Gabriel Tseng is a researcher at the Allen Institute for Artificial Intelligence (Ai2). He researches machine learning for remote sensing, focusing on self-supervised learning methods and applications in agriculture. He led the development of Presto, a self-supervised model which is now the backbone of WorldCereal’s global crop mapping effort. At Ai2 he works on OlmoEarth, a project aiming to make mapping at scale better and more accessible.
Gabi completed a PhD in computer science at McGill University / Mila under the supervision of Professor David Rolnick. During his PhD, he worked closely with NASA Harvest (NASA’s agricultural consortium), supervised by Professor Hannah Kerner.
Outside of machine learning and remote sensing, Gabi enjoys spending time outside by running and climbing in beautiful places.
