World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
13009
World Ranking
6348
National Ranking
2835

Matthai Philipose 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 Matthai Philipose 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: 123 publications — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Matthai Philipose 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 Matthai Philipose 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: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Overview

Matthai Philipose is a researcher affiliated with Microsoft in the United States. Their work spans multiple domains within computer science, including both foundational and applied topics.

The main fields of study for Matthai Philipose include:

  • Computer Science

Within this broad domain, their contributions touch on several subfields such as:

  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications
  • Artificial Intelligence

Their research covers key topics including:

  • Advanced Neural Network Applications
  • Age of Information Optimization
  • Stochastic Gradient Optimization Techniques

Recent publications by Matthai Philipose include the paper titled "Symphony: Optimized DNN Model Serving using Deferred Batch Scheduling", published in 2023 in arXiv (Cornell University).

Their collaborations are recorded with several coauthors, reflecting a partnership in different research efforts. Frequent coauthors include:

  • Lequn Chen
  • Weixin Deng
  • Anirudh Canumalla
  • Xin Yu
  • Arvind Krishnamurthy

The primary venue for publications so far has been:

  • arXiv (Cornell University)

Overall, Matthai Philipose's academic profile highlights a focus on technologies related to artificial intelligence and neural networks with applications in networking and information optimization. Their work intersects theory and practical system design in computer science research.

Best Publications

  • Inferring activities from interactions with objects

    M. Philipose;K.P. Fishkin;M. Perkowitz;D.J. Patterson

  • Mapping and localization with RFID technology

    D. Hahnel;W. Burgard;D. Fox;K. Fishkin

  • Inertially controlled switch and RFID tag

    Joshua R. Smith;Matthai Philipose

  • Fine-grained activity recognition by aggregating abstract object usage

    D.J. Patterson;D. Fox;H. Kautz;M. Philipose

  • A long-term evaluation of sensing modalities for activity recognition

    Beth Logan;Jennifer Healey;Matthai Philipose;Emmanuel Munguia Tapia

  • Real-Time Video Analytics: The Killer App for Edge Computing

    Ganesh Ananthanarayanan;Paramvir Bahl;Peter Bodik;Krishna Chintalapudi

  • A Scalable Approach to Activity Recognition based on Object Use

    Jianxin Wu;A. Osuntogun;T. Choudhury;M. Philipose

  • MCDNN: An Approximation-Based Execution Framework for Deep Stream Processing Under Resource Constraints

    Seungyeop Han;Haichen Shen;Matthai Philipose;Sharad Agarwal

  • Recognizing daily activities with RFID-based sensors

    Michael Buettner;Richa Prasad;Matthai Philipose;David Wetherall

  • Battery-free wireless identification and sensing

    M. Philipose;J.R. Smith;B. Jiang;A. Mamishev

  • Energy Scavenging for Inductively Coupled Passive RFID Systems

    Bing Jiang;J.R. Smith;M. Philipose;S. Roy

  • Live video analytics at scale with approximation and delay-tolerance

    Haoyu Zhang;Ganesh Ananthanarayanan;Peter Bodik;Matthai Philipose

  • RFID-based techniques for human-activity detection

    Joshua R. Smith;Kenneth P. Fishkin;Bing Jiang;Alexander Mamishev

  • Unsupervised activity recognition using automatically mined common sense

    Danny Wyatt;Matthai Philipose;Tanzeem Choudhury

  • Fast, effective dynamic compilation

    Joel Auslander;Matthai Philipose;Craig Chambers;Susan J. Eggers

  • VideoEdge: Processing Camera Streams using Hierarchical Clusters

    Chien-Chun Hung;Ganesh Ananthanarayanan;Peter Bodik;Leana Golubchik

  • Mining models of human activities from the web

    Mike Perkowitz;Matthai Philipose;Kenneth Fishkin;Donald J. Patterson

  • System and method for performing selective dynamic compilation using run-time information

    Craig Chambers;Susan J. Eggers;Brian K. Grant;Markus Mock

  • Energy characterization and optimization of image sensing toward continuous mobile vision

    Robert LiKamWa;Bodhi Priyantha;Matthai Philipose;Lin Zhong

  • DyC: an expressive annotation-directed dynamic compiler for C

    Brian Grant;Markus Mock;Matthai Philipose;Craig Chambers

  • Focus: querying large video datasets with low latency and low cost

    Kevin Hsieh;Ganesh Ananthanarayanan;Peter Bodik;Shivaram Venkataraman

  • Do Deep Convolutional Nets Really Need to be Deep and Convolutional

    Gregor Urban;Krzysztof J. Geras;Samira Ebrahimi Kahou;Özlem Aslan

Frequent Co-Authors

Kenneth P. Fishkin
Kenneth P. Fishkin Google (United States)
Craig Chambers
Craig Chambers Google (United States)
Paramvir Bahl
Paramvir Bahl Microsoft (United States)
Joshua R. Smith
Joshua R. Smith University of Washington
Ganesh Ananthanarayanan
Ganesh Ananthanarayanan Microsoft (United States)
Sumit Roy
Sumit Roy University of Washington
Tanzeem Choudhury
Tanzeem Choudhury Cornell University
Susan J. Eggers
Susan J. Eggers University of Washington
Henry Kautz
Henry Kautz University of Virginia
Rich Caruana
Rich Caruana Microsoft (United States)

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