World's Best Scientists 2026 revealed!
Sayan Mukherjee

Sayan Mukherjee

D-Index & Metrics

Computer Science

D-Index
60
Citations
78038
World Ranking
3144
National Ranking
1523

Sayan Mukherjee 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 Sayan Mukherjee 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.

Sayan Mukherjee 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 Sayan Mukherjee 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: 60 D-Index — 78th percentile

78% of scientists in this discipline score the same or lower.

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

Overview

Sayan Mukherjee is affiliated with Duke University in the United States and has contributed extensively to research primarily in the field of Computer Science. Their work has a significant emphasis on Artificial Intelligence, Statistical and Nonlinear Physics, Molecular Biology, Statistics and Probability, and Sociology and Political Science.

Their principal research topics include:

  • Chaos control and synchronization
  • Complex Systems and Time Series Analysis
  • Topological and Geometric Data Analysis
  • Markov Chains and Monte Carlo Methods
  • Statistical Mechanics and Entropy
  • Machine Learning and Extreme Learning Machines (ELM)
  • Neural Networks and Applications

Sayan Mukherjee has authored papers in various publication venues, with a notable concentration on:

  • arXiv (Cornell University)
  • UNC Libraries
  • The European Physical Journal Special Topics
  • Complexity
  • Nonlinear Dynamics

Frequent collaborators in their research include Michele Caprio, Santo Banerjee, Hayder Natiq, Parthasakha Das, and Pritha Das. These coauthors have worked alongside Mukherjee on multiple projects.

Some selected recent publications by Sayan Mukherjee are:

  • "Acceptance of Location-Based Advertising by Young Consumers: A Stimulus-Organism-Response (S-O-R) Model Perspective," 2023, Information Systems Management
  • "Multistability and chaos in a noise-induced blood flow," 2021, The European Physical Journal Special Topics
  • "Characterizing chaos and multifractality in noise-assisted tumor-immune interplay," 2020, Nonlinear Dynamics
  • "Multistability and chaotic scenario in a quantum pair-ion plasma," 2020, Zeitschrift für Naturforschung A
  • "Dynamical Complexity and Multistability in a Novel Lunar Wake Plasma System," 2020, Complexity

Best Publications

  • Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

    Aravind Subramanian;Pablo Tamayo;Vamsi K. Mootha;Sayan Mukherjee

  • Choosing Multiple Parameters for Support Vector Machines

    Olivier Chapelle;Vladimir Vapnik;Olivier Bousquet;Sayan Mukherjee

  • Support Vector Method for Multivariate Density Estimation

    Vladimir Vapnik;Sayan Mukherjee

  • Multiclass cancer diagnosis using tumor gene expression signatures

    Sridhar Ramaswamy;Pablo Tamayo;Ryan Rifkin;Sayan Mukherjee

  • Feature Selection for SVMs

    Jason Weston;Sayan Mukherjee;Olivier Chapelle;Massimiliano Pontil

  • Nonlinear prediction of chaotic time series using support vector machines

    S. Mukherjee;E. Osuna;F. Girosi

  • An oncogenic KRAS2 expression signature identified by cross-species gene-expression analysis

    Alejandro Sweet-Cordero;Sayan Mukherjee;Sayan Mukherjee;Aravind Subramanian;Han You

  • Fast Principal-Component Analysis Reveals Convergent Evolution of ADH1B in Europe and East Asia

    Kevin J. Galinsky;Kevin J. Galinsky;Gaurav Bhatia;Po-Ru Loh;Po-Ru Loh;Stoyan Georgiev

  • Molecular classification of multiple tumor types.

    Chen-Hsiang Yeang;Sridhar Ramaswamy;Pablo Tamayo;Sayan Mukherjee

  • General conditions for predictivity in learning theory

    Tomaso Poggio;Ryan Rifkin;Ryan Rifkin;Sayan Mukherjee;Sayan Mukherjee;Partha Niyogi

  • Estimating dataset size requirements for classifying DNA microarray data.

    Sayan Mukherjee;Pablo Tamayo;Simon Rogers;Ryan M. Rifkin

  • Probability measures on the space of persistence diagrams

    Yuriy Mileyko;Sayan Mukherjee;John Harer

  • Gene expression changes and molecular pathways mediating activity-dependent plasticity in visual cortex

    Daniela Tropea;Gabriel Kreiman;Alvin Lyckman;Alvin Lyckman;Sayan Mukherjee;Sayan Mukherjee

  • Fréchet Means for Distributions of Persistence Diagrams

    Katharine Turner;Yuriy Mileyko;Sayan Mukherjee;John Harer

  • Learning theory: stability is sufficient for generalization and necessary and sufficient for consistency of empirical risk minimization

    Sayan Mukherjee;Sayan Mukherjee;Partha Niyogi;Tomaso A. Poggio;Ryan M. Rifkin;Ryan M. Rifkin

  • Support Vector Machine Classification of Microarray Data

    Sayan Mukherjee;Ryan Rifkin

  • Optimal gene expression analysis by microarrays

    Lance D. Miller;Philip M. Long;Philip M. Long;Limsoon Wong;Sayan Mukherjee

  • Naught all zeros in sequence count data are the same.

    Justin D. Silverman;Kimberly Roche;Sayan Mukherjee;Lawrence A. David

  • Persistent homology transform for modeling shapes and surfaces

    Katharine Turner;Sayan Mukherjee;Doug M. Boyer

  • A New Fully Automated Approach for Aligning and Comparing Shapes

    Doug M. Boyer;Jesus Puente;Justin T. Gladman;Chris Glynn

  • Permutation tests for classification

    Polina Golland;Feng Liang;Sayan Mukherjee;Dmitry Panchenko

Frequent Co-Authors

Joseph R. Nevins
Joseph R. Nevins Duke University
Terrence S. Furey
Terrence S. Furey University of North Carolina at Chapel Hill
John Harer
John Harer Duke University
Felipe A. Medeiros
Felipe A. Medeiros Duke University
Jonathan C. Mattingly
Jonathan C. Mattingly Duke University
Geoffrey S. Ginsburg
Geoffrey S. Ginsburg Duke University
Todd R. Golub
Todd R. Golub Harvard University
Jill P. Mesirov
Jill P. Mesirov University of California, San Diego
Alkes L. Price
Alkes L. Price Harvard 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 online education can open new doors for students interested in Computer Science. For those seeking a faster path, you can find the quickest cheapest masters degree programs online, allowing you to earn a credential efficiently and affordably.

It's also important to consider the most useful graduate degrees that are in demand. Specializations like data science, cybersecurity, and artificial intelligence frequently offer strong career growth and higher earning potential.

Not everyone wants or needs a full bachelor's or master's degree to start their career. Online associate degree programs can provide a quicker entry point into technology fields, giving students valuable skills and credentials in less time.

Cost is always a concern, but there are many affordable online colleges that offer high-quality computer science education. Choosing the right online degree or pathway can help set you up for future success in a wide range of tech careers.

Best Scientists Citing Sayan Mukherjee

Trending Scientists

Recently Published Articles