World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
50
Citations
18912
World Ranking
3994
National Ranking
1153

Olexandr Isayev 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 Olexandr Isayev 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: 115 publications — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Olexandr Isayev 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 Olexandr Isayev 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: 50 D-Index — 59th percentile

59% of scientists in this discipline score the same or lower.

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

Overview

Olexandr Isayev is affiliated with the University of North Carolina at Chapel Hill in the United States. Their research spans multiple domains including Materials Science, Computer Science, and Biochemistry, Genetics, and Molecular Biology. The primary subfields of study encompass Materials Chemistry, Computational Theory and Mathematics, Molecular Biology, Physical and Theoretical Chemistry, and Electrical and Electronic Engineering.

The main topics covered by their work include Computational Drug Discovery Methods, Machine Learning in Materials Science, Protein Structure and Dynamics, Various Chemistry Research Topics, Chemical Synthesis and Analysis, Catalysis and Oxidation Reactions, and RNA and protein synthesis mechanisms.

Isayev has contributed to several scientific papers across respected journals. Notable recent publications include:

  • "QSAR without borders" (2020) in Chemical Society Reviews
  • "Best practices in machine learning for chemistry" (2021) in Nature Chemistry
  • "Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and Halogens" (2020) in Journal of Chemical Theory and Computation
  • "TorchANI: A Free and Open Source PyTorch-Based Deep Learning Implementation of the ANI Neural Network Potentials" (2020) in Journal of Chemical Information and Modeling
  • "Generative Models as an Emerging Paradigm in the Chemical Sciences" (2023) in Journal of the American Chemical Society

Their frequent collaborators include Adrián E. Roitberg, R.I. Zubatyuk, Filipp Gusev, Artem Cherkasov, and Justin S. Smith. Across their career, Isayev has published extensively in venues such as UNC Libraries, Journal of Chemical Information and Modeling, arXiv (Cornell University), Chemical Science, and Journal of Chemical Theory and Computation.

Isayev's work involves integrating machine learning techniques with chemistry and materials science to advance computational models for molecular simulations and drug discovery. This interdisciplinary approach reflects a combination of chemical theory, computer science methodologies, and biological sciences.

Best Publications

  • Machine learning for molecular and materials science.

    Keith T. Butler;Daniel W. Davies;Hugh Cartwright;Olexandr Isayev

  • ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost

    Justin S Smith;Olexandr Isayev;Adrian E Roitberg

  • Deep reinforcement learning for de novo drug design

    Mariya Popova;Mariya Popova;Mariya Popova;Olexandr Isayev;Alexander E Tropsha

  • Less is more: Sampling chemical space with active learning

    Justin Steven Smith;Benjamin Tyler Nebgen;Nicholas Edward Lubbers;Olexandr Isayev

  • QSAR without borders

    Eugene N. Muratov;Eugene N. Muratov;Jürgen Bajorath;Robert P. Sheridan;Igor V. Tetko

  • Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning.

    Justin S. Smith;Justin S. Smith;Benjamin T. Nebgen;Roman Zubatyuk;Roman Zubatyuk;Nicholas Lubbers

  • Universal fragment descriptors for predicting properties of inorganic crystals

    Olexandr Isayev;Corey Oses;Cormac Toher;Eric Gossett

  • Best practices in machine learning for chemistry.

    Nongnuch Artrith;Keith T. Butler;François Xavier Coudert;Seungwu Han

  • Materials Cartography: Representing and Mining Materials Space Using Structural and Electronic Fingerprints

    Olexandr Isayev;Denis Fourches;Eugene N. Muratov;Corey Oses

  • Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and Halogens.

    Christian Devereux;Justin S. Smith;Kate K. Davis;Kipton Barros

  • ANI-1, A data set of 20 million calculated off-equilibrium conformations for organic molecules

    Justin S. Smith;Olexandr Isayev;Adrian E. Roitberg

  • TorchANI: A Free and Open Source PyTorch-Based Deep Learning Implementation of the ANI Neural Network Potentials.

    Xiang Gao;Farhad Ramezanghorbani;Olexandr Isayev;Justin S. Smith

  • Accurate and transferable multitask prediction of chemical properties with an atoms-in-molecules neural network.

    Roman Zubatyuk;Roman Zubatyuk;Roman Zubatyuk;Justin S. Smith;Jerzy Leszczynski;Olexandr Isayev

  • The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules

    Justin S. Smith;Roman Zubatyuk;Roman Zubatyuk;Benjamin Nebgen;Nicholas Lubbers

  • Materials Cartography: Representing and Mining Material Space Using Structural and Electronic Fingerprints

    Olexandr Isayev;Denis Fourches;Eugene N. Muratov;Corey Oses

  • A critical overview of computational approaches employed for COVID-19 drug discovery.

    Eugene N Muratov;Rommie Amaro;Carolina H Andrade;Nathan Brown

  • Ab initio molecular dynamics study on the initial chemical events in nitramines: thermal decomposition of CL-20.

    Olexandr Isayev;Leonid Gorb;Mo Qasim;Jerzy Leszczynski

  • Development of Multimodal Machine Learning Potentials: Toward a Physics-Aware Artificial Intelligence.

    Tetiana Zubatiuk;Olexandr Isayev

  • Machine-Learning-Guided Discovery of 19F MRI Agents Enabled by Automated Copolymer Synthesis.

    Marcus Reis;Filipp Gusev;Nicholas G Taylor;Sang Hun Chung

  • Discovering a Transferable Charge Assignment Model Using Machine Learning.

    Andrew E Sifain;Andrew E Sifain;Nicholas Lubbers;Benjamin T Nebgen;Justin S Smith;Justin S Smith

  • Harnessing the Power of Smart and Connected Health to Tackle COVID-19: IoT, AI, Robotics, and Blockchain for a Better World

    Farshad Firouzi;Bahar Farahani;Mahmoud Daneshmand;Kathy Grise

  • Effect of solvation on the vertical ionization energy of thymine: from microhydration to bulk.

    Debashree Ghosh;Olexandr Isayev;Lyudmila V. Slipchenko;Anna I. Krylov

  • Transferable Dynamic Molecular Charge Assignment Using Deep Neural Networks.

    Benjamin Nebgen;Nicholas Lubbers;Justin S. Smith;Justin S. Smith;Andrew E. Sifain;Andrew E. Sifain

  • MolecularRNN: Generating realistic molecular graphs with optimized properties.

    Mariya Popova;Mykhailo Shvets;Junier Oliva;Olexandr Isayev

Frequent Co-Authors

Adrian E. Roitberg
Adrian E. Roitberg University of Florida
Jerzy Leszczynski
Jerzy Leszczynski Jackson State University
Leonid Gorb
Leonid Gorb Jackson State University
Alexander Tropsha
Alexander Tropsha University of North Carolina at Chapel Hill
David A. Winkler
David A. Winkler La Trobe University
Stefano Curtarolo
Stefano Curtarolo Duke University
Sergei Tretiak
Sergei Tretiak Los Alamos National Laboratory
Joseph G. Shapter
Joseph G. Shapter University of Queensland
Eugene N. Muratov
Eugene N. Muratov University of North Carolina at Chapel Hill
Aron Walsh
Aron Walsh Imperial College London

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:

Best Scientists Citing Olexandr Isayev

Trending Scientists

Recently Published Articles