World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
9442
World Ranking
5643
National Ranking
2571

Milind R. Naphade 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 Milind R. Naphade 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: 168 publications — 34th percentile

34% of scientists in this discipline score the same or lower.

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

Milind R. Naphade 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 Milind R. Naphade 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: 50 D-Index — 62nd percentile

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

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

Overview

Milind R. Naphade is affiliated with Nvidia in the United States. Their research focuses primarily on computer science, with specific contributions in computer vision and pattern recognition, radiological and ultrasound technology, civil and structural engineering, safety, risk, reliability and quality, and artificial intelligence.

Their work covers a variety of topics within these fields, including:

  • Advanced Neural Network Applications
  • Human Pose and Action Recognition
  • Generative Adversarial Networks and Image Synthesis
  • Occupational Health and Safety Research
  • Infrastructure Maintenance and Monitoring
  • Traffic and Road Safety
  • Video Surveillance and Tracking Methods

Milind R. Naphade has published research in several venues. The most frequent publication outlets include:

  • arXiv (Cornell University)
  • Journal of Computing in Civil Engineering

Notable recent papers authored or co-authored by Milind R. Naphade include:

  • "Video-Based Motion Trajectory Forecasting Method for Proactive Construction Safety Monitoring Systems" (2020), Journal of Computing in Civil Engineering
  • "PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data" (2020), arXiv (Cornell University)
  • "LLM Surgery: Efficient Knowledge Unlearning and Editing in Large Language Models" (2024), arXiv (Cornell University)
  • "Training Dynamics Underlying Language Model Scaling Laws: Loss Deceleration and Zero-Sum Learning" (2025), arXiv (Cornell University)

The scientist has collaborated frequently with peers including Xiaodong Yang, Yue Yao, Liang Zheng, Tom Gedeon, and Shuai Tang, indicating ongoing engagement in collaborative research efforts.

Best Publications

  • Large-scale concept ontology for multimedia

    M. Naphade;J.R. Smith;J. Tesic;Shih-Fu Chang

  • Smarter Cities and Their Innovation Challenges

    M Naphade;G Banavar;C Harrison;J Paraszczak

  • CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification

    Zheng Tang;Milind Naphade;Ming-Yu Liu;Xiaodong Yang

  • A probabilistic framework for semantic video indexing, filtering, and retrieval

    H.R. Naphide;T.S. Huang

  • IBM Research TRECVID-2003 Video Retrieval System.

    Arnon Amir;Marco Berg;Shih-Fu Chang;Winston H. Hsu

  • IBM Research TRECVID-2005 Video Retrieval System

    Arnon Amir;Janne Argillander;Murray Campbell;Alexander Haubold

  • Probabilistic multimedia objects (multijects): a novel approach to video indexing and retrieval in multimedia systems

    M.R. Naphade;T. Kristjansson;B. Frey;T.S. Huang

  • Semantic Indexing of Multimedia Content Using Visual, Audio, and Text Cues

    W. H. Adams;Giridharan Iyengar;Ching-Yung Lin;Milind Ramesh Naphade

  • Multimedia semantic indexing using model vectors

    J.R. Smith;M. Naphade;A. Natsev

  • Factor graph framework for semantic video indexing

    M. Ramesh Naphade;I.V. Kozintsev;T.S. Huang

  • A high-performance shot boundary detection algorithm using multiple cues

    M.R. Naphade;R. Mehrotra;A.M. Ferman;J. Warnick

  • Novel scheme for fast and efficent video sequence matching using compact signatures

    Milind Ramesh Naphade;Minerva M. Yeung;Boon-Lock Yeo

  • On the detection of semantic concepts at TRECVID

    Milind R. Naphade;John R. Smith

  • PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data

    Zheng Tang;Milind Naphade;Stan Birchfield;Jonathan Tremblay

  • Extracting semantics from audio-visual content: the final frontier in multimedia retrieval

    M.R. Naphade;T.S. Huang

  • Learning the semantics of multimedia queries and concepts from a small number of examples

    Apostol (Paul) Natsev;Milind R. Naphade;Jelena TešiĆ

  • Simulating Content Consistent Vehicle Datasets with Attribute Descent.

    Yue Yao;Liang Zheng;Xiaodong Yang;Milind Naphade

  • IBM Research TRECVID-2006 Video Retrieval System

    Murray Campbell;Alexander Haubold;Shahram Ebadollahi;Dhiraj Joshi

  • Method and apparatus for active annotation of multimedia content

    Sankar Basu;Ching-Yung Lin;Milind Naphade;John Smith

  • Method for content-based temporal segmentation of video

    James Warnick;Ahmet M. Ferman;Bilge Gunsel;Milind R. Naphade

  • IBM Research TRECVID 2004 Video Retrieval System.

    Arnon Amir;Janne Argillander;Marco Berg;Shih-Fu Chang

Frequent Co-Authors

John R. Smith
John R. Smith IBM (United States)
Apostol Natsev
Apostol Natsev Google (United States)
Ching-Yung Lin
Ching-Yung Lin National Chi Nan University
Belle L. Tseng
Belle L. Tseng Apple (United States)
Thomas S. Huang
Thomas S. Huang University of Illinois at Urbana-Champaign
Sambit Sahu
Sambit Sahu IBM (United States)
Xiaodong Yang
Xiaodong Yang Nvidia (United Kingdom)
Arnon Amir
Arnon Amir IBM (United States)
Chung-Sheng Li
Chung-Sheng Li PricewaterhouseCoopers (United Kingdom)
Chalapathy Neti
Chalapathy Neti IBM (United States)

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