World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
53
Citations
12054
World Ranking
4804
National Ranking
2236

Sridhar Mahadevan 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 Sridhar Mahadevan 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: 163 publications — 32nd percentile

32% of scientists in this discipline score the same or lower.

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

Sridhar Mahadevan 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 Sridhar Mahadevan 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: 53 D-Index — 67th percentile

67% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2014 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to the field of machine learning including pioneering work in robot learning and representation discovery.

Overview

Sridhar Mahadevan is affiliated with the University of Massachusetts Amherst in the United States. Their research primarily spans the field of Computer Science, with a significant focus on Artificial Intelligence, Computational Theory and Mathematics, and Management Science and Operations Research. Additional subfields include Signal Processing and Computer Vision and Pattern Recognition.

Their work addresses various advanced topics, encompassing Bayesian Modeling and Causal Inference, Rough Sets and Fuzzy Logic, Topological and Geometric Data Analysis, Advanced Bandit Algorithms Research, Auction Theory and Applications, Non-Destructive Testing Techniques, and Infrastructure Maintenance and Monitoring.

Some recent papers authored by Sridhar Mahadevan include:

  • Finite-Sample Analysis of Proximal Gradient TD Algorithms, 2020, published in arXiv (Cornell University)
  • Manifold Warping: Manifold Alignment over Time, 2021, published in Proceedings of the AAAI Conference on Artificial Intelligence
  • Multi-fidelity physics-informed machine learning for probabilistic damage diagnosis, 2023, published in Reliability Engineering & System Safety
  • Regularized Off-Policy TD-Learning, 2020, published in arXiv (Cornell University)
  • Optimizing for the Future in Non-Stationary MDPs, 2020, published in arXiv (Cornell University)

Sridhar Mahadevan has frequently published in venues such as arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence, Entropy, Reliability Engineering & System Safety, and the 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

Frequent co-authors collaborating with Sridhar Mahadevan include:

  • Zhao Song
  • Georgios Theocharous
  • Sarah Miele
  • Pranav Karve
  • Ritwik Sinha

In 2014, Sridhar Mahadevan was recognized as a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) for contributions to machine learning research, including work in robot learning and representation discovery.

Best Publications

  • Recent Advances in Hierarchical Reinforcement Learning

    Andrew G. Barto;Sridhar Mahadevan

  • Automatic programming of behavior-based robots using reinforcement learning

    Sridhar Mahadevan;Jonathan Connell

  • LEAP: a learning apprentice for VLSI design

    Tom M. Mitchell;Sridbar Mahadevan;Louis I. Steinberg

  • Average reward reinforcement learning: foundations, algorithms, and empirical results

    Sridhar Mahadevan

  • Recent Advances in Hierarchical Reinforcement Learning

    Unknown

  • Heterogeneous domain adaptation using manifold alignment

    Chang Wang;Sridhar Mahadevan

  • Proto-value Functions: A Laplacian Framework for Learning Representation and Control in Markov Decision Processes

    Sridhar Mahadevan;Mauro Maggioni

  • Manifold alignment using Procrustes analysis

    Chang Wang;Sridhar Mahadevan

  • Generative Multi-Adversarial Networks

    Ishan P. Durugkar;Ian Gemp;Sridhar Mahadevan

  • Solving Semi-Markov Decision Problems Using Average Reward Reinforcement Learning

    Tapas K. Das;Abhijit Gosavi;Sridhar Mahadevan;Nicholas Marchalleck

  • Robot Learning

    Jonathan H. Connell;Sridhar Mahadevan

  • Manifold alignment without correspondence

    Chang Wang;Sridhar Mahadevan

  • Hierarchical multi-agent reinforcement learning

    Rajbala Makar;Sridhar Mahadevan;Mohammad Ghavamzadeh

  • Hierarchical multi-agent reinforcement learning

    Mohammad Ghavamzadeh;Sridhar Mahadevan;Rajbala Makar

  • Self-Improving Factory Simulation using Continuous-time Average-Reward Reinforcement Learning

    Sridhar Mahadevan;Tapas K. Das;Abhijit Gosavi

  • Robot Learning

    Unknown

  • A study of machine learning regression methods for major elemental analysis of rocks using laser-induced breakdown spectroscopy

    Thomas F. Boucher;Marie V. Ozanne;Marco L. Carmosino;M. Darby Dyar

  • Repairing Disengagement With Non-Invasive Interventions

    Ivon Arroyo;Kimberly Ferguson;Jeff Johns;Toby Dragon

  • Proto-value functions: developmental reinforcement learning

    Sridhar Mahadevan

  • Value Function Approximation with Diffusion Wavelets and Laplacian Eigenfunctions

    Sridhar Mahadevan;Mauro Maggioni

  • Finite-sample analysis of proximal gradient TD algorithms

    Bo Liu;Ji Liu;Mohammad Ghavamzadeh;Sridhar Mahadevan

  • Hierarchical Memory-Based Reinforcement Learning

    Natalia Hernandez-Gardiol;Sridhar Mahadevan

Frequent Co-Authors

Mohammad Ghavamzadeh
Mohammad Ghavamzadeh Amazon (United States)
Ji Liu
Ji Liu Facebook (United States)
M. Darby Dyar
M. Darby Dyar Mount Holyoke College
Jonathan H. Connell
Jonathan H. Connell IBM (United States)
Beverly Park Woolf
Beverly Park Woolf University of Massachusetts Amherst
Tom M. Mitchell
Tom M. Mitchell Carnegie Mellon University
Mauro Maggioni
Mauro Maggioni Johns Hopkins University
Andrew G. Barto
Andrew G. Barto University of Massachusetts Amherst
Samuel M. Clegg
Samuel M. Clegg Los Alamos National Laboratory
John M. Henderson
John M. Henderson University of California, Davis

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