World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
4822
World Ranking
9899
National Ranking
4158

Kumara Sastry 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 Kumara Sastry 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: 112 publications — 12th percentile

12% of scientists in this discipline score the same or lower.

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

Kumara Sastry 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 Kumara Sastry 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: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

Kumara Sastry is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their research primarily spans the field of engineering, with a specific focus on electrical and electronic engineering, artificial intelligence, biomedical engineering, statistical and nonlinear physics, and computational mechanics.

Their work covers a range of topics that include:

  • Advancements in photolithography techniques
  • Model reduction and neural networks
  • Advanced numerical methods in computational mathematics
  • Welding techniques and residual stresses
  • Industrial vision systems and defect detection
  • Electron and X-ray spectroscopy techniques
  • Machine learning and algorithms

Kumara Sastry has published research in several venues, with frequent contributions to:

  • arXiv (Cornell University)
  • Proceedings of the 59th ACM/IEEE Design Automation Conference
  • International Journal of Development Research

Some of the recent papers by Kumara Sastry include:

  • Generic lithography modeling with dual-band optics-inspired neural networks, 2022, Proceedings of the 59th ACM/IEEE Design Automation Conference
  • Large Scale Mask Optimization Via Convolutional Fourier Neural Operator and Litho-Guided Self Training, 2022, arXiv (Cornell University)
  • An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design, 2022, arXiv (Cornell University)
  • Generic Lithography Modeling with Dual-band Optics-Inspired Neural Networks, 2022, arXiv (Cornell University)
  • Classification of colon cancer by using cnn and capsule neural network, 2023, International Journal of Development Research

Kumara Sastry frequently collaborates with several co-authors, many of whom have co-authored four publications with them each. The identified frequent co-authors are:

  • Zongyi Li
  • Saumyadip Mukhopadhyay
  • Anima Anandkumar
  • Brucek Khailany
  • Haoxing Ren

Best Publications

  • Scalable Optimization via Probabilistic Modeling

    Martin Pelikan;Kumara Sastry;Erick Cantu-Paz

  • Scalable optimization via probabilistic modeling : from algorithms to applications

    Martin Pelikan;Kumara Sastry;Erick Cantú-Paz

  • Estimation of heat transfer parameters in a trickle-bed reactor using differential evolution and orthogonal collocation

    B.V Babu;K.K.N Sastry

  • Linkage Learning via Probabilistic Modeling in the Extended Compact Genetic Algorithm (ECGA)

    Georges R. Harik;Fernando G. Lobo;Kumara Sastry

  • Evaluation-Relaxation Schemes for Genetic and Evolutionary Algorithms

    Kumara Sastry;Martin Pelikan;Prasanna Parthasarathy;Ravi Srivastava

  • Scalability of the Bayesian optimization algorithm

    Martin Pelikan;Kumara Sastry;David E. Goldberg

  • Probabilistic Model Building and Competent Genetic Programming

    Kumara Sastry;David E. Goldberg

  • Combating user fatigue in iGAs: partial ordering, support vector machines, and synthetic fitness

    Xavier Llorà;Kumara Sastry;David E. Goldberg;Abhimanyu Gupta

  • Multiobjective hBOA, clustering, and scalability

    Martin Pelikan;Kumara Sastry;David E. Goldberg

  • Using previous models to bias structural learning in the hierarchical boa

    M. W. Hauschild;M. Pelikan;K. Sastry;D. E. Goldberg

  • Don't evaluate, inherit

    Kumara Sastry;David E. Goldberg;Martin Pelikan

  • Dependency structure matrix, genetic algorithms, and effective recombination

    Tian-Li Yu;David E. Goldberg;Kumara Sastry;Claudio F. Lima

  • Bayesian optimization algorithm, decision graphs, and Occam's razor

    Martin Pelikan;David E. Goldberg;Kumara Sastry

  • Fitness inheritance in multi-objective optimization

    Jian-Hung Chen;David E. Goldberg;Shinn-Ying Ho;Kumara Sastry

  • A practical schema theorem for genetic algorithm design and tuning

    David E. Goldberg;Kumara Sastry

  • Fitness Inheritance in the Bayesian Optimization Algorithm

    Martin Pelikan;Kumara Sastry

  • Designing Competent Mutation Operators Via Probabilistic Model Building of Neighborhoods

    Kumara Sastry;David E. Goldberg

  • Tournament selection: stable fitness pressure in XCS

    Martin V. Butz;Kumara Sastry;David E. Goldberg

  • On the supply of building blocks

    David E. Goldberg;Kumara Sastry;Thomas Latoza

  • Multiobjective Estimation of Distribution Algorithms

    Martin Pelikan;Kumara Sastry;David E. Goldberg

  • Genetic and Evolutionary Computation Conference 2008 : GECCO 2008

    Maarten Keijzer;Giuliano Antoniol.;Clare Bates Congdon;Kalyanmoy Deb

Frequent Co-Authors

David E. Goldberg
David E. Goldberg University of Illinois at Urbana-Champaign
Martin Pelikan
Martin Pelikan University of Missouri
Duane D. Johnson
Duane D. Johnson Iowa State University
Pier Luca Lanzi
Pier Luca Lanzi Polytechnic University of Milan
Martin V. Butz
Martin V. Butz University of Tübingen
Hussein A. Abbass
Hussein A. Abbass University of New South Wales
Todd J. Martínez
Todd J. Martínez Stanford University
Pascal Bellon
Pascal Bellon University of Illinois at Urbana-Champaign
Erick Cantú-Paz
Erick Cantú-Paz Amazon (United States)

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