Current research interests

Biomedical image analysis and visualization

My activities in the field of Biomedical image analysis, featuring state-of-the-art results on many datasets including membrane segmentation in EM images, mitosis detection in histopathology images, retinal blood vessel segementation, segmentation of embryos and zygotes in hoffmann modulation contrast microscopy images and stacks.

I also developed a cool (and useful) visualization technique for visual markers on Z-stacks.


Efficient testing of Deep Neural Networks

Convolutional Deep Neural Networks are surprisingly good for image segmentation and object detection tasks; but applying these networks to every patch of a large image is computationally expensive: here's our fast scanning algorithm which speeds this up by several orders of magnitude.

Distributed Algorithms for the Smart Grid

I have been actively involved in the swiss S2G project and I am currently working on the GridSense technology.

Supplementary material for our paper “Restricted Neighborhood Communication Improves Decentralized Demand-Side Load Management”, Transactions on Smart Grid, 2104.

Past research interests