World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
46
Citations
7371
World Ranking
5212
National Ranking
1474

Ming Ye publication distribution in Engineering and Technology in 2026

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 Ming Ye sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 243 publications — 62nd percentile

62% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Ming Ye D-index placement in Engineering and Technology in 2026

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 Ming Ye sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 46 D-Index — 49th percentile

49% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Ming Ye is a researcher affiliated with Florida State University in the United States. Their work spans multiple fields of study including Medicine, Engineering, and Environmental Science. Within these broader areas, Ming Ye has contributed substantially to subfields such as Neurology, Environmental Engineering, Civil and Structural Engineering, Public Health, Environmental and Occupational Health, and Global and Planetary Change.

The researcher's main topics of work encompass Soil and Unsaturated Flow, Groundwater flow and contamination studies, Mathematical and Theoretical Epidemiology and Ecology Models, Vascular Malformations Diagnosis and Treatment, Hydrology and Watershed Management Studies, Intracranial Aneurysms: Treatment and Complications, and Groundwater and Isotope Geochemistry.

Among Ming Ye's recent notable papers are:

  • Groundwater sustainability: a review of the interactions between science and policy, 2020, Environmental Research Letters
  • Using t-distributed Stochastic Neighbor Embedding (t-SNE) for cluster analysis and spatial zone delineation of groundwater geochemistry data, 2021, Journal of Hydrology
  • Using cluster analysis for understanding spatial and temporal patterns and controlling factors of groundwater geochemistry in a regional aquifer, 2020, Journal of Hydrology
  • GW-PINN: A deep learning algorithm for solving groundwater flow equations, 2022, Advances in Water Resources
  • Performance analysis and optimization of a novel cooling plate with non-uniform pin-fins for lithium battery thermal management, 2021, Applied Thermal Engineering

The primary publication venues where Ming Ye's work appears include the Journal of Hydrology, SSRN Electronic Journal, Water Resources Research, Agricultural Water Management, and Sensors. The most frequent venue is the Journal of Hydrology, with 24 publications.

Ming Ye often collaborates with other researchers, with frequent coauthors being Qimin Zhang, Yan Zhu, Jinzhong Yang, Jing Yang, and Heng Dai. These collaborations highlight a network of scientific relationships mainly within the fields of environmental and engineering sciences.

Best Publications

  • Developing a Long Short-Term Memory (LSTM) based model for predicting water table depth in agricultural areas.

    Jianfeng Zhang;Yan Zhu;Xiaoping Zhang;Ming Ye

  • Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications

    Xiaomeng Song;Jianyun Zhang;Chesheng Zhan;Yunqing Xuan

  • Towards a comprehensive assessment of model structural adequacy

    Hoshin V. Gupta;Martyn P. Clark;Jasper A. Vrugt;Jasper A. Vrugt;Gab Abramowitz

  • Spatiotemporal variations of hydrogeochemistry and its controlling factors in the Gandaki River Basin, Central Himalaya Nepal.

    Ramesh Raj Pant;Fan Zhang;Faizan Ur Rehman;Guanxing Wang

  • Maximum likelihood Bayesian averaging of spatial variability models in unsaturated fractured tuff

    Ming Ye;Shlomo P. Neuman;Philip D. Meyer

  • A model-averaging method for assessing groundwater conceptual model uncertainty.

    Ming Ye;Karl F. Pohlmann;Jenny B. Chapman;Greg M. Pohll

  • Bayesian analysis of data-worth considering model and parameter uncertainties

    Shlomo P. Neuman;Liang Xue;Ming Ye;Dan Lu

  • Estimating daily air temperatures over the Tibetan Plateau by dynamically integrating MODIS LST data

    Hongbo Zhang;Hongbo Zhang;Fan Zhang;Fan Zhang;Ming Ye;Tao Che;Tao Che

  • Sensitivity analysis and assessment of prior model probabilities in MLBMA with application to unsaturated fractured tuff

    Ming Ye;Shlomo P. Neuman;Philip D. Meyer;Karl Pohlmann

  • Using t-distributed Stochastic Neighbor Embedding (t-SNE) for cluster analysis and spatial zone delineation of groundwater geochemistry data

    Honghua Liu;Jing Yang;Jing Yang;Ming Ye;Scott C. James

  • Snow cover and runoff modelling in a high mountain catchment with scarce data: effects of temperature and precipitation parameters

    Fan Zhang;Hongbo Zhang;Scott C. Hagen;Ming Ye

  • An adaptive sparse-grid high-order stochastic collocation method for Bayesian inference in groundwater reactive transport modeling

    Guannan Zhang;Dan Lu;Ming Ye;Max Gunzburger

  • Fume transports in a high rise industrial welding hall with displacement ventilation system and individual ventilation units

    Han-Qing Wang;Chun-Hua Huang;Di Liu;Fu-Yun Zhao;Fu-Yun Zhao

  • Using cluster analysis for understanding spatial and temporal patterns and controlling factors of groundwater geochemistry in a regional aquifer

    Jing Yang;Jing Yang;Ming Ye;Zhonghua Tang;Tian Jiao

  • Identification of sorption processes and parameters for radionuclide transport in fractured rock

    Zhenxue Dai;Andrew Wolfsberg;Paul Reimus;Hailin Deng

  • Nonlocal and localized analyses of conditional mean transient flow in bounded, randomly heterogeneous porous media

    Ming Ye;Ming Ye;Shlomo P. Neuman;Alberto Guadagnini;Daniel M. Tartakovsky

  • Assessment of parametric uncertainty for groundwater reactive transport modeling

    Xiaoqing Shi;Xiaoqing Shi;Ming Ye;Gary P. Curtis;Geoffery L. Miller

  • Estimation of effective unsaturated hydraulic conductivity tensor using spatial moments of observed moisture plume

    Tian Chyi J. Yeh;Ming Ye;Raziuddin Khaleel

  • Quantifying model structural error: Efficient Bayesian calibration of a regional groundwater flow model using surrogates and a data-driven error model

    Tianfang Xu;Tianfang Xu;Albert J. Valocchi;Ming Ye;Feng Liang

  • Numerical Comparison of Iterative Ensemble Kalman Filters for Unsaturated Flow Inverse Modeling

    Xuehang Song;Liangsheng Shi;Ming Ye;Jinzhong Yang

  • Practical Use of Computationally Frugal Model Analysis Methods

    Mary C. Hill;Dmitri Kavetski;Martyn Clark;Ming Ye

  • Groundwater Quality: Analysis of Its Temporal and Spatial Variability in a Karst Aquifer.

    Roger Pacheco Castro;Julia Pacheco Ávila;Ming Ye;Armando Cabrera Sansores

  • Expert elicitation of recharge model probabilities for the Death Valley regional flow system

    Ming Ye;Karl F. Pohlmann;Jenny B. Chapman

Frequent Co-Authors

Shlomo P. Neuman
Shlomo P. Neuman University of Arizona
Yu-Shu Wu
Yu-Shu Wu Colorado School of Mines
Martyn P. Clark
Martyn P. Clark University of Saskatchewan
Dmitri Kavetski
Dmitri Kavetski University of Adelaide
Mazdak Arabi
Mazdak Arabi Colorado State University
Zhenxue Dai
Zhenxue Dai Los Alamos National Laboratory
Anthony P. Walker
Anthony P. Walker Oak Ridge National Laboratory
Jichun Wu
Jichun Wu Nanjing University
Guo-Yue Niu
Guo-Yue Niu University of Arizona
Greg A. Barron-Gafford
Greg A. Barron-Gafford University of Arizona

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