World's Best Scientists 2026 revealed!
Milad Arabloo

Milad Arabloo

Award Badge
Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
35
Citations
3042
World Ranking
858
National Ranking
20

Engineering and Technology

D-Index
37
Citations
3328
World Ranking
8531
National Ranking
341

Milad Arabloo 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 Milad Arabloo 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: 61 publications — 1st percentile

1% of scientists in this discipline score the same or lower.

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

Milad Arabloo 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 Milad Arabloo 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: 37 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Milad Arabloo is affiliated with PERM Inc. in Canada and has contributions across multiple fields related to engineering and environmental science. Their research portfolio spans diverse subfields including ocean engineering, environmental engineering, water science and technology, computational mechanics, and civil and structural engineering.

Their published work includes studies on enhanced oil recovery techniques, hydrological forecasting using artificial intelligence, water quality monitoring technologies, lattice Boltzmann simulation studies, grouting, rheology and soil mechanics, hydraulic fracturing and reservoir analysis, as well as drilling and well engineering.

Their recent scholarly articles include:

  • Microfluidic study of surfactant flooding of heavy oil in layered porous media containing fractures, 2024, The Canadian Journal of Chemical Engineering
  • Physicochemical properties of nano-enhanced colloidal gas aphron (NCGA)-based fluids, 2020, The European Physical Journal Plus
  • Robust computational modelling of the sodium adsorption ratio using regression analysis and support vector machine, 2020, International Journal of Data Science

Milad Arabloo has published multiple articles in several frequent publication venues such as:

  • International Journal of Data Science
  • The European Physical Journal Plus
  • The Canadian Journal of Chemical Engineering

Their collaboration network includes frequent coauthors:

  • Mohammad Hossein Ghazanfari
  • Alireza Rostami
  • Alibakhsh Kasaeian
  • Khalil Shahbazi
  • Amir Tabzar

The main areas of study of their work consist of:

  • Engineering
  • Environmental Science

The subfields most represented in their research are:

  • Ocean Engineering
  • Environmental Engineering
  • Water Science and Technology
  • Computational Mechanics
  • Civil and Structural Engineering

The core topics covered in Milad Arabloo's publications include:

  • Enhanced Oil Recovery Techniques
  • Hydrological Forecasting Using AI
  • Water Quality Monitoring Technologies
  • Lattice Boltzmann Simulation Studies
  • Grouting, Rheology, and Soil Mechanics
  • Hydraulic Fracturing and Reservoir Analysis
  • Drilling and Well Engineering

Best Publications

  • Intelligent model for prediction of CO2 – Reservoir oil minimum miscibility pressure

    Amin Shokrollahi;Milad Arabloo;Farhad Gharagheizi;Farhad Gharagheizi;Amir H. Mohammadi

  • Implementing radial basis function networks for modeling CO2-reservoir oil minimum miscibility pressure

    Afshin Tatar;Amin Shokrollahi;Mohammad Mesbah;Saeed Rashid

  • Implementation of SVM framework to estimate PVT properties of reservoir oil

    Shahin Rafiee-Taghanaki;Milad Arabloo;Ali Chamkalani;Ali Chamkalani;Mahmood Amani

  • Laccase immobilized manganese ferrite nanoparticle: Synthesis and LSSVM intelligent modeling of decolorization

    Niyaz Mohammad Mahmoodi;Milad Arabloo;Jafar Abdi

  • Efficient estimation of natural gas compressibility factor using a rigorous method

    Amir Fayazi;Milad Arabloo;Amir H. Mohammadi

  • Rapid method to estimate the minimum miscibility pressure (MMP) in live reservoir oil systems during CO2 flooding

    Arash Kamari;Milad Arabloo;Amin Shokrollahi;Farhad Gharagheizi;Farhad Gharagheizi

  • Application of ANFIS soft computing technique in modeling the CO2 capture with MEA, DEA, and TEA aqueous solutions

