Ivan Zvonkov

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Developing machine learning systems for remote sensing data and agriculture.

Full Bio

I am a Machine Learning Engineer at NASA Harvest where I work on scaling up machine learning research relating to agriculture and food security. I completed my master's degree in Computer Science at the University of Maryland. My thesis was titled "Usable Machine Learning for Remote Sensing Data". Before that, I worked at a fintech start-up developing machine learning and data science solutions for automating trade finance document processing. I completed a BEng in Software Engineering at the University of Western Ontario.

Professional Focus

Selected Publications

Tseng, G., Cartuyvels, R., Zvonkov, I., Purohit, M., Rolnick, D., and Kerner, H. (2023). Lightweight, Pre-trained Transformers for Remote Sensing Timeseries.
NeurIPS Climate Change AI Workshop.
Paper   Code

Zvonkov, I., Tseng, G., Nakalembe, C., and Kerner, H. (2023). OpenMapFlow: A Library for Rapid Map Creation with Machine Learning and Remote Sensing Data.
AAAI Conference on Artificial Intelligence.
Paper   Code   PyPI   Poster   Video

Tseng, G., Zvonkov, I., Nakalembe, C., Kerner, H. (2021). CropHarvest: a global satellite dataset for crop type classification.
NeurIPS Datasets and Benchmarks.
Paper   Code   PyPI

Outside