World's Best Scientists 2026 revealed!
B. John Oommen

B. John Oommen

D-Index & Metrics

Computer Science

D-Index
39
Citations
6351
World Ranking
9775
National Ranking
386

B. John Oommen 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 B. John Oommen 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: 449 publications — 90th percentile

90% of scientists in this discipline score the same or lower.

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

B. John Oommen 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 B. John Oommen 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.

Research.com Recognitions

  • 2006 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to fundamental and applied problems in syntactic and statistical pattern recognition.

Overview

B. John Oommen is a researcher affiliated with Carleton University in Canada. Their research contributions span several areas of computer science and engineering, with a focus on optimization, machine learning, and decision sciences.

Their work has been published extensively in various academic venues. Frequent publication venues include:

  • Pattern Analysis and Applications
  • IEEE Transactions on Neural Networks and Learning Systems
  • Evolving Systems
  • Pattern Recognition Letters
  • The Knowledge Engineering Review

Oommen's main fields of study cover:

  • Computer Science
  • Engineering
  • Decision Sciences

The subfields in which they concentrate include:

  • Computer Networks and Communications
  • Artificial Intelligence
  • Management Science and Operations Research
  • Electrical and Electronic Engineering
  • Radiology, Nuclear Medicine and Imaging

The primary research topics associated with their work are:

  • Optimization and Search Problems
  • Machine Learning and Algorithms
  • Auction Theory and Applications
  • Distributed systems and fault tolerance
  • AI in cancer detection
  • Semigroups and automata theory
  • Advanced Bandit Algorithms Research

Frequent co-authors in their research collaborations include:

  • Lei Jiao
  • Rebekka Olsson Omslandseter
  • Anis Yazidi
  • Tahira Ghani
  • Xuan Zhang

Selected recent papers by B. John Oommen include:

  • "Achieving Fair Load Balancing by Invoking a Learning Automata-Based Two-Time-Scale Separation Paradigm," 2020, IEEE Transactions on Neural Networks and Learning Systems
  • "User grouping and power allocation in NOMA systems: a novel semi-supervised reinforcement learning-based solution," 2022, Pattern Analysis and Applications
  • "The Hierarchical Discrete Pursuit Learning Automaton: A Novel Scheme With Fast Convergence and Epsilon-Optimality," 2022, IEEE Transactions on Neural Networks and Learning Systems
  • "Solving Two-Person Zero-Sum Stochastic Games With Incomplete Information Using Learning Automata With Artificial Barriers," 2021, IEEE Transactions on Neural Networks and Learning Systems
  • "Learning automata-based partitioning algorithms for stochastic grouping problems with non-equal partition sizes," 2023, Pattern Analysis and Applications

Oommen has received recognition including the 2006 Fellow award from the International Association for Pattern Recognition (IAPR) for contributions to syntactic and statistical pattern recognition.

Best Publications

  • Robot navigation in unknown terrains using learned visibility graphs. Part I: The disjoint convex obstacle case

    B. Oommen;S. Iyengar;N. Rao;R. Kashyap

  • Generalized pursuit learning schemes: new families of continuous and discretized learning automata

    Unknown

  • Discretized pursuit learning automata

    Unknown

  • Continuous and discretized pursuit learning schemes: various algorithms and their comparison

    Unknown

  • The Kohonen network incorporating explicit statistics and its application to the travelling salesman problem

    N. Aras;B. J. Oommen;I. K. Altinel

  • Deterministic Learning Automata Solutions to the Equipartitioning Problem

    Unknown

  • Learning Automata-Based Solutions to the Nonlinear Fractional Knapsack Problem With Applications to Optimal Resource Allocation

    Unknown

  • Graph Partitioning Using Learning Automata

    Unknown

  • A brief taxonomy and ranking of creative prototype reduction schemes

    S. W. Kim;B. John Oommen

  • Continuous Learning Automata Solutions to the Capacity Assignment Problem

    Unknown

  • Dynamic algorithms for the shortest path routing problem: learning automata-based solutions

    S. Misra;B.J. Oommen

  • Stochastic learning-based weak estimation of multinomial random variables and its applications to pattern recognition in non-stationary environments

    B. John Oommen;Luis Rueda

  • Discretized estimator learning automata

    Unknown

  • Random Early Detection for Congestion Avoidance in Wired Networks: A Discretized Pursuit Learning-Automata-Like Solution

    S. Misra;B.J. Oommen;S. Yanamandra;M.S. Obaidat

  • Stochastic searching on the line and its applications to parameter learning in nonlinear optimization

    Unknown

  • On terrain acquisition by a point robot amidst polyhedral obstacles

    N.S.V. Rao;S.S. Iyengar;B.J. Oommen;R.L. Kashyap

  • Recognition of Noisy Subsequences Using Constrained Edit Distances

    B. John Oommen

  • Ε-optimal Discretized Linear Reward-penalty Learning Automata

    Unknown

  • Spelling correction using probabilistic methods

    R. L. Kashyap;B. J. Oommen

  • GPSPA: a new adaptive algorithm for maintaining shortest path routing trees in stochastic networks

    Sudip Misra;B. John Oommen

  • List organizing strategies using stochastic move-to-front and stochastic move-to-rear operations

    B. John Oommen;E. R. Hansen

  • Routing Bandwidth-Guaranteed Paths in MPLS Traffic Engineering: A Multiple Race Track Learning Approach

    B.J. Oommen;S. Misra;O.-C. Granmo

  • Absorbing and Ergodic Discretized Two-Action Learning Automata

    Unknown

  • Service selection in stochastic environments: a learning-automaton based solution

    Anis Yazidi;Ole-Christoffer Granmo;B. John Oommen

  • Parameter learning from stochastic teachers and stochastic compulsive liars

    B.J. Oommen;G. Raghunath;B. Kuipers

  • Topology-oriented self-organizing maps: a survey

    César A. Astudillo;B. John Oommen

  • Cybernetics and Learning Automata

    B. John Oommen;Sudip Misra

  • Anomaly Detection in Dynamic Systems Using Weak Estimators

    Justin Zhan;B. John Oommen;Johanna Crisostomo

  • A cryptosystem for data security

    B. John Oommen;Luis G. Rueda

  • An efficient dynamic algorithm for maintaining all-pairs shortest paths in stochastic networks

    S. Misra;B.J. Oommen

  • An efficient compression scheme for data communication which uses a new family of self-organizing binary search trees

    Luis Rueda;B. John Oommen

Frequent Co-Authors

Sudip Misra
Sudip Misra Indian Institute of Technology Kharagpur
Rangasami L. Kashyap
Rangasami L. Kashyap Purdue University West Lafayette
Yuanwei Liu
Yuanwei Liu University of Hong Kong
Mohammad S. Obaidat
Mohammad S. Obaidat University of Jordan
S. Sitharama Iyengar
S. Sitharama Iyengar Florida International University
Benjamin Kuipers
Benjamin Kuipers University of Michigan–Ann Arbor
Nageswara S. V. Rao
Nageswara S. V. Rao Oak Ridge National Laboratory
Stan Matwin
Stan Matwin Dalhousie University

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