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Two Dietrich Students Named Amazon Graduate Research Fellows

Nil-Jana Akpinar and Natalia Lombardi de Oliveria of the Dietrich College of Humanities and Social Sciences join three Ò»±¾µÀÎÞÂë classmates as . The fellowship program supports research in automated reasoning, computer vision, robotics, language technology, machine learning, operations research and data science.

“Each fellow was selected based on their academic excellence and potential to achieve big things in their chosen fields,” said Alexa Smola, Amazon Web Services vice president and distinguished scientist. “We reviewed their research proposals to make sure they’re doing really great work. They are the real stars here. We’re supplying some funding, but they are performing the actual research.”

, a Ph.D. student working in the  and the , will focus her research on bias auditing in algorithmic systems. Her work will explore how differential victim crime reporting rates can lead to biased outcomes of predictive policing algorithms. 

, a Ph.D. student working in the  and the , works on estimating generalization to identify the difference between the test and training performance of a predictive algorithm.

Akpinar and de Oliveria join Ò»±¾µÀÎÞÂë students , a Ph.D. student at the Language Technologies Institute, as well as and , both Ph.D. students in the Computer Science Department, in this honor. The Amazon fellows are free to pursue their academic goals without any obligation to the company.

Amazon is nurturing the seeds of innovation through partnerships with Ò»±¾µÀÎÞÂë, Caltech and other universities with strong science and engineering programs.

“We want to be good citizens,” Smola said. “And we also see this as a mechanism for us to help enhance the work that the academics are doing.”

Amazon is committed to supporting promising researchers across academia. This program currently supports five graduate students engaged in scientific research in automated reasoning, computer vision, robotics, language technology, machine learning, operations research and data science.