Rate My Professor Esther Rolf

Esther Rolf is an Assistant Professor in the Computer Science Department at the University of Colorado Boulder, a position she has held since 2024. She earned her Ph.D. in Computer Science from the University of California, Berkeley in 2022, where she was advised by Ben Recht and Michael I. Jordan. Her doctoral studies were supported by the NSF Graduate Research Fellowship, Google Research Fellowship, and UC Berkeley Stonebreaker Fellowship. Prior to joining CU Boulder, Rolf served as a Postdoctoral Fellow with the Harvard Data Science Initiative and the Center for Research on Computation and Society from 2022 to 2024. She completed her B.S.E. in Computer Science and Engineering at Princeton University in 2016, graduating summa cum laude. Additional experience includes research internships at Google Research (November 2021–January 2022) and Microsoft Research (May–July 2021). Currently, she is the AI/ML Lead for the Environmental Data Science Innovation and Impact Lab (ESIIL) since 2025 and Scientific Director for the Togo Data Lab since 2024.

Rolf's research blends methodological and applied techniques in statistical and geospatial machine learning, with an emphasis on usability, data-efficiency, and fairness. Her work addresses reliable environmental monitoring using machine learning, satellite imagery analysis, data representation's influence on fair systems, and geospatial challenges like spatial error structures. Key publications include 'A generalizable and accessible approach to machine learning with global satellite imagery' in Nature Communications (2021, Rolf et al.); 'Representation matters: Assessing the importance of subgroup allocations in training data' at ICML (2021, Rolf et al.); 'Position: Mission critical–Satellite data is a distinct modality in machine learning' at ICML (2024, Spotlight, Rolf et al.); 'SatCLIP: Global, general-purpose location embeddings with satellite imagery' at AAAI (2025, Klemmer et al.); and 'Mapping on a Budget: Optimizing Spatial Data Collection for ML' at AAAI (2025, Betti et al.). She has received the SDG Digital Gamechangers Award (2023) from the United Nations Development Programme and International Telecommunication Union, best paper awards at ICML (2018), NeurIPS Workshop on AI for Social Good (2019), and ICLR Workshop on Machine Learning for Remote Sensing (2025, best student paper). Rolf teaches CSCI 5622: Machine Learning and CSCI 7000: Geospatial and Statistical Machine Learning at CU Boulder, and contributes to service through peer reviewing for NeurIPS, ICML, ICLR, and workshop organization including lead organizer for ICLR ML for Remote Sensing workshops (2025, 2026). She delivered a keynote at the NeurIPS Tackling Climate Change with Machine Learning workshop (2024).