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Julia Olkhovskaya is an Assistant Professor in the Department of Intelligent Systems at Delft University of Technology. She completed her PhD at Universitat Pompeu Fabra under the supervision of Gergely Neu and Gábor Lugosi. Her research interests are primarily in designing and analyzing algorithms for sequential decision-making problems, with a specific focus on bandit problems and theoretical reinforcement learning. Olkhovskaya has published articles in prestigious conferences including NeurIPS and ALT, contributing significant findings on regret bounds and algorithms in adversarial contexts. As a researcher, she collaborates with leading academics in the field and continuously explores new methodologies to enhance learning outcomes in complex environments. Additionally, she is currently seeking PhD students for her research group, emphasizing the importance of robust algorithms in reinforcement learning.
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