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Lauren E. Gillespie
Assistant Professor
Geospatial Data Sciences
Conservation + Restoration
Websites
About
Coming from a background in both computer science and biology, Dr. Gillespie's interdisciplinary research develops new AI-integrated approaches for monitoring ecosystems at scale. Her work develops foundation models, AI models that can rapidly make sense of large-scale but noisy data with little guidance, and aims to uncover the effects of rapid environmental change on species to improve our ecological forecasting of the natural world. By leveraging diverse and widely available data from sources including remote sensing and citizen + community science, her research aims to create models of biodiversity that are accurate and useful for conservation decision-makers around the world.
Publications
Elena Sierra*, Lauren E. Gillespie*, Salim Soltani, Moises Exposito-Alonso, Teja Kattenborn. DivShift: Exploring Domain-Specific Distribution Shift in Large-Scale, Volunteer-Collected Biodiversity Datasets. Proceedings of the 39th AAAI Conference on Artificial Intelligence, AI for Social Impact Track, April 2025. (* denotes first authors)
Andy Huynh*, Lauren E. Gillespie*, Jael Lopez-Saucedo, Claire Tang, Rohan Sikand, Moises Exposito-Alonso. Contrastive ground-level image and remote sensing pre-training improves representation learning for natural world imagery. Proceedings of the European Conference on Computer Vision, October 2024. (* denotes first authors)
Lauren E. Gillespie, Megan Ruffley, Moises Exposito-Alonso. Deep learning models map rapid plant species changes from citizen science and remote sensing data. Proceedings of the National Academy of Sciences, September 2024.
Research
- Building accurate and open-source remote sensing foundation models of the natural world
- Understanding and forecasting rapid environmental change across ecosystems
- Developing scalable citizen science and field-based approaches for environmental monitoring
Accolades
- Best Paper Award, 39th AAAI Conference on Artificial Intelligence, AI for Social Impact Track, 2025.
- US Fulbright Program Student Research Travel Award, 2024.
- TomKat Fellowship for Translational Research, 2021.
- National Science Foundation Graduate Research Fellowship, 2019
Education
- PhD, Stanford University (Computer Science)
- BS, Southwestern University (Computer Science, Chemistry)
Affiliations
2025-2026 Academic Year: Massachusetts Institute of Technology (METEOR Postdoctoral Associate)