Fi‐John Chang

11.4k citations
200 papers · 9.0k indexed · 1 hit paper · h-index 54

Fi‐John Chang

195 papers receiving 8.7k citations

Hit Papers

Exploring a Long Short-Term Memory based Encoder-Decoder ...297202020262022202450100150200250

Peers

Fi‐John Chang
Comparison fields: 5 of 152
  • Environmental Engineering 4.3k
  • Water Science and Technology 4.1k
  • Global and Planetary Change 3.0k
  • Ocean Engineering 1.9k
  • Civil and Structural Engineering 1.2k
Replace Guangtao Fu with:
Guangtao Fu United Kingdom
Ahmed El‐Shafie Malaysia
Ni‐Bin Chang United States
Ali Najah Ahmed Malaysia
Ravinesh C. Deo Australia
Patrick M. Reed United States
Shenglian Guo China
Slobodan P. Simonović Canada
Graeme C. Dandy Australia
Alban Kuriqi Portugal
Fi‐John Chang relative to Guangtao Fu United Kingdom Guangtao Fu's profile →
Citations per field
00.5×1.5×
Guangtao Fu · 1×
Citations per year

Countries citing papers authored by Fi‐John Chang

Since Specialization
Citations

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

Fields of papers citing papers by Fi‐John Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Fi‐John Chang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Fi‐John Chang Line = papers co-authored together Fi‐John Chang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20257
3 20256
4 20252
5 20250
6 20243
7 202411
8 20241
9 20249
10 202413
11 20245
12 20241
13 202421
14 20239
15 20239
16 202313
17 202333
18 201669
19 20151
20
PHYSICAL MODELING OF HYDRAULIC DESILTATION IN TAPU RESERVOIR
20016

About Fi‐John Chang

Fi‐John Chang is a scholar working on Environmental Engineering, Water Science and Technology, Global and Planetary Change, Ocean Engineering and Atmospheric Science, having authored 200 papers that have together received 9.0k indexed citations. Recurring topics across this work include Hydrological Forecasting Using AI (80 papers), Hydrology and Watershed Management Studies (67 papers), Flood Risk Assessment and Management (60 papers), Water resources management and optimization (39 papers), Water-Energy-Food Nexus Studies (21 papers), Reservoir Engineering and Simulation Methods (16 papers), Water Systems and Optimization (16 papers) and Fish Ecology and Management Studies (13 papers). The work is most often cited by research in Environmental Engineering (4.3k citations), Water Science and Technology (4.1k citations), Global and Planetary Change (3.0k citations), Ocean Engineering (1.9k citations) and Civil and Structural Engineering (1.2k citations). Fi‐John Chang has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Li‐Chiu Chang, Yanlai Zhou, Ya-Ting Chang, I-Feng Kao, Yen‐Ming Chiang, Yen‐Chang Chen, Shenglian Guo, Wen‐Ping Tsai, Li Chen and Pin-An Chen. Their work appears in journals such as Journal of Hydrology, Hydrological Processes, The Science of The Total Environment, Water and Journal of Environmental Management.

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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