World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
84
Citations
31297
World Ranking
845
National Ranking
462

Alok Choudhary publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Alok Choudhary sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 694 publications — 98th percentile

98% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Alok Choudhary D-index placement in Computer Science in 2026

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

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 84 D-Index — 94th percentile

94% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

  • 2009 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2009 - ACM Fellow For contributions to HPC, storage and parallel I/O.
  • 2005 - IEEE Fellow For contributions to high performance computing systems.

Overview

Alok Choudhary is affiliated with Northwestern University in the United States. Their research spans multiple fields including materials science, computer science, and engineering, with a focus on subfields such as materials chemistry, mechanical engineering, computer networks and communications, surfaces, coatings and films, and computer vision and pattern recognition.

Their work covers several main topics, notably machine learning in materials science, X-ray diffraction in crystallography, electron and X-ray spectroscopy techniques, advanced data storage technologies, computational drug discovery methods, distributed and parallel computing systems, and systemic sclerosis and related diseases.

Frequent co-authors in their publications include Ankit Agrawal, Wei-keng Liao, Vishu Gupta, Yuwei Mao, and Kamal Choudhary.

Alok Choudhary's research has appeared in a variety of publication venues. These include Scientific Reports, arXiv (Cornell University), SSRN Electronic Journal, npj Computational Materials, and Integrating Materials and Manufacturing Innovation.

Some of their recent papers are:

  • Structure-aware graph neural network based deep transfer learning framework for enhanced predictive analytics on diverse materials datasets, 2024, npj Computational Materials
  • Recent advances and applications of deep learning methods in materials science, 2022, npj Computational Materials
  • Moving closer to experimental level materials property prediction using AI, 2022, Scientific Reports
  • Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data, 2021, Nature Communications
  • Enabling deeper learning on big data for materials informatics applications, 2021, Scientific Reports

Alok Choudhary has published a book titled Artificial Intelligence for Science (2022) through World Scientific.

The scientist has been recognized with several awards including Fellow of the IEEE (2005) for contributions to high performance computing systems, ACM Fellow (2009) for contributions to HPC, storage and parallel I/O, and Fellow of the American Association for the Advancement of Science (AAAS) in 2009.

Best Publications

  • A general-purpose machine learning framework for predicting properties of inorganic materials

    Logan Ward;Ankit Agrawal;Alok Nidhi Choudhary;Christopher M Wolverton

  • Perspective: Materials informatics and big data: Realization of the “fourth paradigm” of science in materials science

    Ankit Agrawal;Alok Choudhary

  • Deep Convolutional Neural Networks with transfer learning for computer vision-based data-driven pavement distress detection

    Kasthurirangan Gopalakrishnan;Siddhartha K. Khaitan;Alok Choudhary;Ankit Agrawal

  • Recent Advances and Applications of Deep Learning Methods in Materials Science

    Kamal Choudhary;Brian DeCost;Chi Chen;Anubhav Jain

  • The International Exascale Software Project roadmap

    Jack Dongarra;Pete Beckman;Terry Moore;Patrick Aerts

  • A two-phase algorithm for fast discovery of high utility itemsets

    Ying Liu;Wei-keng Liao;Alok Choudhary

  • Combinatorial screening for new materials in unconstrained composition space with machine learning

    Bryce Meredig;Amit K Agrawal;Scott Kirklin;James E. Saal

  • Terascale direct numerical simulations of turbulent combustion using S3D

    J. H. Chen;A. Choudhary;B. De Supinski;M. Devries

  • A fast high utility itemsets mining algorithm

    Ying Liu;Wei-keng Liao;Alok Choudhary

  • Firefly: illuminating future network-on-chip with nanophotonics

    Yan Pan;Prabhat Kumar;John Kim;Gokhan Memik

  • Parallel netCDF: A High-Performance Scientific I/O Interface

    Jianwei Li;Wei-keng Liao;Alok Choudhary;Robert Ross

  • ElemNet: Deep Learning the Chemistry of Materials From Only Elemental Composition.

    Dipendra Jha;Logan Ward;Arindam Paul;Wei-Keng Liao

  • Twitter Trending Topic Classification

    Kathy Lee;Diana Palsetia;Ramanathan Narayanan;Md. Mostofa Ali Patwary

  • Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations

    Logan Ward;Ruoqian Liu;Amar Krishna;Vinay I. Hegde

  • Improved parallel I/O via a two-phase run-time access strategy

    Juan Miguel del Rosario;Rajesh Bordawekar;Alok Choudhary

  • Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets

    Zijiang Yang;Yuksel C. Yabansu;Reda Al-Bahrani;Wei keng Liao

  • An Exploration of Parameter Redundancy in Deep Networks with Circulant Projections

    Yu Cheng;Yu Cheng;Felix X. Yu;Rogerio S. Feris;Sanjiv Kumar

  • Sentiment Analysis of Conditional Sentences

    Ramanathan Narayanan;Bing Liu;Alok Choudhary

  • Towards Online Spam Filtering in Social Networks

    Hongyu Gao;Yan Chen;Kathy Lee;Diana Palsetia

  • Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning

    Dipendra Jha;Kamal Choudhary;Francesca Tavazza;Wei keng Liao

  • Terascale direct numerical simulations of turbulent combustion using S3D.

    Ramanan Sankaran;J. Mellor-Crummy;M. DeVries;Chun Sang Yoo

Frequent Co-Authors

Wei-keng Liao
Wei-keng Liao Northwestern University
Ankit Agrawal
Ankit Agrawal Northwestern University
Mahmut Kandemir
Mahmut Kandemir Pennsylvania State University
Gokhan Memik
Gokhan Memik Northwestern University
J. Ramanujam
J. Ramanujam Louisiana State University
Yu Cheng
Yu Cheng Microsoft (United States)
Rajeev Thakur
Rajeev Thakur Argonne National Laboratory
Prithviraj Banerjee
Prithviraj Banerjee Ansys (United States)
Geoffrey C. Fox
Geoffrey C. Fox University of Virginia
Rajesh Bordawekar
Rajesh Bordawekar IBM (United States)

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