Photo of Pavlo Melnyk

Pavlo Melnyk

PhD student

Passionate about AI in general and Geometric Deep Learning in particular: debunking the magic behind artificial neural networks by viewing and designing them from a geometry perspective.

I am an academic PhD student at Computer Vision Laboratory.

Research Activities

My PhD project, “How to Inject Geometry into Deep Learning - Theoretical Foundation and New Computational Methods,” is funded by Wallenberg AI, Autonomous Systems and Software Program (WASP).

I am part of the Geometric Deep Learning Cluster within WASP.

Teaching

I am a teacher assistant and a project supervisor in several courses such as ”TSBB06 Multi-dimensional signal analysis”, ”TSBB14 Signal- and image-processing”, and ”TSBB15 Computer vision”.

I also supervise master theses.

Publications

  • Pavlo Melnyk, Michael Felsberg, Mårten Wadenbäck. "Steerable 3D Spherical Neurons", Proceedings of the 39th International Conference on Machine Learning, PMLR 162:15330-15339, 2022.

Quick Facts: Pavlo Melnyk

CV

  • 2019-: PhD in Electrical Engineering with specialization in Computer Vision, Linköping University, Linköping, Sweden.
  • 2016-2019: Master's in Computer Science and Technology, Hunan University (湖南大学), Changsha, Hunan province, China.
  • 2012-2016: Bachelor's in Information Security Systems, Donetsk National Technical University, Pokrovsk, Ukraine.

Languages

  • Swedish (certified, C1)
  • Chinese (certified, HSK5 (2019's version))
  • English
  • Ukrainian (native/bilingual)

Publications

2022

Pavlo Melnyk, Michael Felsberg, Mårten Wadenbäck (2022) Steerable 3D Spherical Neurons Proceedings of the 39th International Conference on Machine Learning, p. 15330-15339

2021

Pavlo Melnyk, Michael Felsberg, Mårten Wadenbäck (2021) Embed Me If You Can: A Geometric Perceptron Proceedings 2021 IEEE/CVF International Conference on Computer Vision ICCV 2021, p. 1256-1264 Continue to DOI

Coworkers CVL

Organisation