Evaluation Challenges for Geospatial ML
Esther Rolf. Workshop on Machine Learning for Remote Sensing at ICLR, 2023.
In my research I develop and analyze of machine learning algorithms to address pressing social and environmental problems. Sometimes this entails developing or analyzing new statistical ML techniques, sometimes this entails carefully applying, adapting, and evaluating ML methods in a specific context of use; most often it entails a blend of the two. Some specific project areas and application contexts:
For a full list of papers please see my google scholar page.
New! "Geographic location encoding with spherical harmonics and sinusoidal representation networks" (w/ Marc Rußwurm, Konstantin Klemmer, Robin Zbinden, and Devis Tuia) will appear at ICLR 2024.
"Fairness and representation in satellite-based poverty maps: Evidence of urban-rural disparities and their impacts on downstream policy" (w/ Emily Aiken and Joshua Blumenstock) appeared at IJCAI 2023.Esther Rolf. Workshop on Machine Learning for Remote Sensing at ICLR, 2023.
Esther Rolf*, Nikolay Malkin*, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic. UAI, 2022.
Esther Rolf, Theodora Worledge, Benjamin Recht, Michael I. Jordan. ICML, 2021.
Esther Rolf*, Jonathan Proctor*, Tamma Carleton*, Ian Bolliger*, Vaishaal Shankar*, Miyabi Ishihara, Benjamin Recht, Solomon Hsiang. Nature Communications, 2021.
I am looking for postdocs and PhD Students to join my lab at CU, starting as soon as the fall of 2024, who are interested in
and who want to work in and foster a lab environment which is
Interested in a PhD? Apply to CU Boulder's PhD program in computer science and list me as a potential advisor. Applications open in the fall for positions in fall of the following year.
Interested in a postdoc? Send me an email at esther.rolf@colorado.edu describing your background, research interests, and fit with my lab.
Other? Email me at esther.rolf@colorado.edu. Please note that I will not be able to respond to all emails.