Jan Engel

1.1k citations
38 papers · 648 · h-index 14

Impact in

Papers in

Jan Engel

36 papers receiving 606 citations

Peers

Jan Engel
Comparison fields: 5 of 123
  • Statistics and Probability 132
  • Statistics, Probability and Uncertainty 111
  • Management Science and Operations Research 168
  • Industrial and Manufacturing Engineering 46
  • Computational Theory and Mathematics 69
Replace John J. Borkowski with:
John J. Borkowski United States
Dayanand N. Naik United States
Ernest M. Scheuer United States
Spencer Graves United States
Robert N. Rodriguez United States
Ping Chen China
J. Susan Milton United States
L. C. A. Corsten Netherlands
Jérôme Saracco France
Joan Fisher Box
Jan Engel relative to John J. Borkowski United States John J. Borkowski's profile →
Citations per field
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John J. Borkowski · 1×
Citations per year

Countries citing papers authored by Jan Engel

Since Specialization
Citations

This map shows the geographic impact of Jan Engel'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 Jan Engel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Engel more than expected).

Fields of papers citing papers by Jan Engel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jan Engel. 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 Jan Engel. The network helps show where Jan Engel may publish in the future.

Co-authors

The 25 scholars most cited alongside Jan Engel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jan Engel Line = papers co-authored together Jan Engel links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 198886
2 199659
3 200553
4 198451
5 199649
6 201948
7 199241
8 199136
9 201735
10 201130
11 201228
12 202223
13 198016
14 199714
15 199610
16 20208
17 20247
18 20136
19 19986
20 20145

About Jan Engel

Jan Engel is a scholar working on Management Science and Operations Research, Statistics and Probability, Statistics, Probability and Uncertainty, Global and Planetary Change and Industrial and Manufacturing Engineering, having authored 38 papers that have together received 648 indexed citations. Recurring topics across this work include Optimal Experimental Design Methods (8 papers), Statistical Distribution Estimation and Applications (6 papers), Manufacturing Process and Optimization (4 papers), Probabilistic and Robust Engineering Design (4 papers), Advanced Statistical Process Monitoring (4 papers), Statistical Methods and Bayesian Inference (3 papers), Plant responses to elevated CO2 (3 papers) and Bayesian Methods and Mixture Models (3 papers). The work is most often cited by research in Statistics and Probability (132 citations), Statistics, Probability and Uncertainty (111 citations), Management Science and Operations Research (168 citations), Industrial and Manufacturing Engineering (46 citations) and Computational Theory and Mathematics (69 citations). Jan Engel has collaborated with scholars based in Netherlands, Germany and United States. Frequent co-authors include Karin Frank, Andreas Huth, Sönke Zaehle, Silvia Caldararu, Bert de Vries, Anne Ebeling, Lin Yu, Melanie Kern, Reiner Schnur and Tea Thum. Their work appears in journals such as Technometrics, Journal of Applied Probability, Journal of the Royal Statistical Society Series C (Applied Statistics), Biogeosciences and Displays.

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.

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