World's Best Scientists 2026 revealed!

D-Index & Metrics

Neuroscience

D-Index
93
Citations
33536
World Ranking
982
National Ranking
523

Engineering and Technology

D-Index
88
Citations
32233
World Ranking
315
National Ranking
107

Krishna V. Shenoy publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Krishna V. Shenoy sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 134 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 117 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 59 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 272 publications — 70th percentile

70% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Krishna V. Shenoy D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Krishna V. Shenoy sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 128 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 349 scientists 41 D-Index: 362 scientists 42 D-Index: 425 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 94 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 24 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 88 D-Index — 97th percentile

97% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Research.com Recognitions

  • 2016 - Fellow of the Indian National Academy of Engineering (INAE)
  • 2002 - Fellow of Alfred P. Sloan Foundation

Overview

Krishna V. Shenoy is affiliated with Stanford University in the United States and has made significant contributions to the field of neuroscience. Their work spans multiple subfields including cognitive neuroscience, cellular and molecular neuroscience, electrical and electronic engineering, biomedical engineering, and artificial intelligence.

The scientist's research primarily focuses on topics such as EEG and brain-computer interfaces, neuroscience and neural engineering, neural dynamics and brain function, advanced memory and neural computing, muscle activation and electromyography studies, motor control and adaptation, and functional brain connectivity studies.

Krishna V. Shenoy has published extensively in various academic venues. The most frequent publication outlets include:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • Nature
  • Neuron
  • Nature Communications
  • Nature Neuroscience

Their recent papers include:

  • High-performance brain-to-text communication via handwriting (2021, Nature)
  • Computation Through Neural Population Dynamics (2020, Annual Review of Neuroscience)
  • A high-performance speech neuroprosthesis (2023, Nature)
  • Large-scale neural recordings with single neuron resolution using Neuropixels probes in human cortex (2022, Nature Neuroscience)
  • Hand Knob Area of Premotor Cortex Represents the Whole Body in a Compositional Way (2020, Cell)

Krishna V. Shenoy frequently collaborates with other researchers, with several coauthors appearing repeatedly in their body of work. Frequent collaborators include:

  • Leigh R. Hochberg
  • Jaimie M. Henderson
  • Francis R. Willett
  • Donald T. Avansino
  • Eric M. Trautmann

The scientist has been recognized by professional organizations, having been named a Fellow of the Indian National Academy of Engineering (INAE) in 2016 and a Fellow of the Alfred P. Sloan Foundation in 2002.

Best Publications

  • Context-dependent computation by recurrent dynamics in prefrontal cortex

    Valerio Mante;David Sussillo;Krishna V. Shenoy;William T. Newsome

  • Neural population dynamics during reaching

    Mark M. Churchland;John P. Cunningham;John P. Cunningham;Matthew T. Kaufman;Justin D. Foster

  • 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

  • A high-performance brain–computer interface

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

  • Cortical activity in the null space: permitting preparation without movement

    Matthew T Kaufman;Mark M Churchland;Stephen I Ryu;Krishna V Shenoy

  • 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

  • High-performance brain-to-text communication via handwriting

    Francis R. Willett;Francis R. Willett;Donald T. Avansino;Leigh R. Hochberg;Jaimie M. Henderson

  • Inferring single-trial neural population dynamics using sequential auto-encoders.

    Chethan Pandarinath;Daniel J. O’Shea;Jasmine Collins;Rafal Jozefowicz;Rafal Jozefowicz

  • A high-performance neural prosthesis enabled by control algorithm design

    Vikash Gilja;Paul Nuyujukian;Cindy A Chestek;John P Cunningham;John P Cunningham

  • A neural network that finds a naturalistic solution for the production of muscle activity

    David Sussillo;Mark M Churchland;Matthew T Kaufman;Krishna V Shenoy

  • Computation Through Neural Population Dynamics.

    Saurabh Vyas;Matthew D Golub;David Sussillo;David Sussillo;Krishna V Shenoy

  • Neural Variability in Premotor Cortex Provides a Signature of Motor Preparation

    Mark M. Churchland;Byron M. Yu;Stephen I. Ryu;Gopal Santhanam

  • Cortical Preparatory Activity: Representation of Movement or First Cog in a Dynamical Machine?

    Mark M. Churchland;John P. Cunningham;John P. Cunningham;Matthew T. Kaufman;Stephen I. Ryu;Stephen I. Ryu

  • High performance communication by people with paralysis using an intracortical brain-computer interface

    Chethan Pandarinath;Paul Nuyujukian;Christine H Blabe;Brittany L Sorice

  • An optogenetic toolbox designed for primates

    Ilka Diester;Matthew T Kaufman;Murtaza Mogri;Ramin Pashaie;Ramin Pashaie

  • A Central Source of Movement Variability

    Mark M. Churchland;Afsheen Afshar;Krishna V. Shenoy

  • A high-performance speech neuroprosthesis

    Unknown

  • Temporal Complexity and Heterogeneity of Single-Neuron Activity in Premotor and Motor Cortex

    Mark M. Churchland;Krishna V. Shenoy

  • Long-term stability of neural prosthetic control signals from silicon cortical arrays in rhesus macaque motor cortex

    Cynthia A Chestek;Vikash Gilja;Paul Nuyujukian;Justin D Foster

  • Clinical translation of a high-performance neural prosthesis

    Vikash Gilja;Chethan Pandarinath;Christine H Blabe;Paul Nuyujukian

Frequent Co-Authors

Stephen I. Ryu
Stephen I. Ryu Stanford University
Byron M. Yu
Byron M. Yu Carnegie Mellon University
Leigh R. Hochberg
Leigh R. Hochberg Harvard University
Jaimie M. Henderson
Jaimie M. Henderson Stanford University
Mark M. Churchland
Mark M. Churchland Columbia University
John P. Cunningham
John P. Cunningham Columbia University
Maneesh Sahani
Maneesh Sahani University College London
Teresa H. Meng
Teresa H. Meng Stanford University
Richard A. Andersen
Richard A. Andersen California Institute of Technology
Karl Deisseroth
Karl Deisseroth Stanford University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Engineering and Technology in the USA offers more flexibility than ever. Many students and working professionals are choosing online options for their convenience and career growth. From self-paced classes to fast-track qualifications, online learning adapts to diverse needs.

For those seeking quick entry into high-earning fields, 6-month certificate programs that pay well can offer focused training in areas like IT, engineering technology, or project management. These programs are ideal for upskilling or launching a new career without a lengthy commitment.

Flexible learning is vital for busy parents, too. There are many college programs for moms that prioritize online access, flexible schedules, and family-friendly options, helping moms continue or restart their education in high-demand STEM fields.

If you prefer a shorter commitment before diving deeper, consider college classes online. These 6-week courses allow you to explore foundational skills or complete prerequisites at your own pace.

Career advancement remains central for many. For those interested in management or financial roles within the tech sector, accelerated finance degree programs online provide a fast path to credentials that can help you stand out in engineering-related fields.

Best Scientists Citing Krishna V. Shenoy

Trending Scientists

Recently Published Articles