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Oleksandr Kotlyar

Position: Database Manager School/office: School of Science and Technology

Email: b2xla3NhbmRyLmtvdGx5YXI7b3J1LnNl

Phone: +46 19 303730, +46 19 302117

Room: T2219, B2308

Oleksandr Kotlyar

About 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.

Publications

Articles in journals |  Conference papers |  Manuscripts | 

Articles in journals

Conference papers

  • Alijagic, A. , Södergren Seilitz, F. , Bredberg, A. , Hakonen, A. , Larsson, M. , Sjöberg, V. , Kotlyar, O. , Persson, A. & et al. (2024). Comprehensive chemical and toxicological screening of e-waste plastic chemicals. Paper presented at 58th Congress of the European Societies of Toxicology (EUROTOX 2024), Copenhagen, Denmark, September 8-11, 2024. (pp. S66-S66). Elsevier. [BibTeX]
  • Gupta, H. , Kotlyar, O. , Andreasson, H. & Lilienthal, A. J. (2024). Robust Object Detection in Challenging Weather Conditions. In:  2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Conference Proceedings. Paper presented at 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV 2024), Waikoloa, HI, USA, January 3-8, 2024. (pp. 7508-7517). IEEE. [BibTeX]
  • 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. In:  Toxicology Letters. Paper presented at XVIth International Congress of Toxicology (ICT 2022) - UNITING IN TOXICOLOGY, Maastricht, The Netherlands, September 18-21, 2022. (pp. S226-S227). Elsevier. [BibTeX]
  • 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. In: Danilo Tardioli; Vicente Matellán; Guillermo Heredia; Manuel F. Silva; Lino Marques,  ROBOT2022 Fifth Iberian Robotics Conference: Advances in Robotics, Volume 2. Paper presented at ROBOT2022: Fifth Iberian Robotics Conference, Zaragoza, Spain, November 23-25, 2022. (pp. 178-188). Springer. [BibTeX]

Manuscripts