Changhyun Jun

2.7k total citations · 2 hit papers
143 papers, 1.8k citations indexed

About

Changhyun Jun is a scholar working on Global and Planetary Change, Water Science and Technology and Environmental Engineering. According to data from OpenAlex, Changhyun Jun has authored 143 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 86 papers in Global and Planetary Change, 55 papers in Water Science and Technology and 53 papers in Environmental Engineering. Recurrent topics in Changhyun Jun's work include Hydrology and Watershed Management Studies (51 papers), Flood Risk Assessment and Management (45 papers) and Hydrology and Drought Analysis (37 papers). Changhyun Jun is often cited by papers focused on Hydrology and Watershed Management Studies (51 papers), Flood Risk Assessment and Management (45 papers) and Hydrology and Drought Analysis (37 papers). Changhyun Jun collaborates with scholars based in South Korea, United States and Iran. Changhyun Jun's co-authors include Sayed M. Bateni, Shahab S. Band, Chulsang Yoo, Mohammad Valipour, Roohollah Noori, Soroush Abolfathi, Xiaosheng Qin, Kwok‐wing Chau, Mengzhu Chen and Khabat Khosravi and has published in prestigious journals such as Environmental Science & Technology, The Science of The Total Environment and Water Research.

In The Last Decade

Changhyun Jun

131 papers receiving 1.7k citations

Hit Papers

Predicting Chlorophyll-a Concentrations in the World’s La... 2025 2026 2025 2025 10 20 30
What are hit papers?

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.

  1. Predicting Chlorophyll-a Concentrations in the World’s Largest Lakes Using Kolmogorov-Arnold Networks
    2025 32 citations Roohollah Noori, Changhyun Jun et al. profile →
  2. Environmental controls on the conversion of nutrients to chlorophyll in lakes
    2025 20 citations Roohollah Noori, Dongkyun Kim et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Changhyun Jun South Korea 23 761 562 507 314 203 143 1.8k
Vahid Moosavi Iran 20 690 0.9× 799 1.4× 477 0.9× 268 0.9× 141 0.7× 61 1.5k
Giha Lee South Korea 17 748 1.0× 594 1.1× 637 1.3× 376 1.2× 224 1.1× 82 1.6k
Jun Guo China 19 895 1.2× 653 1.2× 397 0.8× 381 1.2× 177 0.9× 89 1.8k
Mohammad Ali Ghorbani Iran 18 511 0.7× 640 1.1× 406 0.8× 129 0.4× 129 0.6× 34 1.4k
Shengqi Jian China 18 1.0k 1.4× 774 1.4× 866 1.7× 326 1.0× 131 0.6× 69 1.7k
Biswa Bhattacharya Netherlands 17 486 0.6× 481 0.9× 452 0.9× 210 0.7× 196 1.0× 51 1.2k
Saeed Samadianfard Iran 24 630 0.8× 951 1.7× 670 1.3× 211 0.7× 268 1.3× 54 1.9k
Sarita Gajbhiye Meshram India 29 1.1k 1.4× 999 1.8× 888 1.8× 264 0.8× 100 0.5× 104 2.7k
Duong Tran Anh Vietnam 30 1.1k 1.4× 792 1.4× 778 1.5× 335 1.1× 143 0.7× 87 2.3k

Countries citing papers authored by Changhyun Jun

Since Specialization
Citations

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

Fields of papers citing papers by Changhyun Jun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Changhyun Jun

