Jonathan Sauder

I'm a PhD student at EPFL in Lausanne, Switzerland, working at the intersection of 3D computer vision, machine learning, and coral reefs.

My goal is to use recent breakthroughs in AI to create the next generation of tools to monitor the ocean's previous ecosystems at unprecedented scale.

I am supervised by Devis Tuia leading the Environmental Computational Science and Earth Observation Laboratory, and Anders Meibom, who leads the Laboratory for Biological Geochemistry which hosts the Transnational Red Sea Center. Previously I obtained my master's degree in computer science at the TU Berlin, where I worked on research in machine learning, signal processing, and compressed sensing.

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Research

Undo the degrading effects of the water column and noise patterns from sunlight on water surface by using self-supervised monocular SLAM to devise effective learning objectives.

Self-supervised deep SLAM is combined with semantic segmentation on a new coral reef video dataset, creating a method for automatically analyzing video transects of reefs at unprecedented speed and cost-efficiency.

Combining unrolled compressed sensing techniques with Gumbel-top-K allows learning compressed sensing matrices that follow imposed structure by real-world applications.

A tiny LSTM component in unrolled compressed sensing for sparse signal reconstruction can significantly push the phase transition, with insights on how the LSTM chooses the optimal reconstruction thresholds and steps.

One of the first approaches to do self-supervised learning directly on point cloud data, learning to undo masking and reshuffling.

The Transnational Red Sea Center

This website uses Jon Barron's temaple.