Microsoft Research

P is a programming framework for design, implementation, and validation of event-driven asynchronous systems.

Reproducibility is important in computing, whether reproducing bug reports or scientific results.

Sensing, Computing and Communication are essential components of an IoT system.

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

Energy breakdown: the process of breaking down a home's energy consumption into constituent appliances, is considered an important step towards energy saving in the residential setting.

The constant-time programming discipline is an effective countermeasure against timing and cache-timing attacks, which can lead to complete breaks of otherwise secure systems.

1:15 – 2:00PM Challenges of Electronic Structure Calculations on Quantum Computers Speaker: Sabre Kais, Purdue University and Qatar Environment and Energy Research Institute Abstract: The exact

Isoperimetry is a well-studied subject that have found many applications in geometric measure theory (e.g.

For the last 20 years, Conservation Northwest has been leading the effort to help wolves return to Washington State.

The similarity distance measures how "similar" two nodes in a dense graph are. Selecting an epsilon-net with respect to this metric is a useful tool in algorithms for very large graphs.

We are exploring a learning-based approach to the acceleration of approximate programs.

Worldwide, a billion people—including those in western North America—depend on winter snowfall and subsequent spring melt for their water.

Vote privacy is a central aspect of most of our elections. It is however not an absolute property: it will depend on the ballot format, tallying rules, voter turnout and preferences.

Myth -- and grapevine -- has it that the Micali-Vazirani maximum matching algorithm is "too complicated".

Research community has done a significant amount of work on authenticating users based upon their typing behavior.

In the "expansion profile" problem and the "small-set expander" problem we are interested in the following question: given a graph and a parameter k, find the subset of k or fewer vertices with the

Stochastic Gradient Descent (SGD) has become popular for solving large scale supervised machine learning optimization problems such as SVM, due to their strong theoretical guarantees.

In this talk, I will show that it is possible to reduce the display power consumption of LCD-based devices by up to 35 to 40% with no noticeable impact on end user performance.

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

In this talk I will present some of my works as a media artist and researcher and show how, depending on the academic/social context, these can flip as a Necker cube between the realms of Media Art

"BigData: Probabilistic Methods for Efficient Search and Statistical Learning in Extremely High-Dimensional Data This talk will present a series of work on probabilistic hashing methods which

3:45 – 4:30 PM Impacts of Quantum Information in Quantum Chemistry Speaker: Garnet Chan, Princeton University Abstract: I will describe recent intersections between quantum information and quantum

10:45 – 11:30 AM The Blurring Interface Between Quantum Computing and Quantum Chemistry Speaker: Jarrod McClean, Harvard University Abstract: Quantum computing offers promising new solutions to

9:00 – 9:15 AM Welcome and Introduction Speaker: Michael Freedman, Microsoft Station Q Bio: Michael Freedman is Director of Station Q, Microsoft’s Project on quantum physics and quantum computation

I will introduce a bug finding technique for concurrent programs over a finitized data domain and a general framework for underapproximations arising from it.

In this talk, we will present the MemCAD analyzer, which relies on a parametric abstract domain for the static analysis by abstract interpretation of programs which manipulate complex and

Ergodic Theorems are widely used in dynamical systems and Probability Theory.

Linear classification is a useful tool for dealing with large-scale data in applications such as document classification and natural language processing.

Effective static analyses have to deal with the approximation of the heap structure and the information about values.

"TARDIS: Time and Remanence Decay in SRAM to Implement Secure Protocols in Embedded Devices without Clocks Lack of a locally trustworthy clock makes security protocols challenging to implement on