This figure shows the co-authorship network connecting the top 25 collaborators of Changhyun Jun. A scholar is included among the top collaborators of Changhyun Jun 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 Changhyun Jun. Changhyun Jun 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
1.
Khosravi, Khabat, et al.. (2025). River total dissolved gas prediction using a hybrid greedy-stepwise feature selection and bidirectional long short-term memory model. Ecological Informatics. 90. 103191–103191. 1 indexed citations
2.
Saleem, Muhammad, Muhammad Shoaib, Hafiz Umar Farid, et al.. (2025). Machine learning-based streamflow projections in the upper indus basin under CMIP6 climate scenarios. Physics and Chemistry of the Earth Parts A/B/C. 140. 104035–104035. 1 indexed citations
3.
Khosravi, Khabat, Sayed M. Bateni, Dongkyun Kim, et al.. (2025). Assessing Pan-Canada wildfire susceptibility by integrating satellite data with novel hybrid deep learning and black widow optimizer algorithms. The Science of The Total Environment. 977. 179369–179369. 3 indexed citations
4.
Noori, Roohollah, Sayed M. Bateni, Changhyun Jun, et al.. (2025). Pivotal role of snow depth, local atmospheric conditions, and large-scale climate signals on ice thinning in Finnish lakes. The Science of The Total Environment. 966. 178715–178715. 8 indexed citations
5.
Noori, Roohollah, Changhyun Jun, Sayed M. Bateni, et al.. (2025). New insights on biomass production in lakes: Integration of Carlson trophic state index and vertically generalized production model. Ecological Indicators. 174. 113450–113450. 5 indexed citations
6.
Xu, Tongren, Shaomin Liu, Dongkyun Kim, et al.. (2025). Estimation and mechanism analysis of global evapotranspiration based on a physics-informed deep-learning model. Journal of Hydrology. 664. 134351–134351.
7.
Janizadeh, Saeid, et al.. (2024). Estimating equilibrium scour depth around non-circular bridge piers using interpretable hybrid machine learning models. Ocean Engineering. 312. 119246–119246. 8 indexed citations
8.
Xu, Tongren, Wenjie Yin, Sayed M. Bateni, et al.. (2024). A machine learning downscaling framework based on a physically constrained sliding window technique for improving resolution of global water storage anomaly. Remote Sensing of Environment. 313. 114359–114359. 18 indexed citations
9.
Janizadeh, Saeid, et al.. (2024). Predicting equilibrium scour depth around non-circular bridge piers with shallow foundations using hybrid explainable machine learning methods. Results in Engineering. 24. 103492–103492. 4 indexed citations
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Baik, Jongjin, et al.. (2024). Quantification of interactions among agricultural drought indices within Köppen–Geiger climate zones in Bangladesh. Agricultural Water Management. 302. 108952–108952. 1 indexed citations
13.
Janizadeh, Saeid, Sayed M. Bateni, Changhyun Jun, et al.. (2024). Advancing the LightGBM approach with three novel nature-inspired optimizers for predicting wildfire susceptibility in Kauaʻi and Molokaʻi Islands, Hawaii. Expert Systems with Applications. 258. 124963–124963. 9 indexed citations
14.
Jun, Changhyun, et al.. (2024). Daily runoff forecasting using novel optimized machine learning methods. Results in Engineering. 24. 103319–103319. 5 indexed citations
15.
Jun, Changhyun, Dongkyun Kim, Sayed M. Bateni, et al.. (2024). Prediction of earth-fissure hazards: Unraveling the crucial roles of land use and groundwater fluctuations. Environmental Impact Assessment Review. 110. 107692–107692. 2 indexed citations
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Valipour, Mohammad, et al.. (2023). Machine-learning-based short-term forecasting of daily precipitation in different climate regions across the contiguous United States. Expert Systems with Applications. 238. 121907–121907. 13 indexed citations
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Rezaie, Fatemeh, Mahdi Panahi, Sayed M. Bateni, et al.. (2023). Development of novel optimized deep learning algorithms for wildfire modeling: A case study of Maui, Hawai‘i. Engineering Applications of Artificial Intelligence. 125. 106699–106699. 11 indexed citations
20.
Nia, Alireza Moghaddam, Ali Salajegheh, Parham Moradi, et al.. (2023). Performance improvement of the linear muskingum flood routing model using optimization algorithms and data assimilation approaches. Natural Hazards. 118(3). 2657–2690. 5 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.

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