In the news | Fred Hutch Press Release

Dana-Farber Cancer Institute, Fred Hutch Cancer Center, Memorial Sloan Kettering Cancer Center, and The Sidney Kimmel Comprehensive Cancer Center and Whiting School of Engineering at Johns Hopkins – have joined forces and secured funding from AI technology leaders AWS, Deloitte,…

White icons representing AI and human computer interaction on a blue to purple to pink gradient.
Microsoft Research Blog

| Chenglong Wang, Steven Drucker, Dan Marshall, Jeevana Priya Inala, Kori Inkpen, and Jianfeng Gao

Data Formulator investigates combining UI interactions with natural language input. Powered by AI, it can help users create or adapt visualizations and supports continuous refinement through an iterative process. Now available on GitHub.

In the news | Planet

Planet’s biodiversity site monitoring program delivers an unprecedented array of high-resolution, high-frequency satellite imagery, analytics, and Planetary Variables into the hands of those who are maintaining a lifeline for biodiversity and the communities that depend on that variety of life.

On the left is a simple drawing of the lungs. The drawing shows the borders of the left and right lung as well as the trachea and the left and right main stem bronchi. The text under the drawing reads: Original image. To the right of the drawing are the 3 additional inputs of RadEdit. They are arranged vertically. On top there is an example editing prompt. It reads "Consolidation". Below there is the same drawing of the lung again but this time the left lung is shaded blue. The text reads: Edit mask according to prompt. Lastly, on the bottom, there is the same drawing of the lung but this time the right lung is shaded red. The text reads: "Do not edit mask". On the right of the 3 additional inputs there is a box saying “RadEdit”. Finally, on the right of the figure, there is the drawing of the lung again. The upper part of the left lung is shaded grey. The text reads: Edited image. Between all the elements, the drawing of the lung, the 3 additional inputs, the box that says “RadEdit”, and the edited image, there are arrows pointing to the next element from left to right.
Microsoft Research Blog

| Max Ilse, Daniel Coelho de Castro, and Javier Alvarez-Valle

RadEdit stress-tests biomedical vision models by simulating dataset shifts through precise image editing. It uses diffusion models to create realistic, synthetic datasets, helping to identify model weaknesses and evaluate robustness.

Outline illustration of Daniela Massiceti next to Martin Grayson
Microsoft Research Podcast

| Amber Tingle, Daniela Massiceti, and Martin Grayson

The personalizable object recognizer Find My Things was recently recognized for accessible design. Researcher Daniela Massiceti and software development engineer Martin Grayson talk about the research project’s origins and the tech advances making it possible.

Articles

Author: Machine Learning Group Time-series forecasting is crucial across various industries, including health, energy, commerce, climate, etc. Accurate forecasts over different prediction horizons are essential for both short-term and long-term planning needs across these domains. For instance, during a public health…

Articles

Author: Youshan Miao Today, deep learning has permeated our daily lives. As the size of models continues to grow, training these models on massive GPU accelerators has become increasingly time-consuming and costly. To effectively harness the power of massive GPUs…

In the news | Businessabc

Dinis Guarda interviews Juan M. Lavista Ferres, Microsoft CVP and Chief Data Scientist, and Director of Microsoft AI for Good Lab, to discuss the key AI For Good initiatives taken by Microsoft for the benefit of humanity. The Dinis Guarda YouTube Podcast is powered by Businessabc.net, Citiesabc.com,…

Research Forum | Episode 4 - abstract chalkboard background with colorful network nodes and circular icons
Microsoft Research Blog

Explore multimodal & small language models, plus advanced benchmarks for AI evaluation. Microsoft researchers are working on breakthroughs in weather prediction, materials design, even a new kind of computer for AI inference and hard optimization problems.