研究组
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The Microsoft Research Redmond Lab’s Central Engineering Team develops software and hardware technologies and components based on Microsoft Research innovations.
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Cloud and Infrastructure Security Group in Microsoft Research in Redmond tackles tough challenges in many different areas related to the areas of security and privacy. In particular, our group has a strong focus in Cloud Security, Infrastructure Security, Hardware Security…
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Cloud Computing and Storaging (CCS) group consists of a team of researchers and engineers that are passionate about end-to-end research. They share a common belief that the ultimate milestone of cool system research is a product of significant impact. In…
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The Cloud Systems Reliability research group at Microsoft Research aims to develop practical tools and techniques that can help cloud developers adequately debug, test, monitor, and troubleshoot their systems. Our research combines Distributed Systems, PL, Software Engineering, and Machine Learning…
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The Computer Vision Group conducts research in areas spanning AI, Machine Learning, Computer Vision, and Computational Photography. Our mission is to conduct state of the art foundational research and to create technologies that empower the use of Vision-based systems in…
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Advancing the state-of-the-art in human-computer conversation, through work on dialog management, dialog state tracking, user modeling, language understanding, and language generation.
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Collaborative biomedical research and innovation When the COVID-19 pandemic began the global science and research community quickly ramped up its efforts in society’s effort to understand, navigate, mitigate, and recover from its consequences. This included researchers, data scientists, engineers, and…
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We are hiring! Click here for details. (opens in new tab) The Data Systems group at Microsoft Research works on problems in data management. Our current areas of focus include infrastructure for large-scale cloud database systems, storage and indexing in key-value…
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The Deep Learning group advances the state-of-the-art in deep learning to achieve general intelligence. We develop algorithms, models, and systems in deep supervised and unsupervised learning, deep reinforcement learning, and neural-symbolic reasoning, and then pursue breakthroughs in computer vision, natural language processing, multimodal intelligence, time…