Microsoft Research

Online applications are vulnerable to theft of sensitive information because adversaries can exploit software bugs to gain access to private data, and because curious or malicious administrators may

Machine learning is being applied in new ways to understand people and to assist them with daily work and activities.

Microsoft Research's Chris Wendt and Dr.

As touch screens are getting smaller, soft keyboards are getting harder to use. With the Analog Keyboard Project we are exploring handwriting recognition for text input on very small touch screens.

Linear algebra is a work-horse of numerical computing. Tensor algebra is a generalization of linear algebra with applications in scientific computing, machine learning, and data analytics.

For six months Andrew Skurka skied, hiked, and packrafted 4,700 miles in a giant loop around Alaska and CanadaΓÇÖs Yukon. His route passed just beneath Mt.

Learn about Microsoft's unique approach to Quantum Computing. For more information, visit: microsoft.com/quantum

Science has long struggled to pinpoint where, precisely, our uniqueness resides.

Cardiography, quantitative measurement of the functioning of the heart, traditionally requires customized obtrusive contact sensors.

This video provides research scientists with in-depth information about using the very wide variety of services that Microsoft Azure offers.

Sphere is a multi-user, multi-touch-sensitive spherical display in which an infrared camera used for touch sensing shares the same optical path with the projector used for the display.

India has the dubious distinction of having 10 out of the 20 most polluted cities in the world.

Great leaders of innovation don't fit the conventional mold of "good" leadership. They're not visionaries who set direction and inspire others to follow.

Fireside Chat with Susan Athey and Eric Horvitz. See more at microsoft.com/en-us/research/video/fireside-chat-with-susan-athey

When performing complex gestures that require a specific form or technique, such as an exercise or playing an instrument, we use resources such as visual diagrams or videos to communicate concepts

Locality-Sensitive Hashing (LSH) is a powerful technique for the approximate nearest neighbor search (ANN) in high dimensions. In this talk I will present two recent results.

The presentation slide and the complete schedule of Dr. TLA+ Series are available at github.com/tlaplus/DrTLAPlus In this talk, we will discuss Raft and its TLA+ spec.

What happens when we die? Does the light just go out and that's thatΓÇöthe million-year nap? Or will some part of my personality, my me-ness persist? What will that feel like? What will I do all day?

Learn the basics of Microsoft's Translator Hub, and what you need to get started.

FoveAR: Combining an Optically See-Through Near-Eye Display with Spatial Augmented Reality Projections See more on this video at

Speakers: Eleanor Dillon, Principal Economist, Microsoft Research New England Amit Sharma, Senior Researcher, Microsoft Research India This session will present the two popular open-source tools

Embark on a voyage through time, infinitely scalable from the Big Bang to today, exploring this master timeline of the cosmos, Earth, life, and human experience.

The Local Search method was illustrated using three problems: Maximum cut (2-approximation), Maximum leaf spanning trees (10-approximation) and the metric k-median problem (3-approximation).

As algorithms reach ever more deeply into our daily lives, increasing concern that they be “fair” has resulted in an explosion of research in the theory and machine learning communities.

We present the first wave-based interactive system for practical rendering of global sound propagation effects including diffraction, in complex game and VR scenes with moving directional sources

The ability to computationally solve imperfect-information games has a myriad of future applications ranging from auctions, negotiations, and (cyber)security settings to medical domains.

This is a demo video of silent speech input system

Scientists and scholars across many fields seek to answer questions in their respective disciplines using large data sets.

Until recently, the wet lab has been a crucial component of every biologist.

Causal inference from observational data is a vital problem, but it comes with strong assumptions.