World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
4263
World Ranking
12262
National Ranking
4969

Alessandro Lazaric 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 Alessandro Lazaric 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: 188 publications — 42nd percentile

42% of scientists in this discipline score the same or lower.

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

Alessandro Lazaric 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 Alessandro Lazaric 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: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Overview

Alessandro Lazaric is affiliated with Facebook in the United States. Their research spans multiple areas within computer science and decision sciences, with a particular focus on artificial intelligence and operations research.

The scientist's main fields of study include:

  • Computer Science
  • Decision Sciences

Within these areas, their subfields of research comprise:

  • Artificial Intelligence
  • Management Science and Operations Research
  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Computational Theory and Mathematics

Lazaric's work covers a range of topics prominently featuring:

  • Advanced Bandit Algorithms Research
  • Reinforcement Learning in Robotics
  • Machine Learning and Algorithms
  • Data Stream Mining Techniques
  • Optimization and Search Problems
  • Age of Information Optimization
  • Stochastic Gradient Optimization Techniques

The scientist has an extensive publication record with frequent appearances in notable venues such as:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • SIAM Journal on Optimization
  • HAL (Le Centre pour la Communication Scientifique Directe)

Among their recent papers are:

  • "Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning" (2021), published in arXiv (Cornell University)
  • "Reinforcement Learning with Prototypical Representations" (2021), published in arXiv (Cornell University)
  • "Learning Near Optimal Policies with Low Inherent Bellman Error" (2020), published in arXiv (Cornell University)
  • "Sketched Newton--Raphson" (2022), published in SIAM Journal on Optimization
  • "Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning" (2022), published in arXiv (Cornell University)

Lazaric frequently collaborates with several researchers, including:

  • Matteo Pirotta
  • Andrea Tirinzoni
  • Jean Tarbouriech
  • Michal Vaľko
  • Evrard Garcelon

Best Publications

  • Transfer in Reinforcement Learning: a Framework and a Survey

    Alessandro Lazaric

  • Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence

    Victor Gabillon;Mohammad Ghavamzadeh;Alessandro Lazaric

  • Transfer of samples in batch reinforcement learning

    Alessandro Lazaric;Marcello Restelli;Andrea Bonarini

  • Linear Thompson Sampling Revisited

    Marc Abeille;Alessandro Lazaric

  • Reinforcement Learning in Continuous Action Spaces through Sequential Monte Carlo Methods

    Alessandro Lazaric;Marcello Restelli;Andrea Bonarini

  • Bayesian Multi-Task Reinforcement Learning

    Alessandro Lazaric;Mohammad Ghavamzadeh

  • Best-Arm Identification in Linear Bandits

    Marta Soare;Alessandro Lazaric;Remi Munos

  • Upper-confidence-bound algorithms for active learning in multi-armed bandits

    Alexandra Carpentier;Alessandro Lazaric;Mohammad Ghavamzadeh;Rémi Munos

  • Finite-sample analysis of least-squares policy iteration

    Alessandro Lazaric;Mohammad Ghavamzadeh;Rémi Munos

  • Multi-Bandit Best Arm Identification

    Victor Gabillon;Mohammad Ghavamzadeh;Alessandro Lazaric;Sébastien Bubeck

  • Risk-Aversion in Multi-armed Bandits

    Amir Sani;Alessandro Lazaric;Rémi Munos

  • Analysis of a Classification-based Policy Iteration Algorithm

    Alessandro Lazaric;Mohammad Ghavamzadeh;R mi Munos

  • Finite-Sample Analysis of LSTD

    Alessandro Lazaric;Mohammad Ghavamzadeh;R mi Munos

  • Sequential Transfer in Multi-armed Bandit with Finite Set of Models

    Mohammad Gheshlaghi azar;Alessandro Lazaric;Emma Brunskill

  • Reinforcement Learning of POMDPs using Spectral Methods

    Kamyar Azizzadenesheli;Alessandro Lazaric;Animashree Anandkumar

  • Learning Near Optimal Policies with Low Inherent Bellman Error

    Andrea Zanette;Alessandro Lazaric;Mykel Kochenderfer;Emma Brunskill

  • Reinforcement distribution in fuzzy Q-learning

    Andrea Bonarini;Alessandro Lazaric;Francesco Montrone;Marcello Restelli

  • Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning

    Ronan Fruit;Matteo Pirotta;Alessandro Lazaric;Ronald Ortner

  • Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning

    Denis Yarats;Rob Fergus;Alessandro Lazaric;Lerrel Pinto

  • LSTD with Random Projections

    Mohammad Ghavamzadeh;Alessandro Lazaric;Odalric Maillard;Rémi Munos

  • Sparse multi-task reinforcement learning

    Daniele Calandriello;Alessandro Lazaric;Marcello Restelli

  • Finite-Sample Analysis of Lasso-TD

    Mohammad Ghavamzadeh;Alessandro Lazaric;Matthew Hoffman;R mi Munos

  • Improved Learning Complexity in Combinatorial Pure Exploration Bandits

    Victor Gabillon;Alessandro Lazaric;Mohammad Ghavamzadeh;Ronald Ortner

  • Analysis of classification-based policy iteration algorithms

    Alessandro Lazaric;Mohammad Ghavamzadeh;Rémi Munos

Frequent Co-Authors

Mohammad Ghavamzadeh
Mohammad Ghavamzadeh Amazon (United States)
Emma Brunskill
Emma Brunskill Stanford University
Rémi Munos
Rémi Munos French Institute for Research in Computer Science and Automation - INRIA
Anima Anandkumar
Anima Anandkumar Nvidia (United Kingdom)
Mykel J. Kochenderfer
Mykel J. Kochenderfer Stanford University
Ludovic Denoyer
Ludovic Denoyer Sorbonne University
Nicolas Usunier
Nicolas Usunier Facebook (United States)
Peter Auer
Peter Auer University of Leoben
Simon S. Du
Simon S. Du University of Washington

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