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25.12.2022 | א טבת התשפג

Prestigious Fellowship Awarded to Bar-Ilan PhD Student

Shauli Ravfogel selected as one of four Bloomberg Data Science PhD Fellows

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Bar-Ilan University student Shauli Ravfogel is among this year's new cohort of four early career researchers who have received the Bloomberg Data Science Ph.D. Fellowship for 2022-2023. Ravfogel, a second year PhD candidate in the University's Natural Language Processing Lab, is the only Israeli among this promising group.

Now in its fifth year, the Fellowship is part of Bloomberg's larger efforts to engage the academic research community. The program awards financial aid and professional support to Fellows as they research their interests and gain real-world professional experience over the course of the academic year.

Despite the impressive success and wide applicability of neural network methods ("Deep learning") for NLP, the ability to control the inner representations that drive these models is limited. This lack of control can result in undesired biases and in a lack of understanding in how the model makes predictions. In the NLP Lab at Bar-Ilan, Ravfogel is developing tools that would aid end-users in guiding the behavior of models according to their individual needs.

"During my fellowship, I aim to explore ways to bridge the gap between the expressiveness of neural models and their opaque, black-box nature," says Ravfogel, whose doctoral adviser is Prof. Yoav Goldberg, from Bar-Ilan's NLP Lab and Department of Computer Science. "I hope to collaborate with Bloomberg's AI researchers and engineers to explore some of the real-world challenges that are the result of the inability to control the behavior of neural models, among them the lack of interpretability and explainability. With its massive NLP infrastructure, Bloomberg is a good place to learn about these difficulties, and to develop techniques to handle them."

Ravfogel and the additional members of the cohort -- from the University of Washington, Princeton University, and the University of Notre Dame -- are engaged in research relating to ongoing areas of interest at Bloomberg. They were selected by a committee of Bloomberg data scientists from across the organization. The goal of the Fellowship is to provide support and encouragement for a successful Ph.D. candidate, resulting in groundbreaking publications in both academic journals and conference proceedings, application development, open source contributions, and other forms of research dissemination. They will also be supported through mentorship, career counseling, and research internships.