From how ambulances are positioned across a city to save the most lives or how millions of orders arrive at the right door on time. And even after 20 years as a leader in her profession, she exudes a level of delight and curiosity that leaves a lasting impression.
One of six siblings who grew up on a small farm in Brazil, outside a remote farming village, computer science was never on Buriol’s radar. But in the late 1980s a middle school teacher noticed her aptitude for numbers and encouraged her to participate in a BASIC programming course.
Mentors, professors, and teachers like that spanned her entire education. After middle school, a high school physics teacher pointed her toward computer science. An undergraduate professor introduced her to optimization and convinced her to move to Sao Paulo. They all had a clear vision of the possibilities and Buriol’s potential. “They were my angels,” she says, pointing her toward opportunities she might never have known about otherwise.
“Professors are so important in the life of kids, especially the kids whose parents and environment can’t point them toward opportunities,” Buriol adds.
One of her PhD advisors, Mauricio Resende, recalls their first meeting outside a countryside hotel in 1999 the night before a conference. Buriol walked up with luggage in tow. She was just off a six-hour interstate bus ride, a two-hour intercity bus ride, and a long walk in the dark from the bus station. “That was one thing that impressed me, her determination to be there,” said Resende, who advised Buriol’s research at AT&T and now is her colleague and a principal research scientist at Amazon.
A year after their meeting, Resende, then senior principal scientist at AT&T Research, became one of Buriol’s advisors after helping her switch her PhD project. At the time she was attending Universidade Estadual de Campinas, pursuing her PhD degree in electrical engineering. She had been optimizing ambulance garage locations in São Paulo — a city of 17 million people at the time — based on emergency call data. But then she learned from Resende that AT&T had a different yet similar problem.
“At the time AT&T needed to grow a lot and quickly,” Buriol said. “The traffic of telecom networks was rapidly increasing.” So in 2001 she moved to New Jersey. She was specifically tasked with algorithms for network design and operation, deciding which nodes should be connected, and with what capacity, to optimize resource utilization for AT&T’s USA telecommunication network. Resende said her work was a resounding success — in fact it became essential to so many groups that AT&T invited her to stay an additional four months.
“Immediately she was very successful not only in the work with me but in her many collaborations with other people at AT&T. She was one of the most successful PhD students who went through AT&T,” Resende said.
She brought the same determination Resende had witnessed at the conference years before to her code. She was constantly optimizing algorithms. At the time, she said, she assumed everyone wrote that way. Implementing efficiently, planning ahead, choosing data structures for the most efficient code, that was normal to her. But when she worked at AT&T during her PhD, her technique quickly impressed her new colleagues. “They’d say things like, ’How did you do that?’” She quickly became an asset to multiple groups.
In 2002 she moved back to Brazil to finish her dissertation. And in 2005, after an 18-month postdoc in the Computer Science Department at Sapienza University, she moved back to Brazil for an associate professorship in computer science.
The position was at Federal University of Rio Grande do Sul (UFRGS), where she spent 15 years teaching and challenging her students to solve some of their university and city’s largest challenges. However, she noted, she found herself curious about other challenges.
“At some point, even the best code has an upper limit,” Buriol said. “At a certain scale the system has to be replanned.” Buriol had always been curious about these limitations and how companies solved problems too big for algorithms. For 15 years she taught and funneled students into some of the most prestigious computer science positions in the world. She led national and international scientific organizations. But all the while she wondered how the world’s biggest data problems were being solved.
Meanwhile, Resende had joined Amazon in December 2014 as a principal research scientist. The two had remained in consistent communication since Buriol’s time in New Jersey. Her students became his students and interns. They collaborated on projects.
So when Buriol started asking about exposure to Amazon — a company that was solving the problems of scale that were on her mind — it was a no brainer for Resende. He suggested she apply for the Amazon Scholar program. She was accepted for a 3-month project in 2019 and said she never planned to stay, just to learn.
“Those three months made her change her mind,” Resende said. “She was very interested in exploring opportunities for a full-time position.”
In 2021 she accepted a full-time position with the Supply Chain Optimization Technologies (SCOT) organization. Her work with the SCOT team resembles the PhD research from 20 years ago. Instead of optimizing nodes and links of a telecommunication network, she’s optimizing Amazon’s distribution network.
“I love this project. When I thought about coming to Amazon, this is what I wanted to do. It’s a huge problem, complex, and it demands that we be talking with people from different groups,” she said.
As a former professor, Buriol is in a unique position to advise young scientists. First and foremost, she says to be happy Buriol said she finds a way each day to pursue what she calls her “scientific joy”.
Her second piece of advice: Collaborate. “Sometimes people are very good from a technical skills perspective, but not good at collaboration,” she says. “If you share what you’re doing and ask questions, your projects will be better from the very beginning. Always be on the lookout for opportunities to help others, ask for help, and share your work.”
Finally, Buriol says, don’t settle. “You can always learn something new or do something even better than what you were.”
