World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
64
Citations
14443
World Ranking
1662
National Ranking
73

Ali Elkamel 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 Ali Elkamel 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: 549 publications — 96th percentile

96% of scientists in this discipline score the same or lower.

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

Ali Elkamel 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 Ali Elkamel 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: 64 D-Index — 84th percentile

84% of scientists in this discipline score the same or lower.

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

Overview

Ali Elkamel is affiliated with the University of Waterloo in Canada, contributing extensively to the field of engineering, especially within electrical and electronic engineering. Their research spans multiple areas, reflecting a broad engagement with energy systems and related technologies.

Elkamel's work covers several main topics, including:

  • Electric Vehicles and Infrastructure
  • Hybrid Renewable Energy Systems
  • Carbon Dioxide Capture Technologies
  • Smart Grid Energy Management
  • Process Optimization and Integration
  • Integrated Energy Systems Optimization
  • Advanced Battery Technologies Research

The scientist has published in numerous venues, with frequent contributions to:

  • Energies
  • Computers & Chemical Engineering
  • Sustainability
  • The Canadian Journal of Chemical Engineering
  • Energy

Several co-authors regularly collaborate with Ali Elkamel, including:

  • Ali Ahmadian
  • Ali Almansoori
  • Farzad Hourfar
  • Hossein Mashhadimoslem
  • Muhammad Rizwan

Among recent papers authored by or involving Ali Elkamel are:

  • "Deep Learning-Based Forecasting Approach in Smart Grids With Microclustering and Bidirectional LSTM Network" (2020), published in IEEE Transactions on Industrial Electronics
  • "Optimal bidding strategy of a virtual power plant in day-ahead energy and frequency regulation markets: A deep learning-based approach" (2020), published in International Journal of Electrical Power & Energy Systems
  • "A Review on Plug-in Electric Vehicles: Introduction, Current Status, and Load Modeling Techniques" (2020), published in Journal of Modern Power Systems and Clean Energy
  • "Short-term wind speed forecasting framework based on stacked denoising auto-encoders with rough ANN" (2020), published in Sustainable Energy Technologies and Assessments
  • "Techno-economic analysis of integrated hydrogen and methanol production process by CO2 hydrogenation" (2022), published in International Journal of Greenhouse Gas Control

Their publications demonstrate a multidisciplinary approach intertwining electrical engineering, mechanical engineering, biomedical engineering, control and systems engineering, and materials chemistry. The research outputs reflect an emphasis on applying advanced methodologies, including deep learning and optimization techniques, to address contemporary challenges in energy and environmental sectors.

Best Publications

  • Optimal Transition to Plug-In Hybrid Electric Vehicles in Ontario, Canada, Considering the Electricity-Grid Limitations

    A. Hajimiragha;C.A. Caizares;M.W. Fowler;A. Elkamel

  • Reservoir permeability prediction by neural networks combined with hybrid genetic algorithm and particle swarm optimization

    Mohammad Ali Ahmadi;Sohrab Zendehboudi;Ali Lohi;Ali Elkamel

  • Pyrolysis, kinetics analysis, thermodynamics parameters and reaction mechanism of Typha latifolia to evaluate its bioenergy potential.

    Muhammad Sajjad Ahmad;Muhammad Aamer Mehmood;Muhammad Aamer Mehmood;Syed Taha Haider Taqvi;Ali Elkamel

  • Design and experimental investigation of portable solar thermoelectric refrigerator

    Sabah A. Abdul-Wahab;Ali Elkamel;Ali Mohamed Al-Damkhi;Is'haq A. Al-Habsi

  • Benchmarking and selection of Power-to-Gas utilizing electrolytic hydrogen as an energy storage alternative

    Sean B. Walker;Ushnik Mukherjee;Michael Fowler;Ali Elkamel

  • Asphaltene precipitation and deposition in oil reservoirs –technical aspects, experimental and hybrid neural network predictive tools

    Sohrab Zendehboudi;Ali Shafiei;Alireza Bahadori;Lesley A. James

  • A Robust Optimization Approach for Planning the Transition to Plug-in Hybrid Electric Vehicles

