World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
41
Citations
6557
World Ranking
1924
National Ranking
823

Computer Science

D-Index
42
Citations
6650
World Ranking
8468
National Ranking
3620

Alessandro Rinaldo 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 Alessandro Rinaldo 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.

Alessandro Rinaldo 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 Alessandro Rinaldo 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: 41 D-Index — 49th percentile

49% of scientists in this discipline score the same or lower.

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

Overview

Alessandro Rinaldo is affiliated with The University of Texas at Austin in the United States. Their research primarily focuses on mathematics, with a particular emphasis on statistics and probability.

The main fields of study that shape their work include:

  • Mathematics

Their research spans several subfields, including:

  • Statistics and Probability
  • Artificial Intelligence
  • Management Science and Operations Research
  • Statistics, Probability and Uncertainty
  • Molecular Biology

Alessandro Rinaldo's research covers a variety of topics, such as:

  • Statistical Methods and Inference
  • Statistical Methods and Bayesian Inference
  • Advanced Statistical Methods and Models
  • Advanced Statistical Process Monitoring
  • Statistical Methods in Clinical Trials
  • Advanced Bandit Algorithms Research
  • Random Matrices and Applications

The scientist has published numerous papers, among the recent notable works are:

  • "Univariate mean change point detection: Penalization, CUSUM and optimality" (2020) in Electronic Journal of Statistics
  • "Optimal change point detection and localization in sparse dynamic networks" (2021) in The Annals of Statistics
  • "Optimal Nonparametric Multivariate Change Point Detection and Localization" (2021) in IEEE Transactions on Information Theory
  • "Optimal covariance change point localization in high dimensions" (2020) in Bernoulli
  • "A note on online change point detection" (2023) in Sequential Analysis

Their publications are frequently presented in venues such as:

  • arXiv (Cornell University)
  • Warwick Research Archive Portal (University of Warwick)
  • Electronic Journal of Statistics
  • IEEE Transactions on Information Theory
  • SIAM Journal on Mathematics of Data Science

Alessandro Rinaldo collaborates regularly with several coauthors, including:

  • Yi Yu
  • Daren Wang
  • Oscar Hernán Madrid Padilla
  • Arun Kumar Kuchibhotla
  • Aaditya Ramdas

Best Publications

  • Consistency of spectral clustering in stochastic block models

    Jing Lei;Alessandro Rinaldo

  • Distribution-Free Predictive Inference for Regression

    Jing Lei;Max G'Sell;Alessandro Rinaldo;Ryan J. Tibshirani

  • Confidence sets for persistence diagrams

    Brittany Therese Fasy;Fabrizio Lecci;Alessandro Rinaldo;Larry Wasserman

  • CONSISTENCY UNDER SAMPLING OF EXPONENTIAL RANDOM GRAPH MODELS

    Cosma Rohilla Shalizi;Alessandro Rinaldo

  • On the asymptotic properties of the group lasso estimator for linear models

    Yuval Nardi;Alessandro Rinaldo

  • Properties and refinements of the fused lasso

    Alessandro Rinaldo

  • Generalized density clustering

    Alessandro Rinaldo;Larry Wasserman

  • Autoregressive process modeling via the Lasso procedure

    Y. Nardi;A. Rinaldo

  • On the geometry of discrete exponential families with application to exponential random graph models

    Alessandro Rinaldo;Stephen E. Fienberg;Yi Zhou

  • Differential privacy for functions and functional data

    Rob Hall;Alessandro Rinaldo;Larry Wasserman

  • Stochastic Convergence of Persistence Landscapes and Silhouettes

    Frédéric Chazal;Brittany Terese Fasy;Fabrizio Lecci;Alessandro Rinaldo

  • Robust Topological Inference: Distance To a Measure and Kernel Distance

    Frédéric Chazal;Brittany Terese Fasy;Fabrizio Lecci;Bertrand Michel

  • Maximum likelihood estimation in log-linear models

    Stephen E. Fienberg;Alessandro Rinaldo

  • Characterization of multilocus linkage disequilibrium.

    Alessandro Rinaldo;Silviu-Alin Bacanu;B. Devlin;Vibhor Sonpar

  • Three centuries of categorical data analysis: Log-linear models and maximum likelihood estimation

    Stephen E. Fienberg;Alessandro Rinaldo

  • Differential privacy and the risk-utility tradeoff for multi-dimensional contingency tables

    Stephen E. Fienberg;Alessandro Rinaldo;Xiaolin Yang

  • Uniform asymptotic inference and the bootstrap after model selection

    Ryan J. Tibshirani;Alessandro Rinaldo;Robert Tibshirani;Larry Wasserman

  • Subsampling Methods for Persistent Homology

    Frederic Chazal;Brittany Fasy;Fabrizio Lecci;Bertrand Michel

  • A conformal prediction approach to explore functional data

    Jing Lei;Alessandro Rinaldo;Larry Wasserman

  • Stochastic convergence of persistence landscapes and silhouettes

    Frédéric Chazal;Brittany Terese Fasy;Fabrizio Lecci;Alessandro Rinaldo

  • Statistical Inference For Persistent Homology: Confidence Sets For Persistence Diagrams

    Brittany Terese Fasy;Fabrizio Lecci;Alessandro Rinaldo;Larry Wasserman

Frequent Co-Authors

Larry Wasserman
Larry Wasserman Carnegie Mellon University
Aarti Singh
Aarti Singh Carnegie Mellon University
Stephen E. Fienberg
Stephen E. Fienberg Carnegie Mellon University
Frédéric Chazal
Frédéric Chazal French Institute for Research in Computer Science and Automation - INRIA
Ryan J. Tibshirani
Ryan J. Tibshirani University of California, Berkeley
Rebecca Willett
Rebecca Willett University of Chicago
Steffen L. Lauritzen
Steffen L. Lauritzen University of Copenhagen
Barnabás Póczos
Barnabás Póczos Carnegie Mellon University
Robert Tibshirani
Robert Tibshirani Stanford University
Timothy Verstynen
Timothy Verstynen Carnegie Mellon University

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