Ribli Dezső

Ribli Dezső

PhD student

Supervisor: István Csabai, (2020)

Department of Physics of Complex Systems

Room(s): Lágymányos Campus, Northern Building 5.103
Phone(s): +36-1-372-2896
Extension(s): +36-1-372-2500 / 6577
Mobile(s): n.a.
Homepage: n.a.


Research interests: machine learning in astronomy and astrophysics, computer vision for medical imaging

Awards: The Digital Mammography DREAM Challenge, a data science competition to detect breast cancers, 2nd place (2017)
National biology competition in Hungary for high school students (OKTV), 3rd place (2009)

Teaching: Data mining and machine learning (dsminingf17vm, FIZ/3/084), Introduction to computing (szamalapf18la)

Links to associated scientific database profiles:

Selected publications of recent years:

  1. Dezsö Ribli, Bálint Ármin Pataki, José Manuel Zorrilla Matilla, Daniel Hsu, Zoltán Haiman, István Csabai, Weak lensing cosmology with convolutional neural networks on noisy data, Monthly Notices of the Royal Astronomical Society, , stz2610, link
  2. Dezső Ribli, László Dobos, István Csabai, Galaxy shape measurement with convolutional neural networks, Monthly Notices of the Royal Astronomical Society, Volume 489, Issue 4, November 2019, Pages 4847–4859, link
  3. Ribli, D., Pataki, B.Á. and Csabai, I., 2019. An improved cosmological parameter inference scheme motivated by deep learning. Nature Astronomy, 3(1), p.93.
  4. Takeda, D.Y., Spisák, S., Seo, J.H., Bell, C., O’Connor, E., Korthauer, K., Ribli, D., Csabai, I., Solymosi, N., Szállási, Z. and Stillman, D.R., 2018. A somatically acquired enhancer of the androgen receptor is a noncoding driver in advanced prostate cancer. Cell, 174(2), pp.422-432.
  5. Turajlic, S., Xu, H., Litchfield, K., Rowan, A., Horswell, S., Chambers, T., O’Brien, T., Lopez, J.I., Watkins, T.B., Nicol, D. and Stares, M., 2018. Deterministic evolutionary trajectories influence primary tumor growth: TRACERx renal. Cell, 173(3), pp.595-610.
  6. Ribli, D., Horváth, A., Unger, Z., Pollner, P. and Csabai, I., 2018. Detecting and classifying lesions in mammograms with deep learning. Scientific reports, 8(1), p.4165.
  7. Pipek, O., Ribli, D., Molnár, J., Póti, Á., Krzystanek, M., Bodor, A., Tusnady, G.E., Szállási, Z., Csabai, I. and Szüts, D., 2017. Fast and accurate mutation detection in whole genome sequences of multiple isogenic samples with IsoMut. BMC bioinformatics, 18(1), p.73.
  8. Zámborszky, J., Szikriszt, B., Gervai, J.Z., Pipek, O., Póti, Á., Krzystanek, M., Ribli, D., Szalai-Gindl, J.M., Csabai, I., Szallasi, Z. and Swanton, C., 2017. Loss of BRCA1 or BRCA2 markedly increases the rate of base substitution mutagenesis and has distinct effects on genomic deletions. Oncogene, 36(6), p.746.
  9. Szikriszt, B., Póti, Á., Pipek, O., Krzystanek, M., Kanu, N., Molnár, J., Ribli, D., Szeltner, Z., Tusnády, G.E., Csabai, I. and Szallasi, Z., 2016. A comprehensive survey of the mutagenic impact of common cancer cytotoxics. Genome biology, 17(1), p.99.
  10. Petrovics, G., Li, H., Stümpel, T., Tan, S.H., Young, D., Katta, S., Li, Q., Ying, K., Klocke, B., Ravindranath, L. and Kohaar, I., 2015. A novel genomic alteration of LSAMP associates with aggressive prostate cancer in African American men. EBioMedicine, 2(12), pp.1957-1964.