Introducing Brightband.

Read the announcement

Brightband is making weather and climate predictable for all, to help humanity adapt to increasingly extreme weather.

Our mission

Responsibly providing advanced Earth System AI to improve weather and climate-related decisions for the long-term benefit of humanity and the Earth

Our approach

  • Target icon

    We are building an end-to-end AI Earth System for probabilistic forecasting.

  • Git Pull Request icon

    We will open source benchmark datasets, models, and metrics to establish a common task for global weather forecasting. We hope this will encourage the community to improve the state of the art.

  • Toolbox icon

    We will provide tools to academia, government, and companies for AI weather and climate forecasting.

Team

  • Amy McGovern

    Amy McGovern

    Lead AI and Meteorology Strategist - Advisor

    Thought leader and leading researcher in applying AI techniques to real-world weather applications, particularly high-impact weather. Lloyd G. and Joyce Austin Presidential Professor in the School of Computer Science and School of Meteorology, University of Oklahoma, Director and PI of AI2ES Institute - NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography.

  • Daniel Rothenberg

    Daniel Rothenberg

    Head of Data and Weather, Co-Founder

    Visionary leader in weather and machine learning. An MIT-trained meteorologist and climate scientist, he helped found the Pangeo community, served as the Chief Scientist of Tomorrow.io and a Staff Software Engineer at Waymo, and worked closely with the Google Research and DeepMind weather programs.

  • Julian Green

    Julian Green

    CEO, Co-Founder

    Successful serial AI entrepreneur, previously GM of AI moonshots at Google X, Head of Google Computer Vision products, Co-Founder and CEO of Headroom (AI Video Conferencing - acquired by Upwork), Jetpac (AI for travel recommendations - acquired by Google), Houzz.

  • Ryan Keisler

    Ryan Keisler

    Chief Scientist, Co-Founder

    Physical scientist and pioneer in AI weather forecasting whose groundbreaking 2022 paper kicked off the current wave of advancements in ML-based global weather forecasting. Previously Staff Data Scientist at KoBold Metals, Chief Scientist at Descartes Labs, and a Kavli Fellow cosmologist at Stanford University.

  • Hans Mohrmann

    Hans Mohrmann

    Geospatial Data Engineer

    Geospatial Data Engineer with expertise in scalable computation on geospatial data and a passion for enabling scientific analysis. He holds a PhD in Atmospheric Sciences at the University of Washington.

  • Gideon Dresdner

    Gideon Dresdner

    Research Engineer

    Research Engineer specializing in machine learning for physics, weather and climate modeling. He holds a PhD in computer science from ETH and has worked extensively on machine learning applications in the physical sciences.

Open roles

We’re looking for a handful of people to join our small team.

Don't see a role that fits? Click on "Join the team" and propose a role.