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Andrew J. Humphrey


Biographic Notes
Andrew Humphrey obtained his bachelor and PhD degrees from the University of Hertfordshire, and has worked at various institutes in Europe, the Americas and Asia, before moving to Porto with a Marie Curie Fellowship. Andrew's research interests include the formation/evolution of galaxies as probed by various phenomena, particularly Lyman-alpha nebulae, powerful active galaxies, and dusty star-forming galaxies at high-redshifts.

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Lastest publications at IA (or with IA Researchers)W. Wang, D. Wylezalek, J. Vernet, C. de Breuck, B. Gullberg, A. M. Swinbank, M. Villar Martín, M. D. Lehnert, G. Drouart, F. Arrigoni-Battaia et al. (including: A. Humphrey, P. Lagos), 2023,
3D tomography of the giant Lyα nebulae of z≈3–5 radio-loud AGN,
Astronomy & Astrophysics, 680, 44
>> Abstract
R. Carvajal, I. Matute, J. Afonso, R. P. Norris, K. J. Luken, P. Sánchez-Sáez, P. A. C. Cunha, A. Humphrey, H. Messias, S. Amarantidis et al. (including: H. Miranda, A. Paulino-Afonso, C. Pappalardo), 2023,
Selection of powerful radio galaxies with machine learning,
Astronomy & Astrophysics, 679, 24
>> Abstract
Euclid Collaboration, L. Bisigello, C. J. Conselice, M. Baes, M. Bolzonella, M. Brescia, S. Cavuoti, O. Cucciati, A. Humphrey, L. K. Hunt et al. (including: E. Branchini, M. Cropper, A. N. Taylor, C. S. Carvalho), 2023,
Euclid preparation – XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images,
Monthly Notices of the Royal Astronomical Society, 520, 19
>> Abstract
L. Binette, Y. Krongold, S. A. R. Haro-Corzo, A. Humphrey, S. G. Morais, 2023,
Optimized Spectral Energy Distribution for Seyfert Galaxies,
Revista Mexicana de Astronomía y Astrofísica, 53, 9
>> Abstract
Euclid Collaboration, A. Humphrey, L. Bisigello, P. A. C. Cunha, M. Bolzonella, S. Fotopoulou, K. Caputi, C. Tortora, G. Zamorani, P. Papaderos et al. (including: J. Brinchmann, A. C. da Silva, I. Tereno, C. S. Carvalho), 2023,
Euclid preparation
XXII. Selection of quiescent galaxies from mock photometry using machine learning
Astronomy & Astrophysics, 671, 36
>> Abstract
A. Humphrey, P. A. C. Cunha, A. Paulino-Afonso, S. Amarantidis, R. Carvajal, J. M. Gomes, I. Matute, P. Papaderos, 2023,
Improving machine learning-derived photometric redshifts and physical property estimates using unlabelled observations,
Monthly Notices of the Royal Astronomical Society, 520, 305 - 313
>> Abstract

Andrew J. Humphrey
Faculdade de Ciências da Universidade de Lisboa Universidade do Porto Faculdade de Ciências e Tecnologia da Universidade de Coimbra
Fundação para a Ciência e a Tecnologia COMPETE 2020 PORTUGAL 2020 União Europeia