Research happens across all of Google, and affects everything we do.
Research at Google is unique. Because so much of what we do hasn't been done before, the lines between research and development are often very blurred. This hybrid approach allows our discoveries to affect the world, both through improving Google products and services, and through the broader advancement of scientific knowledge.Google's Hybrid Approach to Research
Mesa: Geo-Replicated, Near Real-Time, Scalable Data Warehousing
Ashish Gupta, Fan Yang, Jason Govig, Adam Kirsch, Kelvin Chan
Sources of Traffic Demand Variability and Use of Monte Carlo for Network Capacity Planning
Alexander Gilgur, Brian Eck
Performance and Capacity 2014 by CMG Conference, Performance and Capacity 2014 by CMG Conference, Performance and Capacity 2014 by CMG Conference (to appear)
Would a privacy fundamentalist sell their DNA for $1000... if nothing bad happened thereafter? A study of the Westin categories, behavioral intentions, and consequences
Allison Woodruff, Vasyl Pihur, Sunny Consolvo, Lauren Schmidt, Laura Brandimarte, Alessandro Acquisti
Proceedings of the Symposium On Usable Privacy and Security: SOUPS '14, USENIX (2014)
Latest from the blog
Supporting MOOC Research at Carnegie Mellon University
In a multi-year program made possible through a Google Focused Research Award, Carnegie Mellon University researchers will tap data-driven approaches to improve learning as part of a new effort to unlock the educational potential of massive online open courses (MOOCs). The Google-sponsored research plan includes the development of techniques for automatically analyzing and providing feedback on student work, for creating social ties between learners and for designing MOOCs that are effective for students with a variety of cultural backgrounds. We're excited to support CMU's efforts to make online courses much more engaging, benefitting both students and educators around the world.
- Slav Petrov
- Natural Language
- New York, NY
Working on problems that are at the intersection of natural language processing and machine learning, Staff Research Scientist Slav Petrov actively investigates the application of syntactic analysis to the domains of machine translation and question answering. Most recently, Dr. Petrov has worked on the addition of wildcard and morphology queries to the Google Books Ngram Viewer, while also teaching an ongoing statistical natural language processing course at NYU. A native of Sofia, Bulgaria, Dr. Petrov obtained a MS in Computer Science from the Free Universtiy of Berlin and his PhD at UC Berkeley before joining Google Research in the New York office in 2009.
June 22 - 27
In June, Baltimore will host the 52nd annual meeting of the Association for Computational Linguistics (ACL 2014), drawing researchers from around the world who work on the computational and linguistic properties of language. As Gold Sponsor, Google will be on hand to take part in the conversation surrounding the latest technologies that enable the interaction between computers and human languages, such as speech recognition, automatic translation, information retrieval, text summarization, and more. Come visit the Google booth to learn more about the advances in the field of Natural Language Processing (NLP) from the Googlers in attendance.