Faghmous, James H.

Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data

Karpatne, A., Atluri, G., Faghmous, J. H., Steinbach, M., Banerjee, A., Ganguly, A., Shekhar, S., Samatova, N., & Kumar, V. (2017) · IEEE Transactions on Knowledge and Data Engineering

Model Reduction and Neural NetworksMachine Learning in Materials Science

Cited by 1,752

A daily global mesoscale ocean eddy dataset from satellite altimetry

Faghmous, J. H., Frenger, I., Yao, Y., Warmka, R., Lindell, A., & Kumar, V. (2015) · Scientific Data

Oceanographic and Atmospheric ProcessesArctic and Antarctic ice dynamics

Cited by 374

A Big Data Guide to Understanding Climate Change: The Case for Theory-Guided Data Science

Faghmous, J. H., & Kumar, V. (2014) · Big Data

Big Data Technologies and ApplicationsClimate variability and models

Cited by 223

Theory-Guided Data Science for Climate Change

Faghmous, J. H., Banerjee, A., Shekhar, S., Steinbach, M., Kumar, V., Ganguly, A. R., & Samatova, N. (2014) · Computer

Climate variability and modelsSpatial and Panel Data Analysis

Cited by 42

EddyScan: A physically consistent ocean eddy monitoring application

Faghmous, J. H., Styles, L., Mithal, V., Boriah, S., Liess, S., Kumar, V., Vikebo, F., & Mesquita, M. D. S. (2012) · 2012 Conference on Intelligent Data Understanding

Oceanographic and Atmospheric ProcessesOcean Waves and Remote Sensing

Cited by 29

Spatio-Temporal Consistency as a Means to Identify Unlabeled Objects in a Continuous Data Field

Faghmous, J., Nguyen, H., Le, M., & Kumar, V. (2014) · Proceedings of the AAAI Conference on Artificial Intelligence

Oceanographic and Atmospheric ProcessesArctic and Antarctic ice dynamics

Cited by 7

Computing and Climate

Faghmous, J. H., Kumar, V., & Shekhar, S. (2015) · Computing in Science & Engineering

Scientific Computing and Data ManagementEnergy Efficiency in Computing

Cited by 4