Name: Paul Wright
Title: Postdoctoral Research Fellow
E-Mail: pjwright@cp.dias.ie
Address: School of Cosmic Physics, DIAS Dunsink Observatory, Dublin Institute for Advanced Studies, Dublin 15, Ireland.
Biographical Sketch:
Dr Paul Wright is a Postdoctoral Researcher at DIAS, using his expertise in solar physics and machine learning to advance our understanding of solar phenomena. Paul received his PhD in Solar Physics from the University of Glasgow in 2019, focussing on the energetics of solar flares using the NuSTAR astrophysics telescope. After completing his PhD, he joined Stanford University as part of the Solar Dynamics Observatory team and served as faculty at the NASA Frontier Development Lab.
In 2021, Paul joined a startup specialising in spatial computing for asset management. Working cross-functionally across engineering, operations, and product management, he developed 2D/3D machine learning approaches to tackle automation challenges. In 2023, he returned to academia, joining DIAS as part of the Active Region Classification and Flare Forecasting (ARCAFF) project.
ORCID: 0000-0001-9021-611X
Funding: European Union’s HORIZON-CL4-2022-SPACE-01 call (Project ID 101082164)
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Last Updated: 26th April 2023 by Sophie Murray
Dr Paul Wright
Name: Paul Wright
Title: Postdoctoral Research Fellow
E-Mail: pjwright@cp.dias.ie
Address: School of Cosmic Physics, DIAS Dunsink Observatory, Dublin Institute for Advanced Studies, Dublin 15, Ireland.
Biographical Sketch:
Dr Paul Wright is a Postdoctoral Researcher at DIAS, using his expertise in solar physics and machine learning to advance our understanding of solar phenomena. Paul received his PhD in Solar Physics from the University of Glasgow in 2019, focussing on the energetics of solar flares using the NuSTAR astrophysics telescope. After completing his PhD, he joined Stanford University as part of the Solar Dynamics Observatory team and served as faculty at the NASA Frontier Development Lab.
In 2021, Paul joined a startup specialising in spatial computing for asset management. Working cross-functionally across engineering, operations, and product management, he developed 2D/3D machine learning approaches to tackle automation challenges. In 2023, he returned to academia, joining DIAS as part of the Active Region Classification and Flare Forecasting (ARCAFF) project.
ORCID: 0000-0001-9021-611X
Funding: European Union’s HORIZON-CL4-2022-SPACE-01 call (Project ID 101082164)
Category: Astronomy and Astrophysics, Staff
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