Evaluation of PERSIANN-CDR Constructed Using GPCP V2.2 and V2.3 and A Comparison with TRMM 3B42 V7 and CPC Unified Gauge-Based Analysis in Global Scale. - Mojtaba Sadeghi; Ata Akabri Asanjan; Mohammad Faridzad; Vesta Afzali Gorooh; Phu Nguyen; Kuolin Hsu; Soroosh Sorooshian; Dan Braithwaite (Remote. Sens., 2019)

Improving near real-time precipitation estimation using a U-Net convolutional neural network and geographical information. - Mojtaba Sadeghi; Phu Nguyen; Kuolin Hsu; Soroosh Sorooshian (Environ. Model. Softw., 2020)

Spatiotemporal Variations of Precipitation over Iran Using the High-Resolution and Nearly Four Decades Satellite-Based PERSIANN-CDR Dataset. - Hamidreza Mosaffa; Mojtaba Sadeghi; Negin Hayatbini; Vesta Afzali Gorooh; Ata Akbari Asanjan; Phu Nguyen; Soroosh Sorooshian (Remote. Sens., 2020)

The Application of PERSIANN Family Datasets for Hydrological Modeling. - Hossein Salehi; Mojtaba Sadeghi; Saeed Golian; Phu Nguyen; Conor Murphy; Soroosh Sorooshian (Remote. Sens., 2022)

Evaluating the usability of a cancer registry system using Cognitive Walkthrough, and assessing user agreement with its problems. - Fatemeh Bagheri; Faezeh Abbasi; Mojtaba Sadeghi; Reza Khajouei (BMC Medical Informatics Decis. Mak., 2023)