World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
42
Citations
7992
World Ranking
6487
National Ranking
1778

Abhinav Saxena 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 Abhinav Saxena 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: 147 publications — 25th percentile

25% of scientists in this discipline score the same or lower.

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

Abhinav Saxena 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 Abhinav Saxena 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: 42 D-Index — 35th percentile

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

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

Overview

Abhinav Saxena is affiliated with General Electric in the United States and has contributed extensively to the field of engineering, with a notable focus on prognostics and health management. Their research spans various subfields including control and systems engineering, artificial intelligence, aerospace engineering, industrial and manufacturing engineering, and biomedical engineering.

The scientist's work covers key topics such as fault detection and control systems, machine fault diagnosis techniques, cardiac arrest and resuscitation, mechanical circulatory support devices, oil and gas production techniques, digital transformation in industry, and risk and safety analysis.

Frequent collaborators in their research include Jamie Coble, Michael Muhlheim, Pradeep Ramuhalli, Alex Huning, and Askin Guler Yigitoglu. Their most active publication venues comprise the Annual Conference of the PHM Society, the International Journal of Prognostics and Health Management, the Journal of the American College of Cardiology, the 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), and OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).

Some recent papers authored or co-authored by Abhinav Saxena include:

  • Metrics for Offline Evaluation of Prognostic Performance, 2021, International Journal of Prognostics and Health Management
  • Performance Benchmarking and Analysis of Prognostic Methods for CMAPSS Datasets, 2020, International Journal of Prognostics and Health Management
  • Recent advances in materials science: a reinforced approach toward challenges against COVID-19, 2021, Emergent Materials
  • Human Following Robot, 2021, 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)
  • Deep Learning Approach to Within-Bank Fault Detection and Diagnostics of Fine Motion Control Rod Drives, 2024, International Journal of Prognostics and Health Management

Best Publications

  • Damage propagation modeling for aircraft engine run-to-failure simulation

    A. Saxena;K. Goebel;D. Simon;N. Eklund

  • Prognostics in Battery Health Management

    K. Goebel;B. Saha;A. Saxena;J. Celaya

  • Metrics for evaluating performance of prognostic techniques

    A. Saxena;J. Celaya;E. Balaban;K. Goebel

  • Metrics for Offline Evaluation of Prognostic Performance

    Abhinav Saxena;Jose Celaya;Bhaskar Saha;Sankalita Saha

  • Evolving an artificial neural network classifier for condition monitoring of rotating mechanical systems

    Abhinav Saxena;Ashraf Saad

  • An Adaptive Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-ion Batteries

    Jie Liu;Abhinav Saxena;Kai Goebel;Bhaskar Saha

  • Modeling, Detection, and Disambiguation of Sensor Faults for Aerospace Applications

    E. Balaban;A. Saxena;P. Bansal;K.F. Goebel

  • On Applying the Prognostic Performance Metrics

    Abhinav Saxena;Jose Celaya;Bhaskar Saha;Sankalita Saha

  • A diagnostic approach for electro-mechanical actuators in aerospace systems

    Edward Balaban;Prasun Bansal;Paul Stoelting;Abhinav Saxena

  • Evaluating algorithm performance metrics tailored for prognostics

    Abhinav Saxena;Jose Celaya;Bhaskar Saha;Sankalita Saha

  • Performance Benchmarking and Analysis of Prognostic Methods for CMAPSS Datasets.

    Emmanuel Ramasso;Abhinav Saxena

  • In-situ fatigue life prognosis for composite laminates based on stiffness degradation

    Tishun Peng;Yongming Liu;Abhinav Saxena;Kai Goebel

  • Prognostics of Power Mosfets Under Thermal Stress Accelerated Aging Using Data-Driven and Model-Based Methodologies

    José R. Celaya;Abhinav Saxena;Sankalita Saha;Kai F. Goebel

  • Prognostics approach for power MOSFET under thermal-stress aging

    Jose R. Celaya;Abhinav Saxena;Chetan S. Kulkarni;Sankalita Saha

  • A multi-feature integration method for fatigue crack detection and crack length estimation in riveted lap joints using Lamb waves

    Jingjing He;Xuefei Guan;Tishun Peng;Yongming Liu

  • Towards Prognostics of Power MOSFETs: Accelerated Aging and Precursors of Failure

    Jose R Celaya;Abhinav Saxena;Philip Wysocki;Sankalita Saha

  • A knowledge-based system approach for sensor fault modeling, detection and mitigation

    Jonny Carlos da Silva;Abhinav Saxena;Edward Balaban;Kai Goebel

  • Prognostic Health-Management System Development for Electromechanical Actuators

    Edward Balaban;Abhinav Saxena;Sriram Narasimhan;Indranil Roychoudhury

  • Condition-based prediction of time-dependent reliability in composites

    Juan Chiachío;Manuel Chiachío;Shankar Sankararaman;Abhinav Saxena

  • Rolling element bearing feature extraction and anomaly detection based on vibration monitoring

    Bin Zhang;G. Georgoulas;M. Orchard;A. Saxena

  • An Efficient Deterministic Approach to Model-based Prediction Uncertainty Estimation

    Matthew J. Daigle;Abhinav Saxena;Kai Goebel

Frequent Co-Authors

Kai Goebel
Kai Goebel Palo Alto Research Center
George Vachtsevanos
George Vachtsevanos Georgia Institute of Technology
Yongming Liu
Yongming Liu Arizona State University
Marcos E. Orchard
Marcos E. Orchard University of Chile
Marco Giglio
Marco Giglio Polytechnic University of Milan
David He
David He University of Illinois at Chicago
Jie Liu
Jie Liu Hunan University
Fu-Kuo Chang
Fu-Kuo Chang Stanford University
Deepak Khare
Deepak Khare Indian Institute of Technology Roorkee
Magnus Egerstedt
Magnus Egerstedt University of North Carolina at Chapel Hill

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