Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A Review of Global Precipitation Data Sets: Data Sources, Estimation, and Intercomparisons
20171.4k citationsHamed Ashouri, Soroosh Sorooshian et al.profile →
Artificial Neural Network Modeling of the Rainfall‐Runoff Process
19951.2k citationsKuolin Hsu, Hoshin V. Gupta et al.Water Resources Researchprofile →
PERSIANN-CDR: Daily Precipitation Climate Data Record from Multisatellite Observations for Hydrological and Climate Studies
20141.1k citationsHamed Ashouri, Kuolin Hsu et al.profile →
Evaluation of PERSIANN System Satellite–Based Estimates of Tropical Rainfall
20001.0k citationsSoroosh Sorooshian, Kuolin Hsu et al.profile →
Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks
1997893 citationsKuolin Hsu, Soroosh Sorooshian et al.profile →
Precipitation Estimation from Remotely Sensed Imagery Using an Artificial Neural Network Cloud Classification System
2004673 citationsKuolin Hsu, Soroosh Sorooshian et al.profile →
Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter
2005624 citationsKuolin Hsu, Hoshin V. Gupta et al.Water Resources Researchprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Kuolin Hsu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kuolin Hsu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kuolin Hsu more than expected).
This network shows the impact of papers produced by Kuolin Hsu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kuolin Hsu. The network helps show where Kuolin Hsu may publish in the future.
Co-authorship network of co-authors of Kuolin Hsu
This figure shows the co-authorship network connecting the top 25 collaborators of Kuolin Hsu.
A scholar is included among the top collaborators of Kuolin Hsu based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Kuolin Hsu. Kuolin Hsu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Sadeghi, Mojtaba, Phung‐Anh Nguyen, Kuolin Hsu, & Soroosh Sorooshian. (2020). Application of Deep Neural Networks and Geographical Information for Improving the Near Real-time Precipitation Estimation Products. AGU Fall Meeting Abstracts. 2020.1 indexed citations
Pan, Baoxiang, Kuolin Hsu, Amir AghaKouchak, & Soroosh Sorooshian. (2017). The Use of Convolutional Neural Network in Relating Precipitation to Circulation. AGU Fall Meeting Abstracts. 2017.2 indexed citations
Sorooshian, Soroosh, Kuolin Hsu, Hamed Ashouri, et al.. (2015). PERSIANN-CDR Daily Precipitation Dataset for Hydrologic Applications and Climate Studies.. AGUFM. 2015.1 indexed citations
15.
Huffman, George J., David T. Bolvin, Dan Braithwaite, et al.. (2015). First Results from the Integrated Multi-Satellite Retrievals for GPM (IMERG). EGU General Assembly Conference Abstracts. 17. 7034.5 indexed citations
16.
Huffman, George J., David T. Bolvin, Dan Braithwaite, et al.. (2012). Developing the Integrated Multi-Satellite Retrievals for GPM (IMERG). EGU General Assembly Conference Abstracts. 6921.22 indexed citations
17.
Hong, Yulan, Kuolin Hsu, & Soroosh Sorooshian. (2003). Precipitation Estimation from Remotely Sensed Information using ANN-Cloud Classification System. AGU Fall Meeting Abstracts. 2003.4 indexed citations
18.
Hsu, Kuolin, Hoshin V. Gupta, & Soroosh Sorooshian. (1998). Streamflow Forecasting Using Artificial Neural Networks. Water resources engineering. 967–972.21 indexed citations
19.
Hsu, Kuolin. (1996). Rainfall estimation from satellite infrared imagery using artificial neural networks. UA Campus Repository (The University of Arizona).2 indexed citations
20.
Hsu, Kuolin, Hoshin V. Gupta, & Soroosh Sorooshian. (1996). A SUPERIOR TRAINING STRATEGY FOR THREE-LAYER FEEDFORWARD ARTIFICIAL NEURAL NETWORKS. UA Campus Repository (The University of Arizona).2 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.