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Vijayalakshmi Srinivasan

Vijayalakshmi Srinivasan

Vijayalakshmi Srinivasan 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 Vijayalakshmi Srinivasan 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.

Vijayalakshmi Srinivasan 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 Vijayalakshmi Srinivasan 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

Vijayalakshmi Srinivasan is affiliated with IBM in the United States and has contributed to research spanning both medicine and computer science. Their work intersects several specialized fields, primarily within obstetrics and gynecology as well as radiology, nuclear medicine, and imaging.

The research output of Vijayalakshmi Srinivasan includes studies focused on pregnancy-related medical conditions and advanced computational methods. Their publications cover topics such as pregnancy and preeclampsia studies, birth, development, and health, along with applications of advanced neural networks and artificial intelligence techniques.

Recent papers authored or coauthored by Vijayalakshmi Srinivasan include:

  • Multiscale and multimodal imaging of utero-placental anatomy and function in pregnancy, 2021, Placenta
  • ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training, 2021, arXiv (Cornell University)

Other prominent publications associated with their frequent coauthors reflect interdisciplinary collaboration in medicine and computer science:

  • Three-dimensional visualisation of the feto-placental vasculature in humans and rodents, 2021, Placenta
  • Feto-placental vascular structure and in silico haemodynamics: Of mice, rats, and human, 2024, Placenta

Frequent coauthors collaborating with Vijayalakshmi Srinivasan include Alys R. Clark, Swagath Venkataramani, Joanna L. James, Yutthapong Tongpob, and Caitlin S. Wyrwoll. These collaborations have contributed to multiple publications in venues such as Placenta and arXiv.

The primary publication venues where Vijayalakshmi Srinivasan has contributed are:

  • Placenta
  • arXiv (Cornell University)
  • Tropical Journal of Pathology and Microbiology
  • IEEE Micro

Their main fields of study encompass:

  • Medicine
  • Computer Science

Within these, the subfields they have addressed include:

  • Obstetrics and Gynecology
  • Radiology, Nuclear Medicine and Imaging
  • Pediatrics, Perinatology and Child Health
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

Themes prevalent in their research are:

  • Pregnancy and preeclampsia studies
  • Birth, Development, and Health
  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • COVID-19 diagnosis using AI
  • Reproductive System and Pregnancy
  • Gestational Diabetes Research and Management

Best Publications

  • Scalable high performance main memory system using phase-change memory technology

    Moinuddin K. Qureshi;Vijayalakshmi Srinivasan;Jude A. Rivers

  • Enhancing lifetime and security of PCM-based main memory with start-gap wear leveling

    Moinuddin K. Qureshi;John Karidis;Michele Franceschini;Vijayalakshmi Srinivasan

  • PACT: Parameterized Clipping Activation for Quantized Neural Networks

    Jungwook Choi;Zhuo Wang;Swagath Venkataramani;Pierce I.Jen Chuang

  • An Overview of the BlueGene/L Supercomputer

    N.R. Adiga;G. Almasi;G.S. Almasi;Y. Aridor

  • Microarchitectural techniques for power gating of execution units

    Zhigang Hu;Alper Buyuktosunoglu;Viji Srinivasan;Victor Zyuban

  • NDC: Analyzing the impact of 3D-stacked memory+logic devices on MapReduce workloads

    Seth H. Pugsley;Jeffrey Jestes;Huihui Zhang;Rajeev Balasubramonian

  • SAFER: Stuck-At-Fault Error Recovery for Memories

    Nak Hee Seong;Dong Hyuk Woo;Vijayalakshmi Srinivasan;Jude A. Rivers

  • A tagless coherence directory

    Jason Zebchuk;Moinuddin K. Qureshi;Vijayalakshmi Srinivasan;Andreas Moshovos

  • Two dimensional branch history table prefetching mechanism

    Philip Emma;Klaus Getzlaff;Allan Hartstein;Thomas Pflueger

  • Optimizing pipelines for power and performance

    Viji Srinivasan;David Brooks;Michael Gschwind;Pradip Bose

  • New methodology for early-stage, microarchitecture-level power-performance analysis of microprocessors

    D. Brooks;P. Bose;V. Srinivasan;M. K. Gschwind

  • Efficient scrub mechanisms for error-prone emerging memories

    Manu Awasthi;Manjunath Shevgoor;Kshitij Sudan;Bipin Rajendran

  • Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks

    Xiao Sun;Jungwook Choi;Chia Yu Chen;Naigang Wang

  • A Scalable Multi- TeraOPS Deep Learning Processor Core for AI Trainina and Inference

    Bruce Fleischer;Sunil Shukla;Matthew Ziegler;Joel Silberman

  • Accurate and Efficient 2-bit Quantized Neural Networks

    Jungwook Choi;Swagath Venkataramani;Vijayalakshmi Srinivasan;Kailash Gopalakrishnan

  • Co-designing accelerators and SoC interfaces using gem5-aladdin

    Yakun Sophia Shao;Sam Likun Xi;Vijayalakshmi Srinivasan;Gu-Yeon Wei

  • Geometric tolerancing: 2. conditional tolerances

    V. Srinivasan;R. Jayaraman

  • Approximate computing: Challenges and opportunities

    Ankur Agrawal;Jungwook Choi;Kailash Gopalakrishnan;Suyog Gupta

  • Programming with relaxed synchronization

    Lakshminarayanan Renganarayana;Vijayalakshmi Srinivasan;Ravi Nair;Daniel Prener

  • Ultra-Low Precision 4-bit Training of Deep Neural Networks

    Xiao Sun;Naigang Wang;Chia-Yu Chen;Jiamin Ni

Frequent Co-Authors

Swagath Venkataramani
Swagath Venkataramani IBM (United States)
Leland Chang
Leland Chang IBM Research - Thomas J. Watson Research Center
Alper Buyuktosunoglu
Alper Buyuktosunoglu IBM (United States)
Michael A. Guillorn
Michael A. Guillorn IBM (United States)
Moinuddin K. Qureshi
Moinuddin K. Qureshi Georgia Institute of Technology
Pradip Bose
Pradip Bose IBM (United States)
Andreas Moshovos
Andreas Moshovos University of Toronto
Luis Ceze
Luis Ceze University of Washington
Wei Wang
Wei Wang University of California, Los Angeles
David Brooks
David Brooks Harvard University

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