I study Deep Neural Networks for Computer Vision, like CNNs and Vision Transformers, and how they learn to do their job. Topics of choice include learned equivariance, position information and the inductive bias of the self-attention operation. I’ve also dabbled in implicit neural convolutional operators a bit.
ICLR 2022 paper: FlexConv
CVPRW 2023 paper: Learned Equivariance
Organizer of VIPriors workshop (2020-ongoing)
paper with colleagues at TU Delft.
Co-authoredpaper with BSc students at TU Delft.
Co-authoredI was head TA and lecturer in the 2023 edition of CV by Deep Learning at TU Delft.
I am always willing to talk about collaboration or supervision. Please find my contact info at the top of the page.
Office
TU Delft, building 28, room 6.E.280
Van Mourik Broekmanweg 6
2628 XE Delft
The Netherlands