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Congratulations to Harita Dellaporta for receiving the at the premier conference in Artificial Intelligence and Statistics (AISTATS) 2022 for her paper on Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap.

We are pleased to report that members of the department's Theory and Foundations research theme have had four papers accepted to the (STOC 2022), the ACM flagship conference in theoretical computer science. The papers are:

• "Deterministic Massively Parallel Connectivity" by Sam Coy and .
• "Improved Approximation Guarantees for Shortest Superstrings using Cycle Classification by Overlap to Length Ratios", by , Nicolaos Matsakis, and Pavel Vesel媒.
• "Hypercontractivity on High Dimensional Expanders" by , Noam Lifshitz, and Siqi Liu.
• "Worst-Case to Average-Case Reductions via Additive Combinatorics" by Vahid R. Asadi, Alexander Golovnev, , and Igor Shinkar.

We are delighted to announce that Peter Kiss, a PhD student in the Theory and Foundations Research Division, has won the Best Student Paper Award at the conference for his single-author paper on "Deterministic Dynamic Matching in Worst-Case Update Time". Computing a maximum matching in a graph is one of the most fundamental problems in design and analysis of algorithms. The paper makes important progress on this problem in a setting where the input graph is changing over time via a sequence updates, and one wishes to maintain a large matching efficiently in such a dynamic graph. Along the way, the paper develops a general purpose technique for converting any dynamic algorithm with amortised update time into one with worst-case update time, provided the initial algorithm is able to handle a more general form of batch updates.