His work has helped shape key research questions and empirical practices in reinforcement learning, a subarea of artificial intelligence
Age: 38
Marlos Cholodovskis Machado’s world opened in 2013, when he arrived at the University of Alberta to pursue a PhD in artificial intelligence. From a small town in Brazil’s Minas Gerais state, in a family without a strong academic background, Machado believed in the power of education, but never imagined how far it might take him. Neither did his father.
Machado told his father he wanted to pursue a PhD abroad. “He said, ‘I’m not going to pretend I have advice, because I never dreamed that you would get that far,’” he recalls.
Drawn to Edmonton by its reputation in AI, Machado followed a question that still drives his work: What are the underlying principles behind intelligence, and how do we learn from our experiences?
“I’ve always been a nerd,” he says, “and someone who works hard and plans ahead so that things work out.”
He completed his PhD in 2019, and his career took him to internships at Microsoft Research, IBM Research and DeepMind. After that, he got a full-time job working for Google Brain in Montreal, and his team’s work, later published in Nature, was deployed to help provide internet connectivity in Kenya.
But Machado and his wife missed Edmonton and wanted to raise their two children here. So he took a job at DeepMind in the city.
He connected with Edmonton’s AI ecosystem through the Alberta Machine Intelligence Institute and the U of A. He also served as an adjunct professor, discovering in the process that he loved supervising students.
“When DeepMind closed in Edmonton, I could have gone elsewhere,” he says. “I chose Edmonton again.”
Today, Machado is an assistant professor in the university’s department of computing science, an Amii fellow and a Canada CIFAR AI chair, who mentors students and enjoys introducing young people to opportunities in STEM.
This article appears in the November-December 2026 issue of Edify
