Google Research Europe

About our work

Google Research, Europe is an environment where software engineers and researchers specialising in machine learning have the opportunity to develop products and conduct research in our Zürich office, as part of the wider efforts at Google. We solve big challenges across a range of computer science disciplines, with our research strongly focused on the following areas:

  • Algorithms & Optimization - We focus on algorithmic foundations of machine learning, distributed optimization, data mining and data-driven optimization. Our researchers are involved in both long-term efforts as well as immediate applications to Google technologies.
  • Data Compression - We think users’ time is valuable, and that they shouldn’t have to wait long for a web page to load. Our data compression team builds, open-sources and helps to standardize efficient lossy and lossless compression methods for better space utilization and faster page loads.
  • Machine Learning - We gain strong insights on the theoretical underpinnings of deep learning, with a goal of accelerating the speed at which engineers can build and deploy end-to-end learned systems.
  • Machine Perception - We use computer vision and machine learning to gain a semantic understanding of images and videos and ultimately build a "common sense" knowledge.
  • Natural Language Understanding (NLU) - We help the engineering teams that are building the Google Assistant, a product that relies on both a deep semantic understanding of natural language, and on the ability to provide answers using natural language.

Some of Our Projects

To provide users with meaningful answers and deep conversations in multiple domains and languages, we are building technologies based on deep learning and pushing the boundaries on topics like NLU and question answering.
Conversational Assistant
Teams in Zurich are responsible not only for developing the engine for Knowledge Graph, but also for machine learning based transliteration for language pairs in order to power Knowledge Graph and Translate with the most relevant translation for local users.
Knowledge Graph
Google Handwriting Input lets users hand-write text on their Android mobile device as an additional input method for any Android app. Google Handwriting Input supports 98 languages in 24 distinct scripts, and works with both printed and cursive writing input with or without a stylus.
Handwriting Recognition
Our teams are working towards bringing various types of Machine Intelligence to your mobile devices. One example is the Google app on Android, which can identify ambient music with a tap of the finger, or a voice command.
Mobile Machine Intelligence
We know that your time is valuable, and that you shouldn’t have to wait long for a web page to load. That’s why we developed and open sourced a data compression algorithm that achieves typically 17-25% denser compression than gzip while offering similar decompression speed.
Brotli
We play a major role in Unicode: from the encoding standard, to internationalization and localization, to the core internationalization library for Google, Android, Chrome, as well as developed a font family called Noto, which aims to support all languages with a harmonious look and feel.
Unicode

Some of Our Team

 
Emmanuel Mogenet
Engineering Director
“Recent advances in Machine Learning have the potential to bring enormous benefits to humanity, across fields as diverse as speech and communication, to health and climate change. It is very important for all actors in society, including governments, industry and social institutions, to focus on and invest in this field of research, in order to recognize and fully develop new, exciting and useful technological opportunities.”
 
Olivier
Bousquet
 
Srini
Narayanan
 
Enrique
Alfonseca
 
Vitto
Ferrari
 
Thomas
Deselaers
 
Mark
Davis

Join the Team