GISS Personnel Directory
Dr. Mohammad H. Erfani
Columbia University
E-mail: se2639@columbia.edu
Recent Publications
Zarrabi, R., R. McDermott, , and S. Cohen, 2025: Bankfull and mean-flow channel geometry estimation through machine learning algorithms across the CONtiguous United States (CONUS). Water Resour. Res., 61, no. 2, e2024WR037997, doi:10.1029/2024WR037997.
Asadi Shamsabadi, E., , C. Xu, and D. Dias-da-Costa, 2024: Efficient semi-supervised surface crack segmentation with small datasets based on consistency regularisation and pseudo-labelling. Autom. Constr., 158, 105181, doi:10.1016/j.autcon.2023.105181.
, M. Erfani, S. Cohen, A.R.J. Downey, and E. Goharian, 2024: A large dataset of fluvial hydraulic and geometry attributes derived from USGS field measurement records. Environ. Model. Softw., 180, 106136, doi:10.1016/j.envsoft.2024.106136.
, and E. Goharian, 2023: Vision-based texture and color analysis of waterbody images using computer vision and deep learning techniques. J. Hydroinform., 25, no. 3, 835-850, doi:10.2166/hydro.2023.146.
, C. Smith, Z. Wu, E. Asadi Shamsabadi, F. Khatami, A.R.J. Downey, J. Imran, and E. Goharian, 2023: Eye of Horus: A vision-based framework for real-time water level measurement. Hydrol. Earth Syst. Sci., 27, no. 22, 4135-4149, doi:10.5194/hess-27-4135-2023.
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