Artificial Intelligence
Building intelligent machines that complement human reasoning and extend what people can do.
Event
Causal Machine Learning Day 2020
The Causal ML Day 2020 conference will bring together academics, researchers, and business practitioners who are developing innovative ways to use machine learning techniques to improve causal inference.
Group
Causality and Machine Learning
At Microsoft Research, our causality research spans a broad array of topics, including: using causal insights to improve machine learning methods; adapting and scaling causal methods to leverage large-scale and high-dimensional datasets; and applying all…
Video
Data Visualization: Bridging the Gap Between Users and Information
With the explosion of data available today, finding effective ways for humans to interact with that data represents an enormous opportunity for researchers. At present, the ability to understand the nuances of visualizing data extends…
Video
First-person Perception and Interaction
MSR Distinguished Lecture Series: First-person Perception and Interaction Computer vision has seen major success in learning to recognize objects from massive “disembodied” Web photo collections labeled by human annotators. Yet cognitive science tells us that…
Project
Accelerating Biodiversity Surveys with AI
Biodiversity is declining across the globe at a catastrophic rate, as threats from human settlement expansion, illegal wildlife killing, and climate change place enormous pressure on wildlife populations. Conservation biologists are faced with the daunting…
Publication
Embracing Digital Transformation as-a-Service
Publication
Randomized Smoothing of All Shapes and Sizes
Project
Land Cover Mapping
Our land cover mapping work uses computer vision to accelerate the process of turning remote sensing data into land use and land cover information, so that environmental scientists and geospatial analysts can spend less time…