World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
39
Citations
9767
World Ranking
2135
National Ranking
905

George Deodatis publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where George Deodatis sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 144 publications — 35th percentile

35% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

George Deodatis D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where George Deodatis sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 39 D-Index — 41st percentile

41% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Overview

George Deodatis is affiliated with Columbia University in the United States. Their research primarily spans the fields of Engineering and Earth and Planetary Sciences, with a particular focus on Civil and Structural Engineering, Statistics, Probability and Uncertainty, Atmospheric Science, Global and Planetary Change, and Earth-Surface Processes.

The main topics of their research include Probabilistic and Robust Engineering Design, Flood Risk Assessment and Management, Tropical and Extratropical Cyclones Research, Structural Health Monitoring Techniques, Infrastructure Resilience and Vulnerability Analysis, Concrete Corrosion and Durability, and Infrastructure Maintenance and Monitoring.

Key publications by George Deodatis include:

  • "Simulation of wind velocity time histories on long span structures modeled as non-Gaussian stochastic waves," 2020, Probabilistic Engineering Mechanics
  • "High-Speed GIS-Based Simulation of Storm Surge-Induced Flooding Accounting for Sea Level Rise," 2021, Natural Hazards Review
  • "A methodological framework for determining an optimal coastal protection strategy against storm surges and sea level rise," 2021, Natural Hazards
  • "The Spectral Representation Method: A framework for simulation of stochastic processes, fields, and waves," 2024, Reliability Engineering & System Safety
  • "Optimization of Coastal Protections in the Presence of Climate Change," 2021, Frontiers in Climate

George Deodatis has published multiple works in several key venues, including:

  • Probabilistic Engineering Mechanics
  • Reliability Engineering & System Safety
  • Natural Hazards Review
  • Natural Hazards
  • Frontiers in Climate

The scientist has frequent collaborations with several coauthors, notably:

  • Yuki Miura
  • Kyle T. Mandli
  • Haijun Zhou
  • Michael D. Shields
  • Philip C. Dinenis

Among their contributions to academic literature, George Deodatis has authored a book titled Risk-Based Inspection and Strength Evaluation of Suspension Bridge Main Cable Systems, published in 2023 by Transportation Research Board eBooks.

Best Publications

  • Simulation of Stochastic Processes by Spectral Representation

    Masanobu Shinozuka;George Deodatis

  • Simulation of Ergodic Multivariate Stochastic Processes

    George Deodatis

  • Simulation of Multi-Dimensional Gaussian Stochastic Fields by Spectral Representation

    Masanobu Shinozuka;George Deodatis

  • Non-stationary stochastic vector processes: seismic ground motion applications

    George Deodatis

  • Response Variability of Stochastic Finite Element Systems

    M. Shinozuka;G. Deodatis

  • Effects of random heterogeneity of soil properties on bearing capacity

    Radu Popescu;George Deodatis;Arash Nobahar

  • Simulation of Highly Skewed Non-Gaussian Stochastic Processes

    George Deodatis;George Deodatis;Raymond C. Micaletti;Raymond C. Micaletti

  • Stochastic process models for earthquake ground motion

    M. Shinozuka;G. Deodatis

  • Weighted Integral Method. I: Stochastic Stiffness Matrix

    George Deodatis

  • Auto‐Regressive Model for Nonstationary Stochastic Processes

    George Deodatis;M. Shinozuka

  • A method for generating fully non-stationary and spectrum-compatible ground motion vector processes

    Pierfrancesco Cacciola;George Deodatis

  • EFFECTS OF SPATIAL VARIABILITY ON SOIL LIQUEFACTION: SOME DESIGN RECOMMENDATIONS

    R. Popescu;J. H. Prevost;G. Deodatis

  • Weighted Integral Method. II: Response Variability and Reliability

    George Deodatis;Masanobu Shinozuka

  • Probabilistic Benefit-Cost Analysis for Earthquake Damage Mitigation: Evaluating Measures for Apartment Houses in Turkey

    Andrew W. Smyth;Gülay Altay;George Deodatis;Mustafa Erdik

  • A simple and efficient methodology to approximate a general non-Gaussian stationary stochastic process by a translation process

    M.D. Shields;G. Deodatis;P. Bocchini

  • Simulation of homogeneous nonGaussian stochastic vector fields

    R. Popescu;G. Deodatis;J.H. Prevost

  • Critical review and latest developments of a class of simulation algorithms for strongly non-Gaussian random fields

    Paolo Bocchini;George Deodatis

  • Uncertainty quantification in homogenization of heterogeneous microstructures modeled by XFEM

    Badri Hiriyur;Haim Waisman;George Deodatis

  • 3D effects in seismic liquefaction of stochastically variable soil deposits

    R. Popescu;J. H. Prevost;G. Deodatis

  • Dynamics of nonlinear porous media with applications to soil liquefaction

    Radu Popescu;Jean H. Prevost;George Deodatis;Pradipta Chakrabortty

Frequent Co-Authors

Dan M. Frangopol
Dan M. Frangopol Lehigh University
Bruce R. Ellingwood
Bruce R. Ellingwood Colorado State University
Masanobu Shinozuka
Masanobu Shinozuka Columbia University
Jean-Herve Prevost
Jean-Herve Prevost Princeton University
Haim Waisman
Haim Waisman Columbia University
Raimondo Betti
Raimondo Betti Columbia University
Manolis Papadrakakis
Manolis Papadrakakis National Technical University of Athens
Andrew W. Smyth
Andrew W. Smyth Columbia University
Daniel Bienstock
Daniel Bienstock Columbia University
Irene J. Beyerlein
Irene J. Beyerlein University of California, Santa Barbara

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Studying Mathematics in the USA opens doors to various advanced degree programs and diverse career paths. For professionals seeking to expand their expertise beyond pure mathematics, pursuing a specialized business degree, like a 1 year MBA programs in USA, can accelerate leadership opportunities in tech-driven industries.

Many students also leverage academic credits from prior education, making online MBA transfer credits a valuable option to reduce time and cost when earning advanced business qualifications.

For those focused on data-driven decision-making, combining a Mathematics background with analytics is strategic. Programs like analytics masters programs allow graduates to enhance skills in data interpretation and predictive modeling, leading to high-demand roles in various sectors.

Lastly, individuals exploring less competitive entry routes may consider easy MBA programs to get into, which provide accessible learning environments without compromising essential business acumen.

Best Scientists Citing George Deodatis

Trending Scientists

Recently Published Articles