Oleksandr Kotlyar
Befattning: Databasansvarig Organisation: Institutionen för naturvetenskap och teknikE-post: oleksandr.kotlyar@oru.se
Telefon: 019 303730, 019 302117
Rum: T2219, B2308
Forskningsämne
Forskningsmiljöer
Forskningsprojekt
Pågående projekt
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Publikationer
Artiklar i tidskrifter |
Konferensbidrag |
Artiklar i tidskrifter
- Alijagic, A. , Kotlyar, O. , Larsson, M. , Salihovic, S. , Hedbrant, A. , Eriksson, U. , Karlsson, P. , Persson, A. & et al. (2024). Immunotoxic, genotoxic, and endocrine disrupting impacts of polyamide microplastic particles and chemicals. Environment International, 183.
- Alijagic, A. , Scherbak, N. , Kotlyar, O. , Karlsson, P. , Wang, X. , Odnevall, I. , Benada, O. , Amiryousefi, A. & et al. (2023). A Novel Nanosafety Approach Using Cell Painting, Metabolomics, and Lipidomics Captures the Cellular and Molecular Phenotypes Induced by the Unintentionally Formed Metal-Based (Nano)Particles. Cells, 12 (2).
- Kotlyar, O. , Kamalian-Kopae, M. , Pankratova, M. , Vasylchenkova, A. , Prilepsky, J. & Turitsyn, S. (2021). Convolutional long short-term memory neural network equalizer for nonlinear Fourier transform-based optical transmission systems. Optics Express, 29 (7), 11254-11267.
- Kotlyar, O. , Pankratova, M. , Kamalian-Kopae, M. , Vasylchenkova, A. , Prilepsky, J. & Turitsyn, S. (2020). Combining nonlinear Fourier transform and neural network-based processing in optical communications. Optics Letters, 45 (13), 3462-3465.
Konferensbidrag
- Alijagic, A. , Scherbak, N. , Kotlyar, O. , Karlsson, P. , Persson, A. , Hedbrant, A. , Norinder, U. , Larsson, M. & et al. (2022). Cell Painting unveils cell response signatures to (nano)particles formed in additive manufacturing. I: Toxicology Letters. Konferensbidrag vid XVIth International Congress of Toxicology (ICT 2022) - UNITING IN TOXICOLOGY, Maastricht, The Netherlands, September 18-21, 2022. (ss. S226-S227). Elsevier.
- Winkler, N. P. , Kotlyar, O. , Schaffernicht, E. , Fan, H. , Matsukura, H. , Ishida, H. , Neumann, P. P. & Lilienthal, A. (2022). Learning From the Past: Sequential Deep Learning for Gas Distribution Mapping. I: Danilo Tardioli; Vicente Matellán; Guillermo Heredia; Manuel F. Silva; Lino Marques, ROBOT2022 Fifth Iberian Robotics Conference: Advances in Robotics, Volume 2. Konferensbidrag vid ROBOT2022: Fifth Iberian Robotics Conference, Zaragoza, Spain, November 23-25, 2022. (ss. 178-188). Springer.