World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
68
Citations
24352
World Ranking
2050
National Ranking
1037

Ashutosh Saxena 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 Ashutosh Saxena 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: 250 publications — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Ashutosh Saxena 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 Ashutosh Saxena 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: 68 D-Index — 86th percentile

86% 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

  • 2011 - Fellow of Alfred P. Sloan Foundation

Overview

Ashutosh Saxena is affiliated with Cornell University in the United States. Their research spans multiple areas within computer science and engineering, with a particular focus on artificial intelligence, computer vision and pattern recognition, computer networks and communications, signal processing, and information systems.

The main fields of study covered in their publications include:

  • Computer Science
  • Engineering

Within these broad fields, the scientist has contributed extensively to several subfields:

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

Their research touches on key scientific topics such as:

  • Coding theory and cryptography
  • Chaos-based Image/Signal Encryption
  • Advanced Malware Detection Techniques
  • Cryptographic Implementations and Security
  • User Authentication and Security Systems
  • Network Security and Intrusion Detection
  • Graph theory and CDMA systems

Frequent collaborators in their research include Vikas Tiwari, Ajeet Singh, Appala Naidu Tentu, K. V. Pradeepthi, and B. N. Mohapatra.

Publication venues encompass journals specialized in information technology, computer security, and communications. Notable venues from their publication record include:

  • International Journal of Information and Computer Security
  • arXiv (Cornell University)
  • Journal of Advances in Information Technology
  • IET Networks
  • International Journal of Sensors Wireless Communications and Control

Representative recent papers authored or co-authored by Saxena include:

  • "Performance Evaluation of Sentiment Analysis on Text and Emoji Data Using End-to-End, Transfer Learning, Distributed and Explainable AI Models" (2022), Journal of Advances in Information Technology
  • "Energy-efficient reporting scheme for cognitive radio networks" (2021), IET Networks
  • "Improved Detection Performance of Energy Detection Based Spectrum Sensing in Cognitive Radio Networks" (2021), International Journal of Sensors Wireless Communications and Control
  • "Generation of 8 × 8 S-boxes using 4 × 4 optimal S-boxes" (2023), International Journal of Information and Computer Security
  • "Noise level estimation using locality preserving natural image statistics" (2024), Pattern Recognition

Ashutosh Saxena was named a Fellow of the Alfred P. Sloan Foundation in 2011.

Best Publications

  • Make3D: Learning 3D Scene Structure from a Single Still Image

    A. Saxena;Min Sun;A.Y. Ng

  • Deep learning for detecting robotic grasps

    Ian Lenz;Honglak Lee;Ashutosh Saxena

  • Structural-RNN: Deep Learning on Spatio-Temporal Graphs

    Ashesh Jain;Amir R. Zamir;Silvio Savarese;Ashutosh Saxena

  • Learning Depth from Single Monocular Images

    Ashutosh Saxena;Sung H. Chung;Andrew Y. Ng

  • Robotic Grasping of Novel Objects using Vision

    Ashutosh Saxena;Justin Driemeyer;Andrew Y. Ng

  • 3-D Depth Reconstruction from a Single Still Image

    Ashutosh Saxena;Sung H. Chung;Andrew Y. Ng

  • Learning human activities and object affordances from RGB-D videos

    Hema Swetha Koppula;Rudhir Gupta;Ashutosh Saxena

  • Anticipating Human Activities Using Object Affordances for Reactive Robotic Response

    Hema S. Koppula;Ashutosh Saxena

  • A dynamic ID-based remote user authentication scheme

    M.L. Das;A. Saxena;V.P. Gulati

  • Anticipating Human Activities using Object Affordances for Reactive Robotic Response

    Hema Swetha Koppula;Ashutosh Saxena

  • Unstructured human activity detection from RGBD images

    Jaeyong Sung;Colin Ponce;Bart Selman;Ashutosh Saxena

  • Efficient grasping from RGBD images: Learning using a new rectangle representation

    Yun Jiang;Stephen Moseson;Ashutosh Saxena

  • High speed obstacle avoidance using monocular vision and reinforcement learning

    Jeff Michels;Ashutosh Saxena;Andrew Y. Ng

  • Semantic Labeling of 3D Point Clouds for Indoor Scenes

    Hema S. Koppula;Abhishek Anand;Thorsten Joachims;Ashutosh Saxena

  • DeepMPC: Learning Deep Latent Features for Model Predictive Control

    Ian Lenz;Ross A. Knepper;Ashutosh Saxena

  • Human activity detection from RGBD images

    Jaeyong Sung;Colin Ponce;Bart Selman;Ashutosh Saxena

  • Depth estimation using monocular and stereo cues

    Ashutosh Saxena;Jamie Schulte;Andrew Y. Ng

  • Autonomous MAV flight in indoor environments using single image perspective cues

    Cooper Bills;Joyce Chen;Ashutosh Saxena

  • Learning 3-D Scene Structure from a Single Still Image

    A. Saxena;Min Sun;A.Y. Ng

  • Car that Knows Before You Do: Anticipating Maneuvers via Learning Temporal Driving Models

    Ashesh Jain;Hema S. Koppula;Bharad Raghavan;Shane Soh

  • Tell Me Dave: Context-Sensitive Grounding of Natural Language to Manipulation Instructions

    Dipendra Kumar Misra;Jaeyong Sung;Kevin Lee;Ashutosh Saxena

Frequent Co-Authors

Andrew Y. Ng
Andrew Y. Ng Stanford University
Silvio Savarese
Silvio Savarese Stanford University
Bart Selman
Bart Selman Cornell University
Tsuhan Chen
Tsuhan Chen Cornell University
Thorsten Joachims
Thorsten Joachims Cornell University
Min Sun
Min Sun National Tsing Hua University
Amir Roshan Zamir
Amir Roshan Zamir Stanford University
Honglak Lee
Honglak Lee University of Michigan–Ann Arbor
Joseph Y. Halpern
Joseph Y. Halpern Cornell University
Hod Lipson
Hod Lipson Columbia University

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