World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
55
Citations
11900
World Ranking
4324
National Ranking
265

Maneesh Sahani 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 Maneesh Sahani 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: 200 publications — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Maneesh Sahani 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 Maneesh Sahani 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: 55 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Overview

Maneesh Sahani is affiliated with University College London in the United Kingdom. Their research spans the fields of neuroscience and computer science, with a strong focus on cognitive neuroscience and artificial intelligence among other subfields.

The scientist has published extensively, contributing notably to several research venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Neuron
  • 2022 Conference on Cognitive Computational Neuroscience
  • Zenodo (CERN European Organization for Nuclear Research)

Maneesh Sahani's work covers multiple main fields and subfields of study, including:

  • Neuroscience
  • Computer Science
  • Cognitive Neuroscience
  • Artificial Intelligence
  • Cellular and Molecular Neuroscience
  • Molecular Biology
  • Statistics and Probability

The major topics addressed in their research include:

  • Neural dynamics and brain function
  • Neural Networks and Applications
  • Neuroscience and Neuropharmacology Research
  • Functional Brain Connectivity Studies
  • Visual perception and processing mechanisms
  • Reinforcement Learning in Robotics
  • EEG and Brain-Computer Interfaces

Recent papers by Maneesh Sahani include:

  • Deep learning, reinforcement learning, and world models, 2022, Neural Networks
  • Learning and attention increase visual response selectivity through distinct mechanisms, 2021, Neuron
  • Dendritic calcium signals in rhesus macaque motor cortex drive an optical brain-computer interface, 2021, Nature Communications
  • Dynamics on the manifold: Identifying computational dynamical activity from neural population recordings, 2021, Current Opinion in Neurobiology
  • Direct neural perturbations reveal a dynamical mechanism for robust computation, 2022, bioRxiv (Cold Spring Harbor Laboratory)

Collaborations play a significant role in their research output. Frequent co-authors include:

  • Thomas D. Mrsic-Flogel
  • Valerio Mante
  • Jasper Poort
  • Antonin Blot
  • Angus Chadwick

Best Publications

  • Stimulus onset quenches neural variability: a widespread cortical phenomenon

    Mark M. Churchland;Byron M. Yu;Byron M. Yu;John P. Cunningham;Leo P. Sugrue;Leo P. Sugrue

  • Cortical control of arm movements: a dynamical systems perspective.

    Krishna V. Shenoy;Maneesh Sahani;Mark M. Churchland

  • Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity

    Byron M Yu;John P Cunningham;Gopal Santhanam;Stephen I. Ryu

  • Localization bias and spatial resolution of adaptive and non-adaptive spatial filters for MEG source reconstruction

    Kensuke Sekihara;Maneesh Sahani;Srikantan S. Nagarajan

  • Deep learning, reinforcement learning, and world models

    Unknown

  • Learning Enhances Sensory and Multiple Non-sensory Representations in Primary Visual Cortex.

    Jasper Poort;Adil G. Khan;Marius Pachitariu;Abdellatif Nemri;Abdellatif Nemri

  • Spectrotemporal Structure of Receptive Fields in Areas AI and AAF of Mouse Auditory Cortex

    Jennifer F Linden;Robert C Liu;Maneesh Sahani;Maneesh Sahani;Christoph E Schreiner

  • Single-Trial Neural Correlates of Arm Movement Preparation

    Afsheen Afshar;Gopal Santhanam;Byron M. Yu;Byron M. Yu;Stephen I. Ryu;Stephen I. Ryu

  • Distinct learning-induced changes in stimulus selectivity and interactions of GABAergic interneuron classes in visual cortex

    Adil G Khan;Adil G Khan;Jasper Poort;Angus Chadwick;Antonin Blot;Antonin Blot

  • Empirical models of spiking in neural populations

    Jakob H Macke;Lars Buesing;John P Cunningham;Byron M Yu

  • Techniques for extracting single-trial activity patterns from large-scale neural recordings

    Mark M Churchland;Byron M Yu;Byron M Yu;Maneesh Sahani;Krishna V Shenoy

  • Two problems with variational expectation maximisation for time-series models

    Richard Eric Turner;Maneesh Sahani

  • Mixture of trajectory models for neural decoding of goal-directed movements

    Byron M. Yu;Caleb Kemere;Gopal Santhanam;Afsheen Afshar

  • Latent variable models for neural data analysis

    R. A. Andersen;Maneesh Sahani

  • Nonlinearities and contextual influences in auditory cortical responses modeled with multilinear spectrotemporal methods.

    Misha B. Ahrens;Jennifer F. Linden;Maneesh Sahani

  • How Linear are Auditory Cortical Responses

    Maneesh Sahani;Jennifer F. Linden

  • State-Dependent Population Coding in Primary Auditory Cortex

    Marius Pachitariu;Dmitry R. Lyamzin;Maneesh Sahani;Nicholas A. Lesica

  • A Head-Mounted Camera System Integrates Detailed Behavioral Monitoring with Multichannel Electrophysiology in Freely Moving Mice

    Arne F. Meyer;Jasper Poort;John O’Keefe;Maneesh Sahani

  • Outlier responses reflect sensitivity to statistical structure in the human brain

    Marta I. Garrido;Marta I. Garrido;Maneesh Sahani;Raymond J. Dolan

  • Implicit knowledge of visual uncertainty guides decisions with asymmetric outcomes

    Louise Whiteley;Maneesh Sahani

  • Doubly distributional population codes: simultaneous representation of uncertainty and multiplicity

    Maneesh Sahani;Peter Dayan

  • Adaptation and Unsupervised Learning

    Peter Dayan;Maneesh Sahani;Gregoire Deback

Frequent Co-Authors

Krishna V. Shenoy
Krishna V. Shenoy Stanford University
Byron M. Yu
Byron M. Yu Carnegie Mellon University
Misha B. Ahrens
Misha B. Ahrens Howard Hughes Medical Institute
Richard E. Turner
Richard E. Turner University of Cambridge
Stephen I. Ryu
Stephen I. Ryu Stanford University
Richard A. Andersen
Richard A. Andersen California Institute of Technology
John P. Cunningham
John P. Cunningham Columbia University
Michael M. Merzenich
Michael M. Merzenich University of California, San Francisco
Raymond J. Dolan
Raymond J. Dolan University College London
Jonathan W. Pillow
Jonathan W. Pillow Princeton University

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