When world-class research organizations work together on a long-term basis, the whole is greater than the sum of the parts. That premise underlies Microsoft Research’s collaborative projects and joint ventures around the globe, including our recently renewed joint research center (opens in new tab) with Inria (opens in new tab) (the French Institute for Research in Computer Science and Automation).
Since its founding in 2006, the Microsoft Research – Inria Joint Centre (opens in new tab) has innovatively applied computer science and mathematics to a host of scientific challenges, from formal methods for mathematics to distributed systems and security, computer vision and medical imaging, machine learning and big data, and social networks and privacy.
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Microsoft Research – Inria includes 100 researchers overall: 40 permanent researchers from Inria, 30 permanent researchers from Microsoft Research, and 30 non-permanent researchers (interns and postdoctoral and PhD students, representing some 23 nationalities). Today, May 19, the Joint Centre continued its quest to use computing to help solve big problems, hosting an event that reported on the ambitious projects currently underway (see the list later in this blog). The event also featured the following keynotes from some of the world’s foremost computing experts, including Jeanette Wing, corporate vice president of Microsoft Research, who gave an inspiring presentation on how the joint research center is important to science, technology and society.
Jeanette Wing, corporate vice president of Microsoft Research
- “Thinking For Programmers: Rising Above the Code”: Leslie Lamport, this year’s Turing Award winner (opens in new tab) and a principal researcher at Microsoft Research Silicon Valley, discussed the need for programmers to create extremely rigorous specifications before coding complex systems, particularly concurrent and distributed systems.
- “Machine learning for Brain Imaging: from pattern analysis to brain atlases”: Bertrand Thirion, director of research at the Joint Centre, spoke about using machine learning to extract patterns of neurological activity that can lead to a functional atlas of the brain.
- “Formal components for the odd order theorem”: Georges Gonthier, principal researcher and team leader at Inria, focused on how to combine software engineering, programming language, and formal logic techniques to package formal mathematical theories into components that lend themselves to computer-checked formalization of results.
- “Big Learning: New Challenges and Opportunities”: Francis Bach, a senior researcher and team leader at Inria, reviewed recent developments in machine learning—such as improvements in algorithm speed and the use of generalized learning representations—that are tailored to solving modern large-scale problems.
Georges Gonthier, principal researcher and team leader at Inria
Bertrand Thirion, director of research at the Joint Centre
The Joint Centre is currently focusing on the following projects:
Projects on formal methods and their applications
- Mathematical Components aims to develop the ability of existing proof assistants, such as Coq, to automatically check difficult proofs in mathematics.
- Temporal Logic of Actions for Proof System addresses challenges in certifying correct behavior of distributed and concurrent systems, in which there is no certainty as to when distinct components will interact.
- Secure Computing develops new languages and associated certification tools to prove that implementations of cryptographic protocols are sound, thereby improving the security of Internet transactions.
Projects on machine learning and big data
- Large-scale Structured Machine Learning develops new methods for achieving efficient trade-offs between statistical accuracy and computational cost. It also develops algorithms that efficiently trade off exploration with exploitation in active learning scenarios.
- Z-Cloud Workflows develops solutions for efficiently instantiating workflows in a cloud-computing environment by mapping tasks of the workflow to specific machines. It conjointly optimizes the replication of data within the cloud computing nodes.
- Interactive Network Visualization develops tools for interacting with and visualizing data that arises from both online social networks and brain imagery, with a particular emphasis on time series.
- White Box Search-Based Software Engineering uses machine learning to improve software engineering by automatically determining software parameters and assisting developers through the recommendation of code snippets.
Projects on computer vision and medical imaging
- Video Understanding aims to extract rich features automatically from large video catalogues, in order to support semantically rich queries when searching such catalogues.
- Medilearn develops personalized models that assist in the diagnosis and treatment of heart conditions. It also focuses on identification of human brain activation patterns induced by conducting specific cognitive tasks.
Projects on social networks and privacy
- Social Information Networks develops efficient recommendation of contacts and contents to users of online social networks. It also addresses the design of reward schemes for incentivizing efficient filtering of information by users.
- Privacy-Friendly Services and Apps develops means for users to protect their private information, such as geo-localization traces, while preserving the ability of applications to provide value-added services.
All told, this one-day event captured the essence of the valuable research taking place at the Microsoft Research – Inria Joint Research Centre, and it points out the value of our long-term investments in collaborative ventures.
—Scarlet Schwiderski-Grosche (opens in new tab), Senior Research Program Manager, Microsoft Research Connections EMEA
—Pierre-Louis Xech, Microsoft Research-Inria Joint Centre Deputy Director, Microsoft France
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