The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Dongxiao Zhang sits on this spectrum.
This scientist: 344 publications — 83rd percentile
83% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 804 publications or more.
The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Dongxiao Zhang sits on this spectrum.
This scientist: 70 D-Index — 90th percentile
90% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 107 D-Index or more.
Dongxiao Zhang is affiliated with the Southern University of Science and Technology in China. Their research spans multiple areas within engineering, with a particular focus on ocean engineering, artificial intelligence, mechanical engineering, mechanics of materials, and computational mechanics.
The scientist's work targets several main topics, including hydraulic fracturing and reservoir analysis, model reduction and neural networks, drilling and well engineering, reservoir engineering and simulation methods, hydrocarbon exploration and reservoir analysis, energy load and power forecasting, and seismic imaging and inversion techniques.
Frequent co-authors of Dongxiao Zhang include Yuntian Chen, Nanzhe Wang, Hao Xu, Sanbai Li, and Haibin Chang, demonstrating a collaborative research approach across diverse projects.
Their recent publications indicate a focus on the application of deep learning and theory-guided modeling to complex physical and energy systems. Notable papers include:
Dongxiao Zhang's work is frequently published in venues such as arXiv (Cornell University), Zenodo (CERN European Organization for Nuclear Research), SSRN Electronic Journal, SPE Journal, and Journal of Hydrology.
The research profile of Dongxiao Zhang reflects extensive engagement with engineering disciplines, integrating computational techniques and physical modeling to address challenges in energy forecasting, reservoir engineering, and fluid dynamics.
Dongxiao Zhang
Yan Chen;Dean S. Oliver;Dongxiao Zhang
Dongxiao Zhang;Zhiming Lu
Yan Chen;Dongxiao Zhang
Qinjun Kang;Peter C. Lichtner;Dongxiao Zhang
Juan Song;Dongxiao Zhang
Dongxiao Zhang;Raoyang Zhang;Shiyi Chen;Wendy E. Soll
Qinjun Kang;Dongxiao Zhang;Shiyi Chen
Qinjun Kang;Qinjun Kang;Dongxiao Zhang;Shiyi Chen;Shiyi Chen;Xiaoyi He
Heng Li;Heng Li;Dongxiao Zhang;Dongxiao Zhang
Xiaofeng Xu;Shiyi Chen;Shiyi Chen;Dongxiao Zhang;Dongxiao Zhang
Qinjun Kang;Peter C. Lichtner;Dongxiao Zhang
Nanzhe Wang;Dongxiao Zhang;Haibin Chang;Heng Li
Dongxiao Zhang;Juan Song
Dongxiao Zhang;Yuntian Chen;Jin Meng
Xing Luo;Dongxiao Zhang;Xu Zhu;Xu Zhu
Qinjun Kang;Qinjun Kang;Dongxiao Zhang;Shiyi Chen;Shiyi Chen
Qinjun Kang;Qinjun Kang;Dongxiao Zhang;Shiyi Chen;Shiyi Chen
Xianhong Xie;Dongxiao Zhang;Dongxiao Zhang
Junsheng Zeng;Heng Li;Dongxiao Zhang
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