Generating physically-consistent high-resolution climate data with hard-constrained neural networks
- Paula Harder
- Qidong Yang
- et al.
- 2022
- NeurIPS 2022
Campbell Watson is a Senior Research Scientist at IBM Research in New York. He's a global lead of Accelerated Discovery—Climate & Sustainability which includes a team of scientists across IBM's global research labs who are developing scalable technologies to address geospatial climate challenges. Campbell's work is at the intersection of climate, AI and geospatial science.
Campbell currently serves as PI on research projects with the MIT-IBM Watson AI Lab, the IBM-Illinois Discovery Accelerator Institute, and the IBM-Mila AI Horizons Network. He's also associate editor of the AMS journal 'Artificial Intelligence for the Earth Systems.'
From 2014-2020, Campbell was a core member of the IBM Deep Thunder team for weather and climate. The team was awarded a Corporate Technical Award for 'Weather Technology' in 2020—the highest technical award at IBM. Deep Thunder was the foundational technology for The Jefferson Project in which Campbell helped design & develop a rapidly-deployable modeling and observation platform for freshwater and coastal environments. In collaboration with Rensselaer (RPI), the platform was deployed in multiple lakes across upstate New York to monitor and manage harmful algae blooms.
Campbell moved to the United States in 2012 for a postdoc position at Yale University where he studied clouds physics over Dominica and gravity waves over New Zealand. He received his PhD in atmospheric science (specifically orographic precipitation) from The University of Melbourne in Australia.