World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
5373
World Ranking
9871
National Ranking
104

Balaraman Ravindran 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 Balaraman Ravindran 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: 269 publications — 67th percentile

67% of scientists in this discipline score the same or lower.

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

Balaraman Ravindran 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 Balaraman Ravindran 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

Balaraman Ravindran is affiliated with the Indian Institute of Technology Madras in India. Their research work is primarily situated within the field of Computer Science, with a substantial focus on several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Management Science and Operations Research, and Electrical and Electronic Engineering.

The scientist has contributed notably to a variety of topics encompassing advanced and specialized areas such as:

  • Reinforcement Learning in Robotics
  • Advanced Graph Neural Networks
  • Complex Network Analysis Techniques
  • Bioinformatics and Genomic Networks
  • Machine Learning and Data Classification
  • Advanced Bandit Algorithms Research
  • Adversarial Robustness in Machine Learning

Their publication record includes papers in multiple venues, reflecting diverse research interests. Frequent publication venues include:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Frontiers in Artificial Intelligence
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • ACM Computing Surveys

Recent research contributions consist of:

  • A Survey of Adversarial Defenses and Robustness in NLP (2023, ACM Computing Surveys)
  • Hypergraph clustering by iteratively reweighted modularity maximization (2020, Applied Network Science)
  • Understanding Convolutions on Graphs (2021, Distill)
  • Scalable multi-product inventory control with lead time constraints using reinforcement learning (2021, Neural Computing and Applications)
  • EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness against Adversarial Attacks (2020, arXiv (Cornell University))

Balaraman Ravindran has worked with several frequent co-authors, including:

  • Srinivasan Parthasarathy
  • Sriraam Natarajan
  • Karthik Raman
  • Gokul Krishnan
  • Milind Tambe

Best Publications

  • An Autoencoder Approach to Learning Bilingual Word Representations

    Sarath Chandar A P;Stanislas Lauly;Hugo Larochelle;Mitesh Khapra

  • EPOpt: Learning Robust Neural Network Policies Using Model Ensembles

    Aravind Rajeswaran;Sarvjeet Ghotra;Balaraman Ravindran;Sergey Levine

  • Efficient computation of the shapley value for game-theoretic network centrality

    Tomasz P. Michalak;Karthik V. Aadithya;Piotr L. Szczepanski;Balaraman Ravindran

  • Latent dirichlet allocation based multi-document summarization

    Rachit Arora;Balaraman Ravindran

  • Diversity driven Attention Model for Query-based Abstractive Summarization

    Preksha Nema;Mitesh M. Khapra;Anirban Laha;Balaraman Ravindran

  • Correlational neural networks

    Sarath Chandar;Mitesh M. Khapra;Hugo Larochelle;Balaraman Ravindran

  • Accurate mobile robot localization in indoor environments using bluetooth

    Aswin N Raghavan;Harini Ananthapadmanaban;Manimaran S Sivamurugan;Balaraman Ravindran

  • Improving legal information retrieval using an ontological framework

    M. Saravanan;B. Ravindran;S. Raman

  • Model Minimization in Hierarchical Reinforcement Learning

    Balaraman Ravindran;Andrew G. Barto

  • SMDP homomorphisms: an algebraic approach to abstraction in semi-Markov decision processes

    Balaraman Ravindran;Andrew G. Barto

  • An algebraic approach to abstraction in reinforcement learning

    Balaraman Ravindran;Andrew G. Barto

  • Adaptive network intrusion detection system using a hybrid approach

    R Rangadurai Karthick;Vipul P. Hattiwale;Balaraman Ravindran

  • A tutorial survey of reinforcement learning

    S Sathiya Keerthi;B Ravindran

  • Overtaking Maneuvers in Simulated Highway Driving using Deep Reinforcement Learning

    Meha Kaushik;Vignesh Prasad;K Madhava Krishna;Balaraman Ravindran

  • COMMIT: A Scalable Approach to Mining Communication Motifs from Dynamic Networks

    Saket Gurukar;Sayan Ranu;Balaraman Ravindran

  • Latent Dirichlet Allocation and Singular Value Decomposition Based Multi-document Summarization

    R. Arora;B. Ravindran

  • Efficient computation of the shapley value for centrality in networks

    Karthik V. Aadithya;Balaraman Ravindran;Tomasz P. Michalak;Nicholas R. Jennings

  • Hierarchical activity recognition for dementia care using Markov Logic Network

    K. S. Gayathri;Susan Elias;Balaraman Ravindran

  • Towards Transparent and Explainable Attention Models

    Akash Kumar Mohankumar;Preksha Nema;Sharan Narasimhan;Mitesh M. Khapra

  • Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks

    Deepak Mittal;Shweta Bhardwaj;Mitesh M. Khapra;Balaraman Ravindran

  • Symmetries and Model Minimization in Markov Decision Processes

    B. Ravindran;A. G. Barto

Frequent Co-Authors

Milind Tambe
Milind Tambe Harvard University
Ahmed A. Moustafa
Ahmed A. Moustafa Bond University
Srinivasan Parthasarathy
Srinivasan Parthasarathy The Ohio State University
Anand Raghunathan
Anand Raghunathan Purdue University West Lafayette
Andrew G. Barto
Andrew G. Barto University of Massachusetts Amherst
Nicholas R. Jennings
Nicholas R. Jennings Loughborough University
Hugo Larochelle
Hugo Larochelle Google (United States)
Jeffrey Xu Yu
Jeffrey Xu Yu Chinese University of Hong Kong
Anupam Joshi
Anupam Joshi University of Maryland, Baltimore County
Sven Bergmann
Sven Bergmann Swiss Institute of Bioinformatics

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