Gabriel Tseng
Hello! My name is Gabi. I am a PhD student at McGill / Mila, working under the supervision of Professor David Rolnick to investigate ways in which machine learning can help fight climate change. This includes working with Professor Hannah Kerner at NASA Harvest and with Ai2’s Earth System Team.
Land use is one of the most important environmental issues, and agriculture is the main driver of land use. My research seeks to better understand the Earth’s landcover using remote sensing data, with a focus on improving the machine learning algorithms used to make large scale agricultural landcover maps.
In addition to machine learning for remote sensing and agriculture, I have been lucky to contribute to:
- Technology for good, such as for sustainable and regenerative farming, or to increase energy access
- Interpretable machine learning using open source tools
I also love spending time outdoors, either by climbing or running in beautiful places.
In addition to the technical blog here, I also have a non technical blog, at oolongaloha.com
You can check out my CV here.
News
Galileo is accepted to ICML! We develop a new self-supervised learning algorithm tailored to remote sensing, and use it to train a model which achieves state-of-the-art results across a diversity of remote sensing tasks (ranging from image segmentation to pixel-timeseries classification). Check out the code and paper.
I’m at ICLR in Singapore, helping to organize the Machine Learning for Remote Sensing Workshop.
I presented Presto and Galileo to NUS’s Centre for Remote Imaging, Sensing and Processing (CRISP), hosted by Dr. Soo Chin Liew.