World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
40
Citations
8994
World Ranking
2009
National Ranking
850

Engineering and Technology

D-Index
40
Citations
8997
World Ranking
7187
National Ranking
1959

Katya Scheinberg 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 Katya Scheinberg 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: 102 publications — 12th percentile

12% of scientists in this discipline score the same or lower.

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

Katya Scheinberg 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 Katya Scheinberg 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: 40 D-Index — 45th percentile

45% of scientists in this discipline score the same or lower.

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

Overview

Katya Scheinberg is affiliated with Cornell University in the United States and has contributed extensively to research in computer science and engineering. Their work mainly focuses on areas such as artificial intelligence, computational mechanics, management science and operations research, statistics and probability, and numerical analysis.

Key research topics explored in their publications include:

  • Stochastic Gradient Optimization Techniques
  • Sparse and Compressive Sensing Techniques
  • Advanced Bandit Algorithms Research
  • Advanced Optimization Algorithms Research
  • Markov Chains and Monte Carlo Methods
  • Neural Networks and Applications
  • Machine Learning and Algorithms

Katya Scheinberg has co-authored papers with several frequent collaborators, such as:

  • Lam M. Nguyen
  • Miaolan Xie
  • Albert S. Berahas
  • Liyuan Cao
  • Billy Jin

The scientist's research has appeared in multiple journal and conference venues, including:

  • arXiv (Cornell University)
  • SIAM Journal on Optimization
  • Mathematical Programming
  • Journal of Global Optimization
  • Foundations of Computational Mathematics

Notable recent publications by Katya Scheinberg include:

  • A Stochastic Line Search Method with Expected Complexity Analysis, 2020, SIAM Journal on Optimization
  • Optimal decision trees for categorical data via integer programming, 2021, Journal of Global Optimization
  • A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization, 2021, Foundations of Computational Mathematics
  • Feature engineering and forecasting via derivative-free optimization and ensemble of sequence-to-sequence networks with applications in renewable energy, 2020, Energy
  • Adaptive Stochastic Optimization: A Framework for Analyzing Stochastic Optimization Algorithms, 2020, IEEE Signal Processing Magazine

Best Publications

  • Introduction to derivative-free optimization

    Andrew R. Conn;Katya Scheinberg;Luis N. Vicente

  • Efficient svm training using low-rank kernel representations

    Shai Fine;Katya Scheinberg

  • SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient

    Lam M. Nguyen;Jie Liu;Katya Scheinberg;Martin Takáč

  • Recent progress in unconstrained nonlinear optimization without derivatives

    A. R. Conn;K. Scheinberg;Ph. L. Toint

  • Fast alternating linearization methods for minimizing the sum of two convex functions

    Donald Goldfarb;Shiqian Ma;Katya Scheinberg

  • Global Convergence of General Derivative-Free Trust-Region Algorithms to First- and Second-Order Critical Points

    Andrew R. Conn;Katya Scheinberg;Luís N. Vicente

  • On the convergence of derivative-free methods for unconstrained optimization

    Andy Conn;Katya Scheinberg;Philippe Toint

  • Efficient block-coordinate descent algorithms for the Group Lasso

    Zhiwei Qin;Katya Scheinberg;Donald Goldfarb

  • Sparse Inverse Covariance Selection via Alternating Linearization Methods

    Katya Scheinberg;Shiqian Ma;Donald Goldfarb

  • Geometry of interpolation sets in derivative free optimization

    A. R. Conn;K. Scheinberg;Luís N. Vicente

  • Stochastic optimization using a trust-region method and random models

    Ruobing Chen;Matt Menickelly;Katya Scheinberg

  • A derivative free optimization algorithm in practice

    A. Conn;K. Scheinberg;Ph. Toint

  • IBM Research TRECVID-2006 Video Retrieval System

    Murray Campbell;Alexander Haubold;Shahram Ebadollahi;Dhiraj Joshi

  • Global convergence rate analysis of unconstrained optimization methods based on probabilistic models

    Coralia Cartis;Katya Scheinberg

  • SGD and Hogwild! Convergence Without the Bounded Gradients Assumption

    Lam M. Nguyen;Phuong Ha Nguyen;Marten van Dijk;Peter Richtárik

  • Convergence of Trust-Region Methods Based on Probabilistic Models

    Afonso S. Bandeira;Katya Scheinberg;Luís Nunes Vicente

  • A Derivative-Free Algorithm for Least-Squares Minimization

    Hongchao Zhang;Andrew R. Conn;Katya Scheinberg

  • A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization

    Albert S. Berahas;Liyuan Cao;Krzysztof Choromanski;Katya Scheinberg

  • Interior Point Trajectories in Semidefinite Programming

    D. Goldfarb;K. Scheinberg

  • Least-squares approach to risk parity in portfolio selection

    Xi Bai;Katya Scheinberg;Reha Tutuncu

  • Geometry of sample sets in derivative-free optimization: polynomial regression and underdetermined interpolation

    Andrew R. Conn;Katya Scheinberg;Luís Nunes Vicente

Frequent Co-Authors

Luís Nunes Vicente
Luís Nunes Vicente Lehigh University
Donald Goldfarb
Donald Goldfarb Columbia University
Irina Rish
Irina Rish University of Montreal
Marten van Dijk
Marten van Dijk University of Connecticut
Shiqian Ma
Shiqian Ma Rice University
Peter Richtárik
Peter Richtárik King Abdullah University of Science and Technology
Jayant R. Kalagnanam
Jayant R. Kalagnanam IBM (United States)
Bhuvana Ramabhadran
Bhuvana Ramabhadran Google (United States)
Dimitri Kanevsky
Dimitri Kanevsky Google (United States)

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