Esther Rolf

Esther Rolf is an Assistant Professor of Computer Science at the University of Colorado, Boulder. Her research focuses on statistical and geospatial machine learning, emphasizing usability, data efficiency, and fairness. She explores environmental monitoring via machine learning and the impact of data representation on algorithmic fairness. Prior to CU Boulder, she was a postdoctoral fellow at Harvard’s Data Science Initiative. She earned her PhD in Computer Science from UC Berkeley, advised by Benjamin Recht and Michael I. Jordan, supported by NSF, Google, and UC Berkeley fellowships. Her work has garnered best paper awards and international recognition, including the SDG Digital Gamechangers Award. She currently teaches courses on geospatial ML and machine learning, and leads the MOSAIKS project for accessible satellite-based ML systems. She actively recruits PhD students and postdocs focused on interdisciplinary, applied ML research.

Education:

• PhD in Computer Science, UC Berkeley (2022)
• Postdoctoral Fellowship, Harvard (2022)

Research Interests: Esther’s work bridges ML methodology and real-world applications, particularly in environmental and social domains. Key areas include:

• Geospatial ML for environmental monitoring (e.g., satellite imagery analysis)
• Ethical AI: fairness, representation, and bias mitigation
• Algorithmic approaches for data-efficient, scalable systems

Recent Trends in Publications: Her recent work emphasizes geospatial challenges, such as satellite data modality, global location embeddings, and policy impacts of ML-driven environmental models. She also investigates data representation’s role in model fairness across domains like poverty mapping and resource extraction tracking.

Awards:

• SDG Digital Gamechangers Award (2023)
• Best Paper at ICML (2018)
• Best Paper at NeurIPS AI for Social Good Workshop (2019)

Lab & Collaboration: Her lab at CU Boulder fosters interdisciplinary research, emphasizing collaborative, communication-driven projects. Current initiatives include the MOSAIKS project and the ML & Environment Postdoctoral Fellowship program. She teaches advanced courses on geospatial ML and machine learning theory.