Jonathan Sauder

I'm a postdoctoral fellow at MIT CSAIL in Sara Beery's lab, where I work at the intersection of AI and ecology. My fellowship is supported by the Swiss National Science Foundation.

During my PhD at EPFL at the intersection of machine learning and 3D computer vision, I created tools to monitor coral reefs at unprecedented scale. My PhD was embedded in the Transnational Red Sea Center, where I was co-supervised by Devis Tuia and Anders Meibom.

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Research

The first fully AI-based transnational surveying endeavour, corroborating the real-world consistency of DeepReefMap and its robustness against environmental conditions.

The first large-scale dense semantic segmentation dataset in coral reefs.

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.