Oleksandr Kotlyar

I joined Mobile Robotics and Olfaction (MR&O) and Environmental Forensic (EnForce) Laboratories at Örebro University as Database manager in October 2020. Prior this I was Marie S.-Curie MULTIPLY Postdoctoral Research Fellow at Aston Institute of Photonic Technologies, Aston University, Birmingham, UK. Before I worked as a Research Fellow in Department of Theoretical Physics at B. Verkin Institute for Low Temperature Physics and Engineering, Kharkiv, Ukraine. Also, I was a visiting scholar at Pavol Jozef Šafárik University in Košice, Slovak Republic. My higher education was obtained at V.N. Karazin Kharkiv National University, (BSc and MSc in Physics) and B. Verkin Institute for Low Temperature Physics and Engineering (PhD in Theoretical Physics).

My current work is devoted to data analysis and machine learning image processing of materials achieved from “Cell Painting”, a high-content image-based cell profiling experiments. In general, my interest involves (but not limited to) the application of machine learning techniques to the various scientific and engineering tasks.

Contact

Dr. Oleksandr Kotlyar

AASS Research Centre
School of Science and Technology
Örebro University
70182 Örebro, Sweden
Room T2219, B2308
Phone +46 19 303 730
+46 19 302 117
oleksandr.kotlyar@oru.se

Publications

Journal Articles

[1]	A. Alijagic, O. Kotlyar, M. Larsson, S. Salihovic, A. Hedbrant, U. Eriksson, P. Karlsson, A. Persson, N. Scherbak, K. Färnlund, M. Engwall and E. Särndahl. Immunotoxic, genotoxic, and endocrine disrupting impacts of polyamide microplastic particles and chemicals. Environment International, 183, 2024 [ BibTeX \| DiVA ]
[2]	A. Alijagic, N. Scherbak, O. Kotlyar, P. Karlsson, X. Wang, I. Odnevall, O. Benada, A. Amiryousefi, L. Andersson, A. Persson, J. Felth, H. Andersson, M. Larsson, A. Hedbrant, S. Salihovic, T. Hyötyläinen, D. Repsilber, E. Särndahl and M. Engwall. 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), 2023 [ BibTeX \| DiVA ]
[3]	O. Kotlyar, M. Kamalian-Kopae, M. Pankratova, A. Vasylchenkova, J. Prilepsky and S. Turitsyn. Convolutional long short-term memory neural network equalizer for nonlinear Fourier transform-based optical transmission systems. Optics Express, 29(7):11254-11267, 2021 [ BibTeX \| DiVA \| PDF ]
[4]	O. Kotlyar, M. Pankratova, M. Kamalian-Kopae, A. Vasylchenkova, J. Prilepsky and S. Turitsyn. Combining nonlinear Fourier transform and neural network-based processing in optical communications. Optics Letters, 45(13):3462-3465, 2020 [ BibTeX \| DiVA \| PDF ]

Refereed Conference and Workshop Articles

[1]

N. P. Winkler, O. Kotlyar, E. Schaffernicht, H. Fan, H. Matsukura, H. Ishida, P. P. Neumann and A. Lilienthal. Learning From the Past : Sequential Deep Learning for Gas Distribution Mapping. In ROBOT2022 : Fifth Iberian Robotics Conference: Advances in Robotics, Volume 2, 590(590):178-188, 2022 [ BibTeX | DiVA ]

Find the complete BibTeX record here.