About

Hi, I’m Pratyush Tripathy, a PhD candidate in Geography at UC Santa Barbara. I work on environmental and development problems, often in settings where the data needed to answer the question don’t exist yet, so much of my work is building that data from satellite imagery and AI models.

My doctoral research investigates the impact of flooding on people’s livelihoods, from mapping flood extent using satellite imagery, to who understands themselves to be at risk, to the consequences for agricultural productivity and economic development. I’m also interested in how far state-of-the-art models from computer science can be pushed to facilitate causal analysis that conventional data cannot support. Additionally, I am always curious about the hidden pitfalls of applying these AI models to geospatial data.

To learn more, please check my Research and Publications, or read about how I got here.

Recent Work

Tripathy, P., Upadhyay, S., Alegbeleye, O. M., Senkardesler, E., Pingali, D., Goddard, E., Thaker, J., Leiserowitz, A., & Marlon, J. R. (2026). National-scale mapping locates the mismatch between perceived and assessed flood risk in India. EarthArXiv. https://doi.org/10.31223/X5WZ38
Anaya, J. A., Montero, D., Tripathy, P., Schroeder, W., Hantson, S., Bastarrika, A., & Mahecha, M. D. (2026). Assessing fire-exposed vegetation in the Orinoco Basin using Sentinel-2 and deep learning. Sustainable Geosciences: People, Planet and Prosperity, 100031. https://doi.org/10.1016/j.susgeo.2026.100031
Agrawal, A. & Tripathy, P. (2026). Global Flood Mapper v2: Open-Access Flood Mapping and Exposure Assessment with Sentinel-1 SAR. https://doi.org/10.31223/X54482
Tripathy, P., Baylis, K., Wu, K., Watson, J., & Jiang, R. (2026). Zero-shot inference strategies for smallholder (< 0.1 ha) agriculture field delineation with the Segment Anything foundation model. Science of Remote Sensing, 100425. https://doi.org/10.1016/j.srs.2026.100425