    A. H. Hajimiragha;C. A. Canizares;M. W. Fowler;S. Moazeni

  • Modeling and optimization of a network of energy hubs to improve economic and emission considerations

    Azadeh Maroufmashat;Azadeh Maroufmashat;Ali Elkamel;Michael Fowler;Sourena Sattari

  • Plug-in electric vehicle batteries degradation modeling for smart grid studies: Review, assessment and conceptual framework

    Ali Ahmadian;Mahdi Sedghi;Ali Elkamel;Michael Fowler

  • Deep Learning-Based Forecasting Approach in Smart Grids With Microclustering and Bidirectional LSTM Network

    Hamidreza Jahangir;Hanif Tayarani;Saleh Sadeghi Gougheri;Masoud Aliakbar Golkar

  • Cost-Benefit Analysis of V2G Implementation in Distribution Networks Considering PEVs Battery Degradation

    Ali Ahmadian;Mahdi Sedghi;Behnam Mohammadi-ivatloo;Ali Elkamel

  • Risk-Averse Optimal Bidding of Electric Vehicles and Energy Storage Aggregator in Day-Ahead Frequency Regulation Market

    Behzad Vatandoust;Ali Ahmadian;Masoud Aliakbar Golkar;Ali Elkamel

  • The Influence of Temperature, Pressure, Salinity, and Surfactant Concentration on the Interfacial Tension of the N-Octane-Water System

    T. Al-Sahhaf;A. Elkamel;A. Suttar Ahmed;A. R. Khan

  • Electricity demand estimation using an adaptive neuro-fuzzy network: A case study from the Ontario province – Canada

    Gholamreza Zahedi;Saeed Azizi;Alireza Bahadori;Ali Elkamel

  • Optimization Model for Energy Planning with CO2 Emission Considerations

    Haslenda Hashim;Peter Douglas;and Ali Elkamel;Eric Croiset

  • Optimal bidding strategy of a virtual power plant in day-ahead energy and frequency regulation markets: A deep learning-based approach

    Saleh Sadeghi;Hamidreza Jahangir;Behzad Vatandoust;Masoud Aliakbar Golkar

  • Mixed integer linear programing based approach for optimal planning and operation of a smart urban energy network to support the hydrogen economy

    Azadeh Maroufmashat;Azadeh Maroufmashat;Michael Fowler;Sourena Sattari Khavas;Ali Elkamel

  • A new correlation for predicting hydrate formation conditions for various gas mixtures and inhibitors

    Ahmed A. Elgibaly;Ali M. Elkamel

  • Measurement and prediction of ozone levels around a heavily industrialized area: a neural network approach

    A. Elkamel;S. Abdul-Wahab;W. Bouhamra;E. Alper

  • A multi-period optimization model for energy planning with CO2 emission consideration

    H. Mirzaesmaeeli;A. Elkamel;P.L. Douglas;E. Croiset

  • A Review on Plug-In Electric Vehicles: Introduction, Current Status, and Load Modeling Techniques

    Ali Ahmadian;Behnam Mohammadi-Ivatloo;Ali Elkamel

  • Optimal tuning of PID controllers for FOPTD, SOPTD and SOPTD with lead processes

    C.R. Madhuranthakam;A. Elkamel;H. Budman

Frequent Co-Authors

Eric Croiset
Eric Croiset University of Waterloo
Peter L. Douglas
Peter L. Douglas University of Waterloo
Michael Fowler
Michael Fowler University of Waterloo
Sohrab Zendehboudi
Sohrab Zendehboudi Memorial University of Newfoundland
Masoud Aliakbar Golkar
Masoud Aliakbar Golkar K.N.Toosi University of Technology
Ioannis Chatzis
Ioannis Chatzis University of Waterloo
Alireza Bahadori
Alireza Bahadori Southern Cross University
Luis A. Ricardez-Sandoval
Luis A. Ricardez-Sandoval University of Waterloo
Behnam Mohammadi-Ivatloo
Behnam Mohammadi-Ivatloo Lappeenranta University of Technology
Aiping Yu
Aiping Yu University of Waterloo

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