    Mohammad M. Ghiasi;Mohammad M. Ghiasi;Milad Arabloo;Amir H. Mohammadi;Amir H. Mohammadi;Tohid Barghi

  • State-of-the-Art Least Square Support Vector Machine Application for Accurate Determination of Natural Gas Viscosity

    Amir Fayazi;Milad Arabloo;Amin Shokrollahi;Mohammad Hadi Zargari

  • Toward a predictive model for estimating dew point pressure in gas condensate systems

    Milad Arabloo;Amin Shokrollahi;Farhad Gharagheizi;Farhad Gharagheizi;Amir H. Mohammadi

  • Application of constrained multi-variable search methods for prediction of PVT properties of crude oil systems

    Milad Arabloo;Mohammad-Amin Amooie;Abdolhossein Hemmati-Sarapardeh;Mohammad-Hossein Ghazanfari

  • Toward an intelligent approach for determination of saturation pressure of crude oil

    Amir Farasat;Amin Shokrollahi;Milad Arabloo;Farhad Gharagheizi

  • Modeling of CO2 solubility in crude oil during carbon dioxide enhanced oil recovery using gene expression programming

    Alireza Rostami;Milad Arabloo;Arash Kamari;Amir H. Mohammadi

  • Wettability modification, interfacial tension and adsorption characteristics of a new surfactant: Implications for enhanced oil recovery

    Milad Arabloo;Mohammad Hossein Ghazanfari;Davood Rashtchian

  • Application of a radial basis function neural network to estimate pressure gradient in water–oil pipelines

    Mohamad A. Halali;Vahid Azari;Milad Arabloo;Amir H. Mohammadi;Amir H. Mohammadi

  • Prediction of natural gas flow through chokes using support vector machine algorithm

    Ibrahim Nejatian;Mojtaba Kanani;Milad Arabloo;Alireza Bahadori

  • Application of soft computing approaches for modeling saturation pressure of reservoir oils

    Roya Talebi;Mohammad M. Ghiasi;Hossein Talebi;Mehrdad Mohammadyian

  • A novel modeling approach to optimize oxygen–steam ratios in coal gasification process

    Milad Arabloo;Alireza Bahadori;Mohammad M. Ghiasi;Moonyong Lee

  • Robust Modeling Approach for Estimation of Compressibility Factor in Retrograde Gas Condensate Systems

    Mohammad M. Ghiasi;Arya Shahdi;Pezhman Barati;Milad Arabloo

  • Toward genetic programming (GP) approach for estimation of hydrocarbon/water interfacial tension

    Alireza Rostami;Hojatollah Ebadi;Milad Arabloo;Mahdi Kalantari Meybodi

  • Accurate estimation of CO2 adsorption on activated carbon with multi-layer feed-forward neural network (MLFNN) algorithm

    Alireza Rostami;Mohammad Amin Anbaz;Hamid Reza Erfani Gahrooei;Milad Arabloo

  • Characterization of Colloidal Gas Aphron-Fluids Produced from a New Plant-Based Surfactant

    Milad Arabloo;Mojtaba Pordel Shahri;Majid Zamani

Frequent Co-Authors

Amir H. Mohammadi
Amir H. Mohammadi University of KwaZulu-Natal
Amin Shokrollahi
Amin Shokrollahi École Polytechnique Fédérale de Lausanne
Alireza Bahadori
Alireza Bahadori Southern Cross University
Farhad Gharagheizi
Farhad Gharagheizi Georgia Institute of Technology
Mohammad Hossein Ghazanfari
Mohammad Hossein Ghazanfari Sharif University of Technology
Moonyong Lee
Moonyong Lee Yeungnam University
Sohrab Zendehboudi
Sohrab Zendehboudi Memorial University of Newfoundland
Niyaz Mohammad Mahmoodi
Niyaz Mohammad Mahmoodi Institute for Color Science and Technology
Ali Abbas
Ali Abbas University of Sydney
Alibakhsh Kasaeian
Alibakhsh Kasaeian University of Tehran

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