Microsoft Research Blog

The Microsoft Research blog provides in-depth views and perspectives from our researchers, scientists and engineers, plus information about noteworthy events and conferences, scholarships, and fellowships designed for academic and scientific communities.

Most recent

  1. Microsoft Research Montreal welcomes Fernando Diaz, Principal Researcher and lead of the new Montreal FATE Research Group

    Microsoft Research Montreal further bolsters its research force this month, welcoming Fernando Diaz to the Montreal FATE (Fairness, Accountability, Transparency and Ethics in AI) research group as Principal Researcher. Diaz, whose research area is the design of information access systems, including search engines, music recommendation services and crisis response platforms is particularly interested in understanding and addressing the societal implications of artificial intelligence more generally. Immediately previous to joining Microsoft Research Montreal, he was the…

    June 22nd, 2018

  2. Announcing Microsoft Research Open Data – Datasets by Microsoft Research now available in the cloud

    The Microsoft Research Outreach team has worked extensively with the external research community to enable adoption of cloud-based research infrastructure over the past few years. Through this process, we experienced the ubiquity of Jim Gray’s fourth paradigm of discovery based on data-intensive science – that is, almost all research projects have a data component to them. This data deluge also demonstrated a clear need for curated and meaningful datasets in the research community, not only…

    June 21st, 2018

  3. Microsoft Research Dissertation Grants: Broadening the PhD pipeline to increase innovation

    Research shows that diverse teams are more productive teams. Diversity, particularly in the area of computing research, means including unique perspectives that otherwise might not have a voice, fueling innovation. These are some of the key reasons that Microsoft is committed to diversity. One aspect of demonstrating that commitment is that, for the second year in a row, we are awarding Microsoft Research Dissertation Grants to talented PhD candidates from groups that are under-represented in…

    June 19th, 2018

  4. Microsoft HoloLens facilitates computer vision research by providing access to raw image sensor streams with Research Mode

    Microsoft HoloLens is the world’s first self-contained holographic computer. Remarkably, in Research Mode, available in the newest release of Windows 10 for HoloLens, it’s also a potent computer vision research device. Application code can not only access video and audio streams but can also at the same time leverage the results of built-in computer vision algorithms such as SLAM (simultaneous localization and mapping) to obtain the motion of the device as well as the spatial-mapping…

    June 18th, 2018

  5. Using transfer learning to address label noise for large-scale image classification

    In this post, we introduce how to use transfer learning to address label noise for large-scale image classification tasks. We’ll avoid describing the approach using too much math. If you are interested in the deeper theory behind this approach, please refer to our paper, “CleanNet: Transfer learning for scalable image classifier training with label noise,” presented at CVPR 18 in Salt Lake City, Utah. One of the key factors driving recent advances in image classification…

    June 15th, 2018

  6. Believing is seeing: Insightful research illuminates the newly possible in the realm of natural and synthetic images

    A pair of groundbreaking papers in computer vision open new vistas on possibilities in the realms of creating very real-looking natural images and synthesizing realistic, identity-preserving facial images. In CVAE-GAN: Fine-Grained Image Generation through Asymmetric Training, presented this past October at ICCV 2017 in Venice, the team of researchers from Microsoft and the University of Science and Technology of China came up with a model for image generation based on a variational autoencoder generative adversarial…

    June 14th, 2018

  7. Teaching computers to see with Dr. Gang Hua

    Episode 28, June 13, 2018 - Dr. Hua talks about how the latest advances in AI and machine learning are making big improvements on image recognition, video understanding and even the arts. He also explains the distributed ensemble approach to active learning, where humans and machines work together in the lab to get computer vision systems ready to see and interpret the open world.

    June 13th, 2018

  8. Microsoft Unveils FASTER – a key-value store for large state management

    At SIGMOD 2018, a team from Microsoft Research will be presenting a new embedded key-value store called FASTER, described in their paper “FASTER: A Concurrent Key-Value Store with In-Place Updates”. As its name suggests, FASTER makes a major leap forward in terms of supporting fast and frequent lookups and updates of large amounts of state information – a particularly challenging problem for applications in the cloud today. For example, in scenarios such as Internet-of-Things, billions…

    June 8th, 2018

  9. Going beyond the research experience – Exceptional mother in 1970s Romania inspired Stefan Saroiu to know his destiny at a very early age.

    “Growing up, my mom was a programmer with a computer science degree at a time when there was no computer science department in Romania,” remembers Microsoft senior researcher Stefan Saroiu with a smile that is palpable over the telephone. As a child in late 1970s – early 1980s Bucharest, accompanying his mother to her job gave him hands-on access to an assortment of what at the time were cutting-edge minicomputers. “She inspired me and I…

    June 6th, 2018

  10. The democratization of data science with Dr. Chris White

    Episode 27, June 6, 2018 - Dr. White talks about his “problem-first” approach to research, explains the vital importance of making data understandable for everyone, and shares the story of how a one-week detour from academia turned into an extended tour in Afghanistan, a stint at DARPA, and, eventually, a career at Microsoft Research.

    June 6th, 2018

  11. Optimizing Barnes-Hut t-SNE

    Ten years ago, while writing a physics engine, I learned about the Barnes-Hut algorithm for the gravitational n-body problem. Normally, computing the Newtonian gravitational forces between n bodies requires evaluations of Newton's law of universal gravitation, as every body exerts a force on every other body in the system. Barnes-Hut is an approximation that brings that complexity down to , by treating clusters of faraway objects as single particles. An octree is used to subdivide…

    May 30th, 2018

  12. Making intelligence intelligible with Dr. Rich Caruana

    Episode 26, May 30, 2018 - Dr. Rich Caruana talks about how the rise of deep neural networks has made understanding machine predictions more difficult for humans, and discusses an interesting class of smaller, more interpretable models that may help to make the black box nature of machine learning more transparent.

    May 30th, 2018