We perform fundamental research in algorithms, markets, optimization, and graph analysis, and use it to deliver solutions to challenges across Google’s business.
About the team
Our team comprises multiple overlapping research groups working on graph mining, large-scale optimization, and market algorithms. We collaborate closely with teams across Google, benefiting Ads, Search, YouTube, Play, Infrastructure, Geo, Social, Image Search, Cloud and more. Along with these collaborations, we perform research related to algorithmic foundations of machine learning, distributed optimization, economics, data mining, and data-driven optimization. Our researchers are involved in both long-term research efforts as well as immediate applications of our technology.
Examples of recent research interests include online ad allocation problems, distributed algorithms for large-scale graph mining, mechanism design for advertising exchanges, and robust and dynamic pricing for ad auctions.
Featured publications
Proc. of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2017), pp. 1643-1651
Ninth ACM International Conference on Web Search and Data Mining (WSDM), ACM (2016), pp. 387-396
Symposium on the Foundations of Computer Science (FOCS) (2009)
WSDM (2015), pp. 419-420
Our work
This post presents the distributed algorithm we developed which is more applicable to large instances.
The inspiration for this paper comes from studying social networks and the importance of addressing privacy issues in analyzing such networks.
Research areas
Focus areas
Some of our people
For a hungry algorithmist Google is a smorgasbord of appetizing problems: from the best way to route Google Maps cars to create Street Views, to the best way to use satellites to create Earth imagery; from predicting what documents one might need next in Drive, to designing and optimizing advertising markets; from formalizing notions of content diversity, to identifying what is a perfect day in Paris; and so on. Bon Appétit!
We have a unique research environment for combining theory and practice. While working on foundations of machine learning, data mining, and large-scale optimization, we get to bring algorithmic ideas to life in Google systems. We advance the state-of-the-art in CS theory by publishing in top conferences. And our research has immense impact through being deployed in numerous products, from Ads to Search, and from YouTube to data center infrastructure.