I am a Research Scientist at Adobe Research. My research interests are in computer vision and deep learning, focusing on self-supervised learning methods for images and videos. Previously, I was a PhD student in the Computer Vision Group at the University of Bern, supervised by Paolo Favaro. I received my BSc degree in Computer Science in 2015 and my MSc degree in Computer Science in 2017, both at the University of Bern.


  • December, 2021: A paper on video provenance won the best paper award at CVMP 2021

  • August, 2021: A paper on time-equivariant contrastive video representation learning got accepted to ICCV2021 (oral)

  • June, 2021: I succesfully defended my PhD

  • May, 2021: I joined Adobe Research as a Research Scientist

  • November, 2020: I will be joining Adobe Research as a Deep Learning Research Intern at the beginning of 2021

  • September, 2020: A paper on self-supervised multi-view synchronization learning for 3D human pose estimation got accepted to ACCV2020 (oral)

  • July, 2020: Our paper on self-supervised video representation learning by learning to tell motions appart got accepted to ECCV2020

  • March, 2020: A paper on self-supervised feature learning by recognizing transformations in global image statistics got accepted to CVPR2020 (oral)

  • March, 2020: Our work on extreme face superresolution using audio was accepted to CVPR2020 (oral)

  • March, 2019: A paper on stabilzing generative adversarial training with noise was accepted to CVPR2019

  • July, 2018: A paper on improving generalization and robustness to label noise via bilevel optimization was accepted to ECCV2018

  • April, 2018: A paper on self-supervised feature learning by spotting artifacts was accepted to CVPR2018 (spotlight)