Sequential Fair Allocation: Achieving the Optimal Envy-Efficiency Tradeoff Curve is a finalist for 2022 INFORMS Diversity, Equity, and Inclusion Student Paper Competition. Our paper Estimating Total Treatment Effect in Randomized Experiments with Unknown Network Structure has been published in the Proceedings of the National Academy of Sciences. Our paper Robust Max Entrywise Error Bounds for Sparse Tensor Estimation via Similarity Based Collaborative Filtering has been accepted to IEEE Transactions on Information Theory. Her research interests include algorithm design and analysis, high dimensional statistics, inference over networks, sequential decision making under uncertainty, online learning, and network causal inference. She is a recipient of the 2021 Intel Rising Stars Award and a JPMorgan Faculty Research Award. She received honorable mention for the 2018 INFORMS Dantzig Dissertation Award. She received her BS in Computer Science from California Institute of Technology in 2011. She received her PhD in 2017 and MS in 2013 in Electrical Engineering and Computer Science from Massachusetts Institute of Technology in the Laboratory for Information and Decision Systems. Prior to Cornell, she was a postdoc at Microsoft Research New England. Graduate field member in ORIE, Statistics, CAM, and CSĬhristina Lee Yu is an Assistant Professor at Cornell University in the School of Operations Research and Information Engineering. Operations Research and Information Engineering (ORIE)
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