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Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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The Fingerprint is created by mining the titles and abstracts of the person's research outputs and projects/funding awards to create an index of weighted terms from discipline-specific thesauri.
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Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Conference: NSF workshop proposal on AI-Enabled Scientific Revolutions
2/1/23 → 1/31/24
Project: Research project
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Knowledge Guided Machine Learning: A Framework for Accelerating Scientific Discovery
9/1/19 → 8/31/23
Project: Research project
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BIGDATA: F: Advancing Deep Learning to Monitor Global Change
Kumar, V., Pardey, P. G., Senay, S. D., Steinbach, M. & Wilgenbusch, J.
11/1/18 → 10/31/23
Project: Research project
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Correction: Toward Large-Scale Mapping of Tree Crops with High-Resolution Satellite Imagery and Deep Learning Algorithms: A Case Study of Olive Orchards in Morocco (Remote Sens., (2021), 13, (1740), 10.3390/RS13091740)
Lin, C., Jin, Z., Mulla, D., Ghosh, R., Guan, K., Kumar, V. & Cai, Y., Jan 2023, In: Remote Sensing. 15, 1, 141.Research output: Contribution to journal › Comment/debate › peer-review
Open Access -
Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions
Zwart, J. A., Oliver, S. K., Watkins, W. D., Sadler, J. M., Appling, A. P., Corson-Dosch, H. R., Jia, X., Kumar, V. & Read, J. S., Apr 2023, In: Journal of the American Water Resources Association. 59, 2, p. 317-337 21 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Can machine learning accelerate process understanding and decision-relevant predictions of river water quality?
Varadharajan, C., Appling, A. P., Arora, B., Christianson, D. S., Hendrix, V. C., Kumar, V., Lima, A. R., Müller, J., Oliver, S., Ombadi, M., Perciano, T., Sadler, J. M., Weierbach, H., Willard, J. D., Xu, Z. & Zwart, J., Apr 2022, In: Hydrological Processes. 36, 4, e14565.Research output: Contribution to journal › Article › peer-review
Open Access8 Scopus citations -
Clustering augmented self-supervised learning: an application to land cover mapping
Ghosh, R., Jia, X., Yin, L., Lin, C., Jin, Z. & Kumar, V., Nov 1 2022, 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2022. Renz, M., Sarwat, M., Nascimento, M. A., Shekhar, S. & Xie, X. (eds.). Association for Computing Machinery, 3. (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Daily surface temperatures for 185,549 lakes in the conterminous United States estimated using deep learning (1980–2020)
Willard, J. D., Read, J. S., Topp, S., Hansen, G. J. A. & Kumar, V., Aug 2022, In: Limnology And Oceanography Letters. 7, 4, p. 287-301 15 p.Research output: Contribution to journal › Article › peer-review
Open Access3 Scopus citations
Datasets
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Code Release: Daily surface temperatures for 185,549 lakes in the conterminous United States estimated using deep learning (1980-2020)
Willard, J. D., Read, J. S., Topp, S., Hansen, G. A. & Kumar, V., ZENODO, 2022
DOI: 10.5281/zenodo.6210917, https://zenodo.org/record/6210917
Dataset