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
Estimating the changing infection rate of COVID-19 using Bayesian models of mobility.
medRxiv, vol. https://www.medrxiv.org/content/10.1101/2020.08.06.20169664v1.full (2020)
The Unreasonable Effectiveness of Greedy Algorithms in Multi-Armed Bandit with Many Arms
Advances in Neural Information Processing Systems (2020)
Privacy-first health research with federated learning
medrxiv, vol. https://www.medrxiv.org/content/10.1101/2020.12.22.20245407v1.full (2021)
Equitable and Optimal Transport with Multiple Agents
AISTATS 2021 (to appear)
Minimum Cost Flows, MDPs, and $\ell_1$-Regression in Nearly Linear Time for Dense Instances
The 53rd ACM Symposium on Theory of Computing (STOC) (2021) (to appear)
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