World's Best Scientists 2026 revealed!
Pulkit Agrawal

Pulkit Agrawal

D-Index & Metrics

Computer Science

D-Index
30
Citations
8881
World Ranking
13835
National Ranking
5497

Pulkit Agrawal 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 Pulkit Agrawal 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 83 publications — 4th percentile

4% of scientists in this discipline score the same or lower.

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

Pulkit Agrawal 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 Pulkit Agrawal sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 30 D-Index — 3rd percentile

3% of scientists in this discipline score the same or lower.

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

Overview

Pulkit Agrawal is a researcher affiliated with MIT in the United States. Their primary fields of study are Computer Science and Engineering, with a focus on several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Biomedical Engineering, and Aerospace Engineering.

The researcher's main topics of work revolve around robotics and machine learning disciplines. These include Robot Manipulation and Learning, Reinforcement Learning in Robotics, Domain Adaptation and Few-Shot Learning, Robotics and Sensor-Based Localization, Multimodal Machine Learning Applications, Human Pose and Action Recognition, and Robotic Path Planning Algorithms.

Among their recent publications are:

  • "Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation," 2022, 2022 International Conference on Robotics and Automation (ICRA)
  • "Stubborn: A Strong Baseline for Indoor Object Navigation," 2022, 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • "Is Conditional Generative Modeling all you need for Decision-Making?," 2022, arXiv (Cornell University)
  • "3D Neural Scene Representations for Visuomotor Control," 2021, arXiv (Cornell University)
  • "AdaScale SGD: A User-Friendly Algorithm for Distributed Training," 2020, arXiv (Cornell University)

Frequently publishing venues include:

  • arXiv (Cornell University)
  • 2022 International Conference on Robotics and Automation (ICRA)
  • 2021 IEEE International Conference on Big Data (Big Data)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Collaborations with other researchers have been a significant part of Pulkit Agrawal's work. Frequent coauthors include Zhang-Wei Hong, Anthony Simeonov, Abhishek Gupta, Anurag Ajay, and Gabriel B. Margolis.

Best Publications

  • Curiosity-driven Exploration by Self-supervised Prediction

    Deepak Pathak;Pulkit Agrawal;Alexei A. Efros;Trevor Darrell

  • Fully Automated Echocardiogram Interpretation in Clinical Practice

    Jeffrey Zhang;Sravani Gajjala;Pulkit Agrawal;Geoffrey H. Tison

  • Human Pose Estimation with Iterative Error Feedback

    Joao Carreira;Pulkit Agrawal;Katerina Fragkiadaki;Jitendra Malik

  • Learning to See by Moving

    Pulkit Agrawal;Joao Carreira;Jitendra Malik

  • Analyzing the Performance of Multilayer Neural Networks for Object Recognition

    Pulkit Agrawal;Ross B. Girshick;Jitendra Malik

  • What makes ImageNet good for transfer learning

    Minyoung Huh;Pulkit Agrawal;Alexei A. Efros

  • Learning to poke by poking: experiential learning of intuitive physics

    Pulkit Agrawal;Ashvin Nair;Pieter Abbeel;Jitendra Malik

  • Combining self-supervised learning and imitation for vision-based rope manipulation

    Ashvin Nair;Dian Chen;Pulkit Agrawal;Phillip Isola

  • Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation

    Unknown

  • Zero-Shot Visual Imitation

    Deepak Pathak;Parsa Mahmoudieh;Guanghao Luo;Pulkit Agrawal

  • Learning Visual Predictive Models of Physics for Playing Billiards

    Katerina Fragkiadaki;Pulkit Agrawal;Sergey Levine;Jitendra Malik

  • Zero-Shot Visual Imitation

    Deepak Pathak;Parsa Mahmoudieh;Guanghao Luo;Pulkit Agrawal

  • Investigating Human Priors for Playing Video Games

    Rachit Dubey;Pulkit Agrawal;Deepak Pathak;Thomas L. Griffiths

  • Is Conditional Generative Modeling all you need for Decision-Making?

    Unknown

  • Pixels to Voxels: Modeling Visual Representation in the Human Brain

    Pulkit Agrawal;Dustin Stansbury;Jitendra Malik;Jack L. Gallant

  • Generic 3D Representation via Pose Estimation and Matching

    Amir Roshan Zamir;Tilman Wekel;Pulkit Agrawal;Colin Wei

  • What will Happen Next? Forecasting Player Moves in Sports Videos

    Panna Felsen;Pulkit Agrawal;Jitendra Malik

  • Superposition of many models into one

    Brian Cheung;Alexander Terekhov;Yubei Chen;Pulkit Agrawal

  • Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning

    Richard Li;Allan Jabri;Trevor Darrell;Pulkit Agrawal

  • Learning to Perform Physics Experiments via Deep Reinforcement Learning.

    Misha Denil;Pulkit Agrawal;Tejas D. Kulkarni;Tom Erez

  • An End-to-End Differentiable Framework for Contact-Aware Robot Design

    Jie Xu;Tao Chen;Lara Zlokapa;Michael Foshey

  • Investigating Human Priors for Playing Video Games.

    Rachit Dubey;Pulkit Agrawal;Deepak Pathak;Alyosha A. Efros

Frequent Co-Authors

Jitendra Malik
Jitendra Malik University of California, Berkeley
Sergey Levine
Sergey Levine University of California, Berkeley
Trevor Darrell
Trevor Darrell University of California, Berkeley
Alexei A. Efros
Alexei A. Efros University of California, Berkeley
Joao Carreira
Joao Carreira Google (United States)
Thomas L. Griffiths
Thomas L. Griffiths Princeton University
Pieter Abbeel
Pieter Abbeel University of California, Berkeley
Alexandre M. Bayen
Alexandre M. Bayen University of California, Berkeley
Alison Gopnik
Alison Gopnik University of California, Berkeley

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