World's Best Scientists 2026 revealed!
Roland Memisevic

Roland Memisevic

D-Index & Metrics

Computer Science

D-Index
40
Citations
10233
World Ranking
9106
National Ranking
359

Roland Memisevic 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 Roland Memisevic 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: 73 publications — 2nd percentile

2% of scientists in this discipline score the same or lower.

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

Roland Memisevic 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 Roland Memisevic 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: 40 D-Index — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Overview

Roland Memisevic is affiliated with Twenty Billion Neurons in Canada and has contributed extensively to the field of computer science, with a focus on artificial intelligence. Their work spans topics such as topic modeling, natural language processing techniques, and human pose and action recognition.

Memisevic's research encompasses multiple subfields, including artificial intelligence, computer vision and pattern recognition, human-computer interaction, and cognitive neuroscience. Their published work also touches on multimodal machine learning applications, machine learning and data classification, computational physics and Python applications, as well as machine learning algorithms.

The scientist has authored multiple papers published primarily in arXiv (Cornell University), the most frequent venue for their work. Key recent publications include:

  • Static Analysis of Shape in TensorFlow Programs, 2020, arXiv (Cornell University)
  • Deductive Verification of Chain-of-Thought Reasoning, 2023, arXiv (Cornell University)
  • Unleashing the Creative Mind: Language Model As Hierarchical Policy For Improved Exploration on Challenging Problem Solving, 2023, arXiv (Cornell University)
  • Metaphors We Learn By, 2022, arXiv (Cornell University)
  • Is end-to-end learning enough for fitness activity recognition?, 2023, arXiv (Cornell University)

Frequent collaborators in their research include Sunny Panchal, M. Lee, Reza Pourreza, Apratim Bhattacharyya, and Ingo Bax, indicating a collaborative approach across several projects and topics.

The broad range of topics addressed by Memisevic illustrates engagement with machine learning challenges such as topic modeling, natural language processing, human activity recognition, and multimodal learning systems. Their publication record highlights contributions to advancing understanding in these areas through computational methods and interdisciplinary applications.

Best Publications

  • Theano: A Python framework for fast computation of mathematical expressions

    Rami Al-Rfou;Guillaume Alain;Amjad Almahairi

  • The “Something Something” Video Database for Learning and Evaluating Visual Common Sense

    Raghav Goyal;Samira Ebrahimi Kahou;Vincent Michalski;Joanna Materzynska

  • On Using Very Large Target Vocabulary for Neural Machine Translation

    Sébastien Jean;Kyunghyun Cho;Roland Memisevic;Yoshua Bengio

  • EmoNets: Multimodal deep learning approaches for emotion recognition in video

    Samira Ebrahimi Kahou;Xavier Bouthillier;Pascal Lamblin;Çaglar Gülçehre

  • Combining modality specific deep neural networks for emotion recognition in video

    Samira Ebrahimi Kahou;Christopher Pal;Xavier Bouthillier;Pierre Froumenty

  • Recurrent Neural Networks for Emotion Recognition in Video

    Samira Ebrahimi Kahou;Vincent Michalski;Kishore Konda;Roland Memisevic

  • Neural Networks with Few Multiplications

    Zhouhan Lin;Matthieu Courbariaux;Roland Memisevic;Yoshua Bengio

  • Learning to represent spatial transformations with factored higher-order boltzmann machines

    Roland Memisevic;Geoffrey E. Hinton

  • Unsupervised Learning of Image Transformations

    R. Memisevic;G. Hinton

  • The Jester Dataset: A Large-Scale Video Dataset of Human Gestures

    Joanna Materzynska;Guillaume Berger;Ingo Bax;Roland Memisevic

  • Denoising criterion for variational auto-encoding framework

    Daniel Im Jiwoong Im;Sungjin Ahn;Roland Memisevic;Yoshua Bengio

  • Generating images with recurrent adversarial networks

    Daniel Jiwoong Im;Chris Dongjoo Kim;Hui Jiang;Roland Memisevic

  • Learning Visual Odometry with a Convolutional Network

    Kishore Reddy Konda;Roland Memisevic

  • Montreal Neural Machine Translation Systems for WMT’15

    Sébastien Jean;Orhan Firat;Kyunghyun Cho;Roland Memisevic

  • Architectural Complexity Measures of Recurrent Neural Networks

    Saizheng Zhang;Yuhuai Wu;Tong Che;Zhouhan Lin

  • Learning to Relate Images

    R. Memisevic

  • Dropout as data augmentation

    Xavier Bouthillier;Kishore Konda;Pascal Vincent;Roland Memisevic

  • Learning to solve QBF

    Horst Samulowitz;Roland Memisevic

  • Gated Softmax Classification

    Roland Memisevic;Christopher Zach;Marc Pollefeys;Geoffrey E. Hinton

  • Modeling Deep Temporal Dependencies with Recurrent Grammar Cells

    Vincent Michalski;Roland Memisevic;Kishore Konda

Frequent Co-Authors

Yoshua Bengio
Yoshua Bengio University of Montreal
Geoffrey E. Hinton
Geoffrey E. Hinton University of Toronto
David J. Fleet
David J. Fleet University of Toronto
Pascal Vincent
Pascal Vincent Facebook (United States)
Chris Pal
Chris Pal Polytechnique Montréal
Aaron Courville
Aaron Courville University of Montreal
Kyunghyun Cho
Kyunghyun Cho New York University
Caglar Gulcehre
Caglar Gulcehre DeepMind (United Kingdom)
Yann N. Dauphin
Yann N. Dauphin Google (United States)
Hui Jiang
Hui Jiang York University

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