Benjamin Kellenberger

Hello, world! I am researcher with Devis Tuia at the ECEO lab of EPFL, Sion, Switzerland. We work in the fields of Remote Sensing, Computer Vision, and Machine Learning. My focus is primarily on animal conservation from above—using aerial imagery from airplanes, drones, etc. and machine-based tools to efficiently identify, count, and with that protect endangered animal species.

What I do

I am interested in developing and providing solutions for nature and wildlife conservation, particularly using machine learning, computer vision in conjunction with aerial or camera trap imagery. One of my major research directives to this end is the automated and interactive localisation of mammals (elephants, rhino, etc.) in aerial images. You can hover over the image to the right to see one basic example product of what machine learning models can deliver.

Wait, what's so hard about this?

Predicting bounding boxes (i.e., object detection) has long been studied in computer vision, sure. However, aerial imagery poses a completely different set of problems. If you believe this to be simple, I would like to encourage you to get a stopwatch, open up this aerial image and measure the time it takes you to find the mammals. Then, think about how hard it is—even for a computer—to do that in hundreds of thousands of such images with a high recall and low error rate...

Why even bother?

Locating animals in aerial imagery serves many purposes, such as:

How does this work?

As is widespread these days, much of my research uses computer vision and machine learning (including, but not limited to, deep learning) to identify and localise animals. See the publications page if you want to know more.
However, simply developing models and publishing them in papers will not automatically change things for the better. Instead, my work is fuelled by two critical stances:

You may want to check out my latest software projects and publications.

Other things I do

My work is not only limited to animal detection, but spans more general vision, remote sensing and GIS topics as well. In detail, I also work on domain adaptation, weakly- and self-supervised learning, land cover and land use mapping, and more.
Besides that, I am also involved in teaching (BSc and MSc courses in GIS and machine learning for spatial data), and I administer and maintain our research group's computing infrastructure.


April 27, 2021

New paper is out: 21 000 birds in 4.5 h: efficient large‐scale seabird detection with machine learning! In this work we tackled the problem of detecting and counting high-density bird colonies off West Africa. Using deep learning-based models and prior knowledge, we were able to accurately detect 21 000 birds in drone imagery, using only 200 annotations per species and a total of 4.5 hours, from unannotated orthomosaic to prediction.

October 28, 2020

Our new paper about AIDE, the machine learning-assisted web annotation interface, is out! It has been published in the British Ecological Society's journal Methods in Ecology and Evolution, and is openly accessible here:
Link to paper
A bit of social media presence about the work: TwitterYouTube (teaser video)YouTube (extended video)

September 30, 2020

I have moved labs! From October 1 on, I will officially be an employee of the newly inaugurated Environmental Computational Science and Earth Observation Laboratory (ECEO) at EPFL in Sion, Switzerland! My duties will include all I did in Wageningen (including wildlife detection) and much more. I invite you to visit the web page (still work in progress) of our brand new lab (still in growth).

About me

I am originally from Zurich, Switzerland and also did my BSc and MSc there (University of Zurich). I completed my PhD at Wageningen University, Netherlands, with distinction "cum laude" (PhD thesis). A recording of my PhD defence from April 6, 2020, can be found here for your amusement. I have also worked in the U.S. at Microsoft in summer 2019.

Here's a brief summary of my educational activities:

October 2020 - Postdoctoral position at ECEO, École Polytechnique Fédérale de Lausanne, campus Sion, Switzerland.
April 7, 2020 - September 2020 Postdoctoral position at GRS, WUR
May - August 2019 Research Intern at Microsoft in the context of the AI for Earth initiative. Development of the AIde platform.
Aug 2017 - April 6, 2020 PhD candidate (cont'd) at the Laboratory of Geo-Information Science and Remote Sensing (GRS), Wageningen University (WUR), the Netherlands.
Feb 2016 - Jul 2017 PhD candidate at the Remote Sensing Laboratories, University of Zurich.
2015 - 2016 Intern at the Institute of Cartography and Geoinformation, ETH Zurich. Development of the GeoVITe geodata download portal.
2014 - 2015 Intern at the Federal Office of Topography swisstopo. Development of the Swiss Map Mobile data backbone.
2009 - 2014 BSc and MSc in Geography (Remote Sensing and GIS) and Computer Science at University of Zurich, Switzerland.

Feel free to contact me for a full CV.

People I collaborate with

Just a few of the amazing people I have or had the honour to work with: