World's Best Scientists 2026 revealed!

Alexander G. Tartakovsky 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 Alexander G. Tartakovsky 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+

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

Alexander G. Tartakovsky 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 Alexander G. Tartakovsky 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+

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

Overview

Alexander G. Tartakovsky is affiliated with the Moscow Institute of Physics and Technology in the Russian Federation. Their research spans key areas in decision sciences and mathematics, with a particular focus on statistical methods and applications in complex systems monitoring and detection.

The scientist's work primarily contributes to the fields of:

  • Decision Sciences
  • Mathematics

Tartakovsky's subfields of study cover:

  • Statistics, Probability and Uncertainty
  • Statistics and Probability
  • Emergency Medical Services
  • Control and Systems Engineering
  • Computer Networks and Communications

Their main research topics include:

  • Advanced Statistical Process Monitoring
  • Statistical Methods and Inference
  • Advanced Statistical Methods and Models
  • Statistical Methods in Clinical Trials
  • Healthcare Operations and Scheduling Optimization
  • Fault Detection and Control Systems
  • Scientific Measurement and Uncertainty Evaluation

Alexander G. Tartakovsky has published extensively in various venues, with frequent publications in:

  • arXiv (Cornell University)
  • Proceedings of Moscow Institute of Physics and Technology
  • IEEE Transactions on Signal Processing
  • IEEE Transactions on Information Theory
  • Sequential Analysis

Notable recent papers authored or coauthored by Tartakovsky include:

  • Optimal Sequential Detection of Signals With Unknown Appearance and Disappearance Points in Time, 2021, IEEE Transactions on Signal Processing
  • Nearly Optimal Adaptive Sequential Tests for Object Detection, 2020, IEEE Transactions on Signal Processing

Additional related works appearing under coauthors include:

  • Quickest Change Detection With Non-Stationary Post-Change Observations, 2022, IEEE Transactions on Information Theory
  • Minimax and Pointwise Sequential Changepoint Detection and Identification for General Stochastic Models, 2022, Journal of Multivariate Analysis
  • Detecting an Intermittent Change of Unknown Duration, 2023, Sequential Analysis

Frequent collaborators of Tartakovsky include:

  • V.S. Spivak
  • N.R. Berenkov
  • Grigory Sokolov
  • Yuchen Liang
  • Venugopal V. Veeravalli

Best Publications

  • Sequential Analysis: Hypothesis Testing and Changepoint Detection

    Alexander Tartakovsky;Igor Nikiforov;Michele Basseville

  • A novel approach to detection of intrusions in computer networks via adaptive sequential and batch-sequential change-point detection methods

    A.G. Tartakovsky;B.L. Rozovskii;R.B. Blazek;Hongjoong Kim

  • General Asymptotic Bayesian Theory of Quickest Change Detection

    A. G. Tartakovsky;V. V. Veeravalli

  • Detection of intrusions in information systems by sequential change-point methods

    Alexander G. Tartakovsky;Boris L. Rozovskii;Rudolf B. Blažek;Hongjoong Kim

  • A novel approach to detection of \denial{of{service" attacks via adaptive sequential and batch{sequential change{point detection methods

    Boris Rozovskii;Alexander Tartakovsky

  • Asymptotically Optimal Quickest Change Detection in Distributed Sensor Systems

    Alexander G. Tartakovsky;Venugopal Varadachari Veeravalli

  • Efficient Computer Network Anomaly Detection by Changepoint Detection Methods

    A. G. Tartakovsky;A. S. Polunchenko;G. Sokolov

  • State-of-the-Art in Sequential Change-Point Detection

    Aleksey S. Polunchenko;Alexander G. Tartakovsky

  • Asymptotic Performance of a Multichart CUSUM Test Under False Alarm Probability Constraint

    A.G. Tartakovsky

  • ON OPTIMALITY PROPERTIES OF THE SHIRYAEV-ROBERTS PROCEDURE

    Moshe Pollak;Alexander G. Tartakovsky

  • Sequential detection of targets in multichannel systems

    A.G. Tartakovsky;X.R. Li;G. Yaralov

  • Asymptotic Optimality of Certain Multihypothesis Sequential Tests: Non‐i.i.d. Case

    Alexander G. Tartakovsky

  • Quickest change detection in distributed sensor systems

    A.G. Tartakovsky;V.V. Veeravalli

  • State-of-the-Art in Bayesian Changepoint Detection

    Alexander G. Tartakovsky;George V. Moustakides

  • A NUMERICAL APPROACH TO PERFORMANCE ANALYSIS OF QUICKEST CHANGE-POINT DETECTION PROCEDURES

    George V. Moustakides;Aleksey S. Polunchenko;Alexander G. Tartakovsky

  • Modeling Temporal Activity Patterns in Dynamic Social Networks

    Vasanthan Raghavan;Greg Ver Steeg;Aram Galstyan;Alexander G. Tartakovsky

  • Third-order Asymptotic Optimality of the Generalized Shiryaev--Roberts Changepoint Detection Procedures

    Alexander G. Tartakovsky;Moshe Pollak;Aleksey S. Polunchenko

  • An efficient sequential procedure for detecting changes in multichannel and distributed systems

    A.G. Tartakovsky;V.V. Veeravalli

  • Asymptotic Optimality of Change-Point Detection Schemes in General Continuous-Time Models

    M. Baron;A. G. Tartakovsky

  • Asymptotically optimal sequential tests for nonhomogeneous processes

    Alexander Tartakovsky

Frequent Co-Authors

Venugopal V. Veeravalli
Venugopal V. Veeravalli University of Illinois at Urbana-Champaign
George V. Moustakides
George V. Moustakides University of Illinois at Urbana-Champaign
Aram Galstyan
Aram Galstyan University of Southern California
Michèle Basseville
Michèle Basseville Institut de Recherche en Informatique et Systèmes Aléatoires
Andrea L. Bertozzi
Andrea L. Bertozzi University of California, Los Angeles
X. Rong Li
X. Rong Li University of New Orleans
Yaakov Bar-Shalom
Yaakov Bar-Shalom University of Connecticut
Gerard Medioni
Gerard Medioni Amazon (United States)

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 computer science in the USA opens the door to many related online degree programs and career paths. If you have a technical mindset, pursuing an electrical engineering degree online admissions route can provide an excellent foundation in both software and hardware skills. These online programs often offer flexible schedules perfect for working learners.

Many students look for credentials that provide a fast return on investment. There are numerous certifications for jobs which can boost your employability in tech-related roles without a lengthy time commitment. These certifications can be particularly helpful if you want to quickly upgrade your skills for specialized positions.

Some professionals seek advanced qualifications that can be completed quickly. The quickest masters degree online options allow you to earn a master’s degree—sometimes within a year—helping you get ahead in competitive industries.

It’s also wise to explore the most in demand masters degrees that align with your goals. Specializations in data science, cybersecurity, and AI are highly sought after, providing strong pathways to lucrative and future-proof careers.

Best Scientists Citing Alexander G. Tartakovsky

Trending Scientists