Haibin Chang

2.1k citations
45 papers · 1.1k indexed · 1 hit paper · h-index 19
Topics
Reservoir Engineering and Simulation Methods (19 papers)Hydraulic Fracturing and Reservoir Analysis (15 papers)Groundwater flow and contamination studies (12 papers)

In The Last Decade

Haibin Chang

42 papers receiving 1.1k citations

Hit Papers

Deep learning of subsurface flow via theory-guided neural...2020202620222024202050100150200

Peers

Haibin Chang
Comparison fields: 5 of 87
  • Ocean Engineering 509
  • Mechanical Engineering 406
  • Environmental Engineering 328
  • Statistical and Nonlinear Physics 277
  • Geophysics 171
Replace Nanzhe Wang with:
Nanzhe Wang China
G. Tartakovsky United States
Daolun Li China
Pallav Sarma United States
David A. Barajas‐Solano United States
Eduardo Gildin United States
Sergey Oladyshkin Germany
Meng Tang United States
Sadegh Karimpouli Iran
John Jakeman United States
Haibin Chang relative to Nanzhe Wang China Nanzhe Wang's profile →
Citations per field
00.5×4.5×
Nanzhe Wang · 1×
Citations per year

Countries citing papers authored by Haibin Chang

Since Specialization
Citations

This map shows the geographic impact of Haibin Chang'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 Haibin Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haibin Chang more than expected).

Fields of papers citing papers by Haibin Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Haibin Chang. 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 Haibin Chang. The network helps show where Haibin Chang may publish in the future.

Co-authorship network of co-authors of Haibin Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Haibin Chang. A scholar is included among the top collaborators of Haibin Chang 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 Haibin Chang. Haibin Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 1
4 3
5 5
6 15
7 27
8 2
9 0
10 36
11 58
12 4
13
Deep learning of subsurface flow via theory-guided neural networkbreakdown →
223
14 10
15 57
16 15
17 35
18 17
19 28
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MEASURING THE EFFECT OF OBSERVATIONS USING THE POSTERIOR AND THE INTRINSICBAYES FACTORS WITH VAGUE PRIOR INFORMATION
3

About Haibin Chang

Haibin Chang is a scholar working on Ocean Engineering, Environmental Engineering and Statistical and Nonlinear Physics, having authored 45 papers that have together received 1.1k indexed citations. Recurring topics across this work include Reservoir Engineering and Simulation Methods (19 papers), Hydraulic Fracturing and Reservoir Analysis (15 papers) and Groundwater flow and contamination studies (12 papers). The work is most often cited by research in Ocean Engineering (509 citations), Environmental Engineering (328 citations) and Statistical and Nonlinear Physics (277 citations). Haibin Chang has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include Dongxiao Zhang, Nanzhe Wang, Heng Li, Zhiming Lü, Qinzhuo Liao, Hao Xu, Yuntian Chen, Lingzao Zeng, Yan Chen and Meng Jin. Their work appears in journals such as Water Resources Research, Journal of Computational Physics and Journal of Experimental Botany.

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.

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