Ecology and environment
Developing and adopting technologies for scientific visualization and data management that accelerate insight in the environmental and earth sciences
Highlights
Internships Ahoy! with Kirsten Bray, Wei Dai and Sara Beery
Read more about Internships Ahoy! with Kirsten Bray, Wei Dai and Sara Beery
Putting the cloud under the sea with Ben Cutler
Read more about Putting the cloud under the sea with Ben Cutler
Give your dissertation a boost with a grant from Microsoft Research
Read more about Give your dissertation a boost with a grant from Microsoft Research
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196 results found
Publication
Where there’s Smoke, there’s Fire: Wildfire Risk Predictive Modeling via Historical Climate Data
Wildfire is a growing global crisis with devastating consequences. Uncontrolled wildfires take away human lives, destroy millions of animals and trees, degrade the air quality, impact the biodiversity of the planet and cause substantial economic costs. It is incredibly challenging to predict the spatio-temporal likelihood of wildfires based on historical data, due to their stochastic nature. Crucially though, the accurate and reliable prediction of wildfires can help the stakeholders and decision-makers take timely, strategic and…
Career Opportunity
Research Intern – Urban Innovation
The Urban Innovation group at Microsoft Research pursues state of the art science and technology development for urbanization. Lines of research focus on climate change and mitigating the environmental impact of our increasingly urban world, ensuring equitable economic growth, social and environmental justice, and building strong, healthy communities. With more than 2 billion additional urban residents projected by 2050, humanity is rapidly becoming increasingly densely populated. Simultaneously, through the internet, mobile devices, and sensors and…
Career Opportunity
Research Intern – Environmental Understanding group, HoloLens and Mixed Reality Team
The Environmental Understanding (EU) team is building core computer vision (CV) technologies underlying Mixed Reality devices and cloud services at Microsoft. We work on fundamental topics ranging from real-time tracking, mapping and localization to object recognition and semantic scene understanding. We continue to advance the state of the art in computer vision, AI and deep learning. As across the rest of Microsoft, we firmly believe in developing responsible AI systems, which fosters an inclusive approach…
Group
AI For Good Research Lab
The Microsoft AI For Good team helps researchers and organizations reach solutions on some of the world’s biggest problems. Providing technology, resources, and expertise to empower those working to solve humanitarian issues to create a more sustainable and accessible world.
Career Opportunity
Research Intern – Applied Sciences Group
Research Internships at Microsoft provide a dynamic environment for research careers with a network of world-class research labs led by globally-recognized scientists and engineers. Our researchers and engineers pursue innovation in a range of scientific and technical disciplines to help solve complex challenges in diverse fields, including computing, healthcare, economics, and the environment. This is a fascinating chance to show and sharpen your skills in computer vision and machine learning with cutting edge research topics…
Publication
Multispecies bioacoustic classification using transfer learning of deep convolutional neural networks with pseudo-labeling
In this study, we evaluated deep convolutional neural networks for classifying the calls of 24 birds and amphibian species detected in ambient field recordings from the tropical mountains of Puerto Rico. Training data were collected using a template-based detection algorithm followed by a manual validation process. As preparing sufficient training data is a major challenge for many deep learning applications, we propose a novel approach that combines transfer learning of a pre-trained deep convolutional neural…
Publication
Architecting Datacenters for Sustainability: Greener Data Storage using Synthetic DNA
Global digital data generation has been growing at a breakneck pace. Although not all generated data needs to be stored, a non-trivial portion does. Synthetic deoxyribonucleotide acid (DNA) is an attractive medium for digital information storage. If kept under appropriate conditions, DNA can reliably store information for thousands of years. It also has a practical estimated density of 1 Exabyte per cubic inch, which is much higher than commercial data storage media. Buildings, infrastructure, electronic…
Publication
How machine learning can help select capping layers to suppress perovskite degradation.
Environmental stability of perovskite solar cells (PSCs) has been improved by trial-and-error exploration of thin low-dimensional (LD) perovskite deposited on top of the perovskite absorber, called the capping layer. In this study, a machine-learning framework is presented to optimize this layer. We featurize 21 organic halide salts, apply them as capping layers onto methylammonium lead iodide (MAPbI3) films, age them under accelerated conditions, and determine features governing stability using supervised machine learning and Shapley values. We…
Video
Forest Sound Scene Simulation and Bird Localization with Distributed Microphone Arrays
Audio-based wildlife monitoring is an important method for studying animal habitations and for the conservation of animal species and ecosystems. In this work, we have developed a highly efficient and scalable forest acoustics simulation algorithm, a dataset of bird audio clips and background noise clips extracted from two publicly available field recording databases, and a synthetic forest wildlife sound scene generator for distributed microphone array recording setups. We used the synthetic forest sound scenes to…
Publication
Contract Design for Afforestation Programs
Trees on farms provide environmental benefits to society and improve agricultural productivity for farmers. We study incentive schemes for afforestation on farms through the lens of contract theory, designing conditional cash transfer schemes that encourage farmers to sustain tree growth. We capture the tree growth process as a Markov chain whose evolution is affected by the agent’s (farmer) actions – e.g., investing costly effort or cutting the tree for firewood. The principal has imperfect information…