Benjamin Kellenberger
Postdoctoral Associate
Bio:
I am a data scientist with background in Earth observation, computer vision and machine learning. In my previous work at EPFL Switzerland I devised methods to automatically detect and count animals in very high-resolution aerial imagery using deep learning. My current research attempts to make sense not just of where species individuals are, but why; to this end I research on the intersection of data science and ecology to augment our understanding and capabilities of species distribution modeling at scale.
Area of Interest:
Species distribution modeling with remote sensing and machine (deep) learning, hybrid models