World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
68
Citations
20487
World Ranking
2065
National Ranking
1046

Fernando De la Torre 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 Fernando De la Torre 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: 222 publications — 54th percentile

54% of scientists in this discipline score the same or lower.

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

Fernando De la Torre 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 Fernando De la Torre 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.

Overview

Fernando De la Torre is affiliated with Carnegie Mellon University in the United States. Their research spans multiple fields, primarily focused on biochemistry, genetics, molecular biology, and computer science. Their work encompasses both applied and theoretical studies, integrating aspects of molecular biology with artificial intelligence methodologies.

They have contributed substantially to several specific subfields, including:

  • Molecular Biology
  • Plant Science
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Neurology

The main topics covered in their research reflect a diverse range of interests, with a strong emphasis on plant biochemistry, gene expression, and neurological disorders. Key topics include:

  • Plant biochemistry and biosynthesis
  • Plant Gene Expression Analysis
  • Horticultural and Viticultural Research
  • Adversarial Robustness in Machine Learning
  • Neurological disorders and treatments
  • Parkinson's Disease Mechanisms and Treatments
  • Advanced Sensor and Energy Harvesting Materials

Their recent published papers illustrate this breadth of focus. Notable works include:

  • Parkinson's Disease Tremor Detection in the Wild Using Wearable Accelerometers, 2020, Sensors
  • Transcriptional analysis of arogenate dehydratase genes identifies a link between phenylalanine biosynthesis and lignin biosynthesis, 2020, Journal of Experimental Botany
  • Deregulation of phenylalanine biosynthesis evolved with the emergence of vascular plants, 2021, PLANT PHYSIOLOGY
  • Enzymes Involved in the Biosynthesis of Arginine from Ornithine in Maritime Pine (Pinus pinaster Ait.), 2020, Plants
  • Special Issue Editorial: Plant Nitrogen Assimilation and Metabolism, 2021, Plants

Frequent co-authors collaborating with De la Torre demonstrate interdisciplinary cooperation. These include:

  • Concepción Ávila
  • Francisco M. Cánovas
  • Jorge El-Azaz
  • Jinqi Luo
  • Stanislav Panev

Research outputs have often been published in venues such as:

  • arXiv (Cornell University)
  • Plants
  • Sensors
  • Journal of Experimental Botany
  • PLANT PHYSIOLOGY

Best Publications

  • Supervised Descent Method and Its Applications to Face Alignment

    Xuehan Xiong;Fernando De la Torre

  • Facing Imbalanced Data--Recommendations for the Use of Performance Metrics

    Laszlo A. Jeni;Jeffrey F. Cohn;Fernando De La Torre

  • Max-Margin Early Event Detectors

    Minh Hoai;Fernando Torre

  • A Framework for Robust Subspace Learning

    Fernando De La Torre;Michael J. Black

  • Detecting depression from facial actions and vocal prosody

    Jeffrey F. Cohn;Tomas Simon Kruez;Iain Matthews;Ying Yang

  • Robust principal component analysis for computer vision

    F. De la Torre;M.J. Black

  • Factorized Graph Matching

    Feng Zhou;Fernando De la Torre

  • Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion

    Feng Zhou;F. De la Torre;J. K. Hodgins

  • Facial Expression Analysis.

    Fernando De la Torre;Jeffrey F. Cohn

  • Driver Gaze Tracking and Eyes Off the Road Detection System

    Francisco Vicente;Zehua Huang;Xuehan Xiong;Fernando De la Torre

  • Selective Transfer Machine for Personalized Facial Action Unit Detection

    Wen-Sheng Chu;Fernando De La Torre;Jeffery F. Cohn

  • Joint segmentation and classification of human actions in video

    Minh Hoai;Zhen-Zhong Lan;Fernando De la Torre

  • Temporal segmentation and activity classification from first-person sensing

    Ekaterina H Spriggs;Fernando De La Torre;Martial Hebert

  • Optimal feature selection for support vector machines

    Minh Hoai Nguyen;Fernando de la Torre

  • Canonical Time Warping for Alignment of Human Behavior

    Feng Zhou;Fernando Torre

  • Guide to the Carnegie Mellon University Multimodal Activity (CMU-MMAC) Database

    Fernando De la Torre;Jessica Hodgins;Adam Bargteil;Xavier Martin

  • Robust Matrix Factorization with Unknown Noise

    Deyu Meng;Fernando De la Torre

  • Aligned Cluster Analysis for temporal segmentation of human motion

    Feng Zhou;F. Torre;J.K. Hodgins

  • Global supervised descent method

    Xuehan Xiong;Fernando De la Torre

  • Unifying Nuclear Norm and Bilinear Factorization Approaches for Low-Rank Matrix Decomposition

    Ricardo Cabral;Fernando De la Torre;Joao P. Costeira;Alexandre Bernardino

Frequent Co-Authors

Jeffrey F. Cohn
Jeffrey F. Cohn University of Pittsburgh
Jessica K. Hodgins
Jessica K. Hodgins Carnegie Mellon University
Takeo Kanade
Takeo Kanade Carnegie Mellon University
Sergio Escalera
Sergio Escalera University of Barcelona
Simon Lucey
Simon Lucey University of Adelaide
Alexandre Bernardino
Alexandre Bernardino Instituto Superior Técnico
Manuela Veloso
Manuela Veloso Carnegie Mellon University
Iain Matthews
Iain Matthews University of East Anglia
Martial Hebert
Martial Hebert Carnegie Mellon University
Michael J. Black
Michael J. Black Max Planck Institute for Intelligent Systems

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