World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
33
Citations
6869
World Ranking
3001
National Ranking
1211

Vladimir Koltchinskii publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Vladimir Koltchinskii sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 122 publications — 22nd percentile

22% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

Vladimir Koltchinskii D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Vladimir Koltchinskii sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 33 D-Index — 17th percentile

17% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Overview

Vladimir Koltchinskii is affiliated with the Georgia Institute of Technology in the United States. Their research primarily spans the field of Mathematics, with a focus on Statistics and Probability as the main subfield, alongside contributions in Artificial Intelligence, Finance, Applied Mathematics, and Mathematical Physics.

The scientist has produced work concentrated around several core topics, including Statistical Methods and Inference, Bayesian Methods and Mixture Models, Markov Chains and Monte Carlo Methods, Stochastic Processes and Financial Applications, Mathematical Analysis and Transform Methods, Random Matrices and Applications, and Statistical Methods and Bayesian Inference.

Recent publications by Vladimir Koltchinskii include:

  • Estimation of smooth functionals in high-dimensional models: Bootstrap chains and Gaussian approximation, 2022, The Annals of Statistics
  • Estimation of smooth functionals in normal models: Bias reduction and asymptotic efficiency, 2021, The Annals of Statistics
  • Asymptotically efficient estimation of smooth functionals of covariance operators, 2020, Journal of the European Mathematical Society
  • Estimation of Smooth Functionals of Location Parameter in Gaussian and Poincaré Random Shift Models, 2021, Sankhya A
  • Efficient estimation of smooth functionals in Gaussian shift models, 2021, Annales de l'Institut Henri Poincaré Probabilités et Statistiques

The venues in which the scientist frequently publishes include:

  • arXiv (Cornell University)
  • The Annals of Statistics
  • Annales de l'Institut Henri Poincaré Probabilités et Statistiques
  • Journal of the European Mathematical Society
  • Sankhya A

Collaborations formed a notable part of Koltchinskii's work, with frequent coauthors comprising Mayya Zhilova, Martin Wahl, Matthias Löffler, Richard Nickl, and Minghao Li. These collaborations reflect involvement in interdisciplinary dialogues within statistical and mathematical research.

Best Publications

  • Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion

    Vladimir Koltchinskii;Karim Lounici;Alexandre B. Tsybakov

  • Empirical margin distributions and bounding the generalization error of combined classifiers

    V. Koltchinskii;D. Panchenko

  • Rademacher penalties and structural risk minimization

    V. Koltchinskii

  • Local Rademacher complexities and oracle inequalities in risk minimization

    Vladimir Koltchinskii

  • Oracle inequalities in empirical risk minimization and sparse recovery problems

    Vladimir Koltchinskii;École d'été de probabilités de Saint-Flour

  • High Dimensional Probability

    Unknown

  • Rademacher Processes and Bounding the Risk of Function Learning

    Unknown

  • Concentration inequalities and moment bounds for sample covariance operators

    Vladimir Koltchinskii;Karim Lounici

  • M-estimation, convexity and quantiles

    Unknown

  • SPARSITY IN MULTIPLE KERNEL LEARNING

    Vladimir Koltchinskii;Ming Yuan

  • Oracle Inequalities in Empirical Risk Minimization and Sparse Recovery Problems: École d'Été de Probabilités de Saint-Flour XXXVIII-2008

    Vladimir Koltchinskii;Ecole d'été de probabilités de Saint-Flour

  • Bounding the Smallest Singular Value of a Random Matrix Without Concentration

    Vladimir Koltchinskii;Shahar Mendelson

  • Sparsity in penalized empirical risk minimization

    Vladimir Koltchinskii

  • Empirical graph Laplacian approximation of Laplace–Beltrami operators: Large sample results

    Evarist Giné;Vladimir Koltchinskii

  • Random matrix approximation of spectra of integral operators

    Vladimir Koltchinskii;Evarist Giné

  • The Dantzig selector and sparsity oracle inequalities

    Vladimir Koltchinskii

  • Concentration inequalities and asymptotic results for ratio type empirical processes

    Evarist Giné;Vladimir Koltchinskii

  • Von Neumann entropy penalization and low-rank matrix estimation

    Vladimir Koltchinskii

  • Rademacher Complexities and Bounding the Excess Risk in Active Learning

    Vladimir Koltchinskii

  • Asymptotics and concentration bounds for bilinear forms of spectral projectors of sample covariance

    Vladimir Koltchinskii;Karim Lounici

  • Normal approximation and concentration of spectral projectors of sample covariance

    Vladimir Koltchinskii;Karim Lounici

  • Nuclear norm penalization and optimal rates for noisy low rank matrix completion

    Vladimir Koltchinskii;Alexandre B. Tsybakov;Karim Lounici

  • Complexities of convex combinations and bounding the generalization error in classification

    Vladimir Koltchinskii;Dmitry Panchenko

  • Sparsity in multiple kernel learning

    Vladimir Koltchinskii;Ming Yuan

  • Rejoinder: Local Rademacher complexities and oracle inequalities in risk minimization

    Vladimir Koltchinskii

Frequent Co-Authors

Alexandre B. Tsybakov
Alexandre B. Tsybakov École Nationale de la Statistique et de l'Administration Économique
Evarist Giné
Evarist Giné University of Connecticut
Ming Yuan
Ming Yuan Columbia University
Shahar Mendelson
Shahar Mendelson Texas A&M University
Bin Yu
Bin Yu University of California, Berkeley
Dominique Picard
Dominique Picard Université Paris Cité
Olivier Bousquet
Olivier Bousquet Google (United States)
Peter L. Bartlett
Peter L. Bartlett University of California, Berkeley
Jon A. Wellner
Jon A. Wellner University of Washington

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