E. J. Williams

6.4k citations
71 papers · 2.2k indexed · 1 hit paper · h-index 23
Topics
Advanced Statistical Methods and Models (10 papers)Physics of Superconductivity and Magnetism (4 papers)Statistical Methods and Bayesian Inference (4 papers)
Journals
NatureSHILAP Revista de lepidopterologíaPhysical review. B, Condensed matter

In The Last Decade

E. J. Williams

62 papers receiving 2.0k citations

Hit Papers

The Comparison of Regression Variables19592026198120031959100200300400

Peers

E. J. Williams
Comparison fields: 5 of 192
  • Molecular Biology 486
  • Statistics and Probability 377
  • Plant Science 280
  • Artificial Intelligence 152
  • Genetics 142
Replace Charles L. Odoroff with:
Charles L. Odoroff United States
P. McCullagh United Kingdom
Leone Y. Low United States
C F Starmer United States
Gary W. Oehlert United States
Andrew A. Neath United States
Neil H. Timm United States
Eugene S. Edgington Canada
Christian Hennig United Kingdom
Kathleen Kocherlakota Canada
E. J. Williams relative to Charles L. Odoroff United States Charles L. Odoroff's profile →
Citations per field
00.5×5.6×
Charles L. Odoroff · 1×
Citations per year

Countries citing papers authored by E. J. Williams

Since Specialization
Citations

This map shows the geographic impact of E. J. Williams's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by E. J. Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites E. J. Williams more than expected).

Fields of papers citing papers by E. J. Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by E. J. Williams. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by E. J. Williams. The network helps show where E. J. Williams may publish in the future.

Co-authorship network of co-authors of E. J. Williams

This figure shows the co-authorship network connecting the top 25 collaborators of E. J. Williams. A scholar is included among the top collaborators of E. J. Williams based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with E. J. Williams. E. J. Williams is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 2
3 2
4 2
5 15
6 9
7 1
8 22
9 139
10 14
11 1
12 235
13 52
14 4
15 2
16 3
17 5
18 4
19 35
20 7

About E. J. Williams

E. J. Williams is a scholar working on Statistics and Probability, Applied Mathematics and Mathematical Physics, having authored 71 papers that have together received 2.2k indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (10 papers), Physics of Superconductivity and Magnetism (4 papers) and Statistical Methods and Bayesian Inference (4 papers). The work is most often cited by research in Statistics and Probability (377 citations), Computational Mathematics (8 citations) and Statistics, Probability and Uncertainty (86 citations). E. J. Williams has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include G. S. Watson, C. I. Bliss, Lee H. Wong, Melissa A. Anderson, Margaret Shaw, Richard Saffery, Ross D. Hannan, Emma L. Northrop, Julie Quach and F. N. David. Their work appears in journals such as Nature, SHILAP Revista de lepidopterología and Physical review. B, Condensed matter.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact

Rankless by CCL
2026