Agnieszka Pollo

Research focus: 

large scale structure of the Universe, galaxy evolution, astrostatistics

ML expertise / Scientific Expertise: 

Various approaches; supervised/unsupervised

Relevant publications: 
  1. Solarz, A., Pollo, A., Takeuchi, T. T. et al., Star-galaxy separation in the AKARI NEP deep field, Astronomy & Astrophysics, Volume 541, id.A50, 8 pp, 2012,
  2. Małek, K., Solarz, A., Pollo, A. et al., “The VIMOS Public Extragalactic Redshift Survey (VIPERS). A support vector machine classification of galaxies, stars, and AGNs”, Astronomy & Astrophysics, Volume 557, id.A16, 16 pp., 2013,

  3. Kurcz, A.; Bilicki, M.; Solarz, A.; Krupa, M.; Pollo, A.; Małek, K., Towards automatic classification of all WISE sources, Astronomy & Astrophysics, Volume 592, id.A25, 18 pp., 2016,

  4. Krakowski, T.; Małek, K.; Bilicki, M.; Pollo, A.; Kurcz, A.; Krupa, M., “Machine-learning identification of galaxies in the WISE × SuperCOSMOS all-sky catalogue”,  Astronomy & Astrophysics, Volume 596, id.A39, 11 pp., 2016,

  5. Solarz, A.; Bilicki, M.; Gromadzki, M.; Pollo, A.; Durkalec, A.; Wypych, M., Automated novelty detection in the WISE survey with one-class support vector machines, Astronomy & Astrophysics, Volume 606, id.A39, 13 pp., 2017,

  6. Siudek, M.; Małek, K.; Pollo, A.; Krakowski, T.; Iovino, A. et al., “The VIMOS Public Extragalactic Redshift Survey (VIPERS). The complexity of galaxy populations at 0.4 < z < 1.3 revealed with unsupervised machine-learning algorithms”, Astronomy & Astrophysics, Volume 617, id.A70, 25 pp., 2018,

  7. Nakoneczny, S.; Bilicki, M.; Solarz, A.; Pollo, A.; Maddox, N.; Spiniello, C.; Brescia, M.; Napolitano, N. R., Catalog of quasars from the Kilo-Degree Survey Data Release 3, Astronomy & Astrophysics, Volume 624, id.A13, 15 pp., 2019,

  8. Poliszczuk, A.; Solarz, A.; Pollo, A.; Bilicki, M. et al., Active galactic nucleus selection in the AKARI NEP-Deep field with the fuzzy support vector machine algorithm, Publications of the Astronomical Society of Japan, Volume 71, Issue 3, id.65,

  9. Turner, S.; Siudek, M.; Salim, S.; Baldry, I. K.; Pollo, A.; Longmore, S. N.; Małek, K. et al.; Synergies between low- and intermediate-redshift galaxy populations revealed with unsupervised machine learning, Monthly Notices of the Royal Astronomical Society, 2021 in press,

  10. Nakoneczny, S. J.; Bilicki, M.; Pollo, A.; Asgari, M., et al., Photometric selection and redshifts for quasars in the Kilo-Degree Survey Data Release 4, Astronomy & Astrophysics, , in press, 2021,


whatever enjoyable is good