Machine learning at NASA Harvest,
Incoming PhD Student at Arizona State University
Interests: ML systems, use-inspired research, nature
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 am also an incoming PhD student at Arizona State University
where I will be working with Dr. Hannah Kerner on machine learning for remote sensing data.
While working at NASA Harvest, 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 joining NASA Harvest, 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 where I developed an award-winning forest fire forecasting project for my capstone.
Tseng, G.*, Zvonkov, I.*, Purohit, M., Rolnick, D., and Kerner, H (2023).
Lightweight, Pre-trained Transformers for Remote Sensing Timeseries.
Zvonkov, I., Tseng, G., Nakalembe, C., and Kerner, H. (2023).
OpenMapFlow: A Library for Rapid Map Creation with Machine Learning and Remote Sensing Data.
To appear in Proceedings of the 2023 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.
Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks
Paper Code PyPI
May 2023 - Obtained Master's Degree
Successfully defended M.S. Thesis titled "Usable Machine Learning for Remote Sensing Data" and graduated from University of Maryland.
May 2023 - ICLR (International Conference on Learning Representations)
We hosted a successful 1st Workshop on Machine Learning for Remote Sensing at ICLR 2023 and Tutorial on the same at CMU Africa Website
Feb 2023 - AAAI (Association for the Advancement of Artificial Intelligence)
Presented OpenMapFlow paper in the AI for Social Impact Track.
Feb 2023 - Maui Food Security Project
Kicked off project for combatting food security in Maui County using AI Article
Dec 2022 - AGU (American Geophysical Union) Fall Meeting
Presented OpenMapFlow library in: Leveraging Open Artificial Intelligence and Unsupervised Learning Techniques for Advancements in Earth Science.
Sept 2022 - SatSummit
Participated in panel on Localizing AI.
Aug 2022 - NASA SERVIR Eastern Africa Hub Training
Led multi-day session on Scalable Cropland Mapping.
Jun 2022 - CVPR (Conference on Computer Vision and Pattern Recognition)
Co-organized tutorial with Dr. Hannah Kerner and Dr. Catherine Nakalembe titled:
Machine Learning for Remote Sensing: Agriculture and Food Security.
May 2022 - Living Planet Symposium
Presented our work on the CropHarvest dataset and Helmets Labeling Crops.
Apr 2022 - Makere AI Lab and Kenya Space Agency visits
Demoed cropland mapping at scale. Video