Google’s mission presents many exciting algorithmic and optimization challenges across different product areas including Search, Ads, Social, and Google Infrastructure. These include optimizing internal systems such as scheduling the machines that power the numerous computations done each day, as well as optimizations that affect core products and users, from online allocation of ads to page-views to automatic management of ad campaigns, and from clustering large-scale graphs to finding best paths in transportation networks. Other than employing new algorithmic ideas to impact millions of users, Google researchers contribute to the state-of-the-art research in these areas by publishing in top conferences and journals.
Recent publications
Online Bidding Algorithms for Return-on-Spend Constrained Advertisers
The Proceedings of the ACM Web Conference 2023 (to appear)
Design and analysis of bipartite experiments under a linear exposure-response model
Proceedings of the 23rd ACM Conference on Economics and Computation (2022), pp. 606
Accurate global machine learning force fields for molecules with hundreds of atoms
Science Advances, vol. 9(2) (2023), eadf0873
KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals
International Conference in Learning Representation (ICLR) (2023) (to appear)
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