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.

• Perceiving real-world forest trails for autonomous navigation of micro aerial vehicles.
• Kinect-based People Detection and Tracking for small-footprint mobile robots (includes downloadable software).
• Interactive Augmented Reality for Understanding and Analyzing Multi-Robot Systems (ongoing work).
• Also see Gianni di Caro's webpage (which is written in comic sans, you have been warned) on the topic of swarm robotics.

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.

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.

• Analysis and re-animation of motion-blurred objects was my main research topic during my PhD. An interesting problem which involves elegant, novel theories, and provides counterintuitive results. There are also various practical applications.
• Speedlines: Drawing Motion without Understanding It, i.e. synthesizing comicbook-like speedlines on videos, with only low-level processing.
• 3D Reconstruction of Canal Surfaces from a single perspective image.
• Wakeup Scattering in Wireless Sensor Networks.