World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
37
Citations
4991
World Ranking
2533
National Ranking
1051

Computer Science

D-Index
37
Citations
5151
World Ranking
10853
National Ranking
4518

Richard Beigel 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 Richard Beigel 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: 113 publications — 17th percentile

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

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

Richard Beigel 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 Richard Beigel 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: 37 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

Richard Beigel is affiliated with Temple University in the United States and focuses their research primarily in the fields of medicine and computer science.

The main areas of study associated with their work include:

  • Medicine
  • Computer Science

Their subfields of specialization are equally interdisciplinary, covering:

  • Infectious Diseases
  • Artificial Intelligence
  • Epidemiology
  • Modeling and Simulation

Their research topics provide a detailed glimpse into their contributions, notably in relation to pandemic-related challenges and computational methods for disease surveillance. These topics are:

  • SARS-CoV-2 detection and testing
  • Machine Learning and Algorithms
  • Data-Driven Disease Surveillance
  • COVID-19 epidemiological studies
  • SARS-CoV-2 and COVID-19 Research

Richard Beigel has published research primarily in two venues:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • medRxiv

Their recent notable papers include:

  • "Rate Estimation and Identification of COVID-19 Infections: Towards Rational Policy Making During Early and Late Stages of Epidemics" (2020) published in bioRxiv (Cold Spring Harbor Laboratory)
  • "A Partition-Based Group Testing Algorithm for Estimating the Number of Infected Individuals" (2021) published in medRxiv
  • "A Partition-Based Group Testing Algorithm for Estimating the Number of Infected Individuals" (2021) published in bioRxiv (Cold Spring Harbor Laboratory)

Frequent collaborators include:

  • Max J. Webber
  • Simon Kasif

Best Publications

  • PP is closed under intersection

    Richard Beigel;Nick Reingold;Daniel Spielman

  • On ACC

    Richard Beigel;Jun Tarui

  • Representing Boolean functions as polynomials modulo composite numbers

    David A. Mix Barrington;Richard Beigel;Steven Rudich

  • The expressive power of voting polynomials

    James Aspnes;Richard Beigel;Merrick L. Furst;Steven Rudich

  • OC1: randomized induction of oblique decision trees

    Sreerama Murthy;Simon Kasif;Steven Salzberg;Richard Beigel

  • The polynomial method in circuit complexity

    R. Beigel

  • Bounded queries to SAT and the Boolean hierarchy

    Richard Beigel

  • 3-coloring in time O (1.3289 n )

    Richard Beigel;David Eppstein

  • Counting classes: thresholds, parity, mods, and fewness

    Richard Beigel;John Gill;Ulrich Hertrampf

  • Approximable Sets

    R. Beigel;M. Kummer;F. Stephan

  • Finding maximum independent sets in sparse and general graphs

    Richard Beigel

  • Some connections between bounded query classes and nonuniform complexity

    A. Amir;R. Beigel;W.I. Gasarch

  • Perceptrons, PP, and the polynomial hierarchy

    R. Beigel

  • Query-limited reducibilities

    Richard Beigel

  • Terse, superterse, and verbose sets

    Richard Beigel;William I. Gasarch;John Gill;James C. Owings

  • Learning a Hidden Matching

    Noga Alon;Richard Beigel;Simon Kasif;Steven Rudich

  • A computational framework for optimal masking in the synthesis of oligonucleotide microarrays

    Simon Kasif;Zhiping Weng;Adnan Derti;Richard Beigel

  • The perceptron strikes back

    R. Beigel;N. Reingold;D. Spielman

  • The expressive power of voting polynomials

    James Aspnes;Richard Beigel;Merrick Furst;Steven Rudich

  • A Relationship between Difference Hierarchies and Relativized Polynomial Hierarchies.

    Richard Beigel;Richard Chang;Mitsunori Ogiwara

  • Representing Boolean Functions as Polynomials Modulo Composite Numbers (Extended Abstract)

    David A. Mix Barrington;Richard Beigel;Steven Rudich

Frequent Co-Authors

Lance Fortnow
Lance Fortnow Illinois Institute of Technology
Simon Kasif
Simon Kasif Boston University
David Eppstein
David Eppstein University of California, Irvine
Noga Alon
Noga Alon Tel Aviv University
Harry Buhrman
Harry Buhrman University of Amsterdam
Daniel A. Spielman
Daniel A. Spielman Yale University
Amihood Amir
Amihood Amir Bar-Ilan University
Ben Shneiderman
Ben Shneiderman University of Maryland, College Park
Benny Sudakov
Benny Sudakov ETH Zurich
Eric Allender
Eric Allender Rutgers, The State University of New Jersey

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

Pursuing a Mathematics degree in the USA opens doors to various advanced study options and career paths. For those interested in leveraging quantitative skills, a data analytics master's degree offers a practical route into the booming field of data science and business intelligence. This degree combines mathematical expertise with cutting-edge technology to solve complex problems.

For students considering leadership roles or broader business knowledge, exploring the easiest MBA program to get into can be a strategic choice. These programs provide flexibility and accessibility, helping students gain essential management skills without intense admission pressures.

Many working professionals benefit from an easiest online MBA, which combines convenience with quality education. Online MBAs support balancing career growth with study, making it feasible for a wider range of students.

For those seeking senior-level advancement, pursuing a 1 year DBA program online is an efficient path. These Doctorate in Business Administration programs are designed for timely completion while deepening expertise in data-driven decision-making and leadership.

Best Scientists Citing Richard Beigel

Trending Scientists

Recently Published Articles