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de Oliveira Joins SCS Grads in Amazon Research Fellowship

Amazon awarded its second round of research fellowships to five graduate students at Ò»±¾µÀÎÞÂë

, a student in Dietrich's Department of Statistics & Data Science, joins four colleagues in the School of Computer Science in this honor, including Emily Black, Saurabh Garg, Emre Yolcu and Minji Yoon.

This program supports graduate students researching automated reasoning, computer vision, robotics, language technology, machine learning, operations research and data science. The students will be invited to interview for a science internship at Amazon.

De Oliveira is pursuing her Ph.D. in data science and machine learning. She is focused on estimating generalization — the difference between the test and training performance of a predictive algorithm. Her faculty advisor is , a professor of statistics and machine learning in MLD and Dietrich and an Amazon Scholar.

is a Ph.D. candidate in the research centers on understanding the impact of machine learning models in society. In particular, she focuses on showing novel ways that common machine learning models may act unfairly; finding ways to pinpoint when models are behaving in a harmful manner in practice; developing ways to mitigate harmful behavior when possible; and translating technical insight into technology policy recommendations. Her faculty advisor is , an associate professor in CSD and the who specializes in algorithmic fairness.

, a Ph.D. candidate in the (MLD), is interested in building robust and interpretable machine learning systems. He is researching the behavior of machine learning models in real-world scenarios and building provable methods to make progress toward relaxing simplifying assumptions to make robust and trustworthy models. Garg’s faculty advisors are , assistant professor of operations research and machine learning in MLD and the Heinz College of Information Systems and Public Policy, and a deputy dean in the Tepper School of Business; and , associate professor of statistics in MLD and the Dietrich College of Humanities and Social Sciences.

is pursuing his Ph.D. in CSD. He is interested in logic, particularly proof complexity, satisfiability solving and related topics. His research so far has investigated the complexity of redundancy-based proof systems, a rewriting-based approach to the Collatz conjecture, and learning local search heuristics for satisfiability. Yolcu’s faculty advisor is , an associate professor in CSD and an Amazon Scholar.

, a Ph.D. candidate in CSD, is working on deep graph learning with the goal to automate and democratize it by borrowing the strong generalization power of deep learning. She first identifies the essential building blocks of a graph learning pipeline, applies automation to each block using various deep learning approaches, then glues the automated blocks back into one pipeline. She hopes to provide a plug-and-play end-to-end graph-learning tool for users. Yoon's faculty advisors are , the Fredkin Professor of Computer Science and an Amazon Scholar, and MLD Professor .

De Oliveira, Yolcu and Yoon were among the five Ò»±¾µÀÎÞÂë students to receive the first round of Amazon Graduate Research fellowships. Amazon started the program to expand its efforts to help amplify the work being done by master’s and Ph.D. students. Read more about the fellowship on the .