Postdoc
I am a postdoctoral researcher in the division for Computer Vision and Learning Systems (CVL). My research focuses on geometry, equivariant modelling, and applications of AI for Science. Here at CVL, I have earned my PhD in Electrical Engineering with a specialisation in Computer Vision, where I worked on Geometric Deep Learning under the supervision of Michael Felsberg and with funding from .
For more details about my work, please visit .
Pavlo Melnyk, Anmar Karmush, M氓rten Wadenb盲ck, Ania Beatriz Rodr铆guez-Barrera, Johanna Rosen, Michael Felsberg, Jonas Bj枚rk, Benchmark Dataset for Catalysis on 2D MXenes (2026)
Pavlo Melnyk, Cuong Le, Urs Waldmann, Per-Erik Forss茅n, Bastian Wandt, On the Role of Rotation Equivariance in Monocular 2D-to-3D Human Pose Lifting (2026)
Pavlo Melnyk, Michael Felsberg, Kostas Daniilidis, , GEOMETRY-GROUNDED REPRESENTATION LEARNING AND GENERATIVE MODELING WORKSHOP, GRAM AT ICLR 2026, Proceedings of Machine Learning Research, pp. 416-432, JMLR-JOURNAL MACHINE LEARNING RESEARCH (2026)
Akshay Chandrasekhar, Pavlo Melnyk, Loss-Invariant Projections as Passive Probes of Learned Representations (2026)
Cuong Le, Pavlo Melnyk, Bastian Wandt, M氓rten Wadenb盲ck, , Transactions on Machine Learning Research (2026)
