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Srikumar Ramalingam

Srikumar Ramalingam

Srikumar Ramalingam 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 Srikumar Ramalingam 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+

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

Srikumar Ramalingam 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 Srikumar Ramalingam 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+

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

Overview

Srikumar Ramalingam is a researcher affiliated with Google in the United States, specializing in computer science with a primary focus on artificial intelligence and related subfields. They have contributed to a range of topics including machine learning, data classification, domain adaptation, few-shot learning, face and expression recognition, as well as algorithms and adversarial robustness in machine learning.

Their research spans multiple areas within computer science, concentrating on:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Information Systems and Management

The main topics addressed in their work include:

  • Machine Learning and Data Classification
  • Domain Adaptation and Few-Shot Learning
  • Face and Expression Recognition
  • Machine Learning and Algorithms
  • Algorithms and Data Compression
  • Adversarial Robustness in Machine Learning
  • Anomaly Detection Techniques and Applications

Their publication record features several papers primarily appearing in venues such as arXiv (Cornell University) and Zenodo (CERN European Organization for Nuclear Research). Notable recent publications are:

  • Less is more: Selecting informative and diverse subsets with balancing constraints, 2021, arXiv (Cornell University)
  • Kernelized Classification in Deep Networks, 2020, arXiv (Cornell University)
  • Balancing Robustness and Sensitivity using Feature Contrastive Learning, 2021, arXiv (Cornell University)
  • On Distributed Larger-Than-Memory Subset Selection With Pairwise Submodular Functions, 2024, arXiv (Cornell University)
  • CASENet: Deep Category-Aware Semantic Edge Detection, 2023, Zenodo (CERN European Organization for Nuclear Research)

Frequent collaboration is evident with several coauthors including Sanjiv Kumar, Daniel Gläsner, Sadeep Jayasumana, Kaushal Patel, and Raviteja Vemulapalli. Their joint work has contributed to advancing understanding in their respective fields.

Best Publications

  • Entropy rate superpixel segmentation

    Ming-Yu Liu;Oncel Tuzel;Srikumar Ramalingam;Rama Chellappa

  • CASENet: Deep Category-Aware Semantic Edge Detection

    Zhiding Yu;Chen Feng;Ming-Yu Liu;Srikumar Ramalingam

  • Point-plane SLAM for hand-held 3D sensors

    Yuichi Taguchi;Yong-Dian Jian;Srikumar Ramalingam;Chen Feng

  • Camera Models And Fundamental Concepts Used In Geometric Computer Vision

    Peter Sturm;Srikumar Ramalingam;Jean-Philippe Tardif;Simone Gasparini

  • A Generic Concept for Camera Calibration

    Peter F. Sturm;Srikumar Ramalingam

  • 3DRegNet: A Deep Neural Network for 3D Point Registration

    G. Dias Pais;Srikumar Ramalingam;Venu Madhav Govindu;Jacinto C. Nascimento

  • A theory of multi-layer flat refractive geometry

    Amit Agrawal;Srikumar Ramalingam;Yuichi Taguchi;Visesh Chari

  • Randomized trees for human pose detection

    G. Rogez;J. Rihan;S. Ramalingam;C. Orrite

  • Voting-based pose estimation for robotic assembly using a 3D sensor

    Changhyun Choi;Yuichi Taguchi;Oncel Tuzel;Ming-Yu Liu

  • Entropy-Rate Clustering: Cluster Analysis via Maximizing a Submodular Function Subject to a Matroid Constraint

    Ming-Yu Liu;Oncel Tuzel;Srikumar Ramalingam;Rama Chellappa

  • Digital Refocusing for Wide-Angle Images Using Axial-Cone Cameras

    Yuichi Taguchi;Amit K. Agrawal;Ashok N. Veeraraghavan;Srikumar Ramalingam

  • Exact inference in multi-label CRFs with higher order cliques

    S. Ramalingam;P. Kohli;K. Alahari;P. Torr

  • Bounding and Counting Linear Regions of Deep Neural Networks

    Thiago Serra;Christian Tjandraatmadja;Srikumar Ramalingam

  • Towards complete generic camera calibration

    Srikumar Ramalingam;P. Sturm;S.K. Lodha

  • SKYLINE2GPS: Localization in urban canyons using omni-skylines

    Srikumar Ramalingam;Sofien Bouaziz;Peter Sturm;Matthew Brand

  • Method for Calibrating Cameras with Non-Overlapping Views

    Yuichi Taguchi;Esra Cansizoglu;Srikumar Ramalingam;Yohei Miki

  • A generic structure-from-motion framework

    Srikumar Ramalingam;Suresh K. Lodha;Peter Sturm

  • Simultaneous Edge Alignment and Learning

    Zhiding Yu;Weiyang Liu;Yang Zou;Chen Feng

  • Pose estimation using both points and lines for geo-localization

    Srikumar Ramalingam;Sofien Bouaziz;Peter Sturm

  • Analytical forward projection for axial non-central dioptric and catadioptric cameras

    Amit Agrawal;Yuichi Taguchi;Srikumar Ramalingam

Frequent Co-Authors

Yuichi Taguchi
Yuichi Taguchi Mitsubishi Electric (United States)
Ming-Yu Liu
Ming-Yu Liu Nvidia (United States)
Oncel Tuzel
Oncel Tuzel Apple (United States)
Ashok Veeraraghavan
Ashok Veeraraghavan Rice University
Philip H. S. Torr
Philip H. S. Torr University of Oxford
Rama Chellappa
Rama Chellappa Johns Hopkins University
Gim Hee Lee
Gim Hee Lee National University of Singapore
Sanjiv Kumar
Sanjiv Kumar Google (United States)
Chris Russell
Chris Russell University of Oxford

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