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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Atlanta, GA | Posted: February 11, 2019
Allie McFadden
Communications Officer
Summary Sentence:
Raytheon awards two Georgia Tech Ph.D. students with fellowships in machine learning.
Full Summary:
No summary paragraph submitted.
Georgia Tech machine learning Ph.D. students Scott Freitas and Daniel Scarafoni are the 2019 recipients of Raytheon's Graduate Research Assistantships.Two Georgia Tech Machine Learning Ph.D. students are already celebrating good things happening in 2019. Scott Freitas and Daniel Scarafoni were recently selected for Raytheon’s Graduate Research Assistantship, with each assistantship worth $25,000.
The funding, which began on Jan. 1, will cover part of the students’ graduate research assistantships, augment their existing funding, and support travel to conferences. The funds will also help cover their advisors’ travel to conferences.
Advised by Associate Professor Polo Chau, Freitas is a first-year Ph.D. student in the School of Computational Science and Engineering. His research interests focus on machine learning and large-scale graph mining and how they apply to finance, cybersecurity, and healthcare.
“Receiving this fellowship is an honor. I’m excited for the potential collaboration this fellowship opens with Raytheon. I plan to use the academic flexibility it provides to pursue my research in developing machine learning based cybersecurity systems to detect adversarial attacks,” said Freitas.
Scarafoni is advised by Associate Professor Thomas Ploetz in the School of Interactive Computing and studies deep learning and human-computer interaction. The funding will allow Scarafoni to further pursue his goal of combining the strengths of both disciplines in order to solve problems that would be difficult to solve independently. His current work is focused on activity recognition and the interpretability of deep neural networks.
“I’m so thankful that Raytheon has given me this opportunity, and I hope to use this fellowship to uncover the applications of interpretable machine learning in human activity recognition,” said Scarafoni.
“Georgia Tech’s work in machine learning will enrich the capabilities we are developing with this important technology,” said Raytheon Missile Systems Engineering Vice President Laura McGill. “Supporting the exceptional research being conducted by Scott Freitas and Daniel Scarafoni is a win for them, their great school, Raytheon and our customers.”
