András Prékopa

90 papers receiving 2.4k citations

Hit Papers

Stochastic Programming199520262005201519952505007501000

Peers

András Prékopa
Comparison fields: 5 of 116
  • Management Science and Operations Research 1.3k
  • Control and Systems Engineering 796
  • Statistics and Probability 534
  • Computational Theory and Mathematics 380
  • Statistics, Probability and Uncertainty 326
Replace Werner Römisch with:
Werner Römisch Germany
Darinka Dentcheva United States
Hsien-Chung Wu Taiwan
Berç Rüstem United Kingdom
Huifu Xu United Kingdom
François Oustry France
Włodzimierz Ogryczak Poland
Onésimo Hernández–Lerma Mexico
A. Hadi‐Vencheh Iran
Masahiro Inuiguchi Japan
András Prékopa relative to Werner Römisch Germany Werner Römisch's profile →
Citations per field
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Werner Römisch · 1×
Citations per year

Countries citing papers authored by András Prékopa

Since Specialization
Citations

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

Fields of papers citing papers by András Prékopa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of András Prékopa

This figure shows the co-authorship network connecting the top 25 collaborators of András Prékopa. A scholar is included among the top collaborators of András Prékopa 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 András Prékopa. András Prékopa 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 9
2 1
3 5
4 1
5 1
6 10
7 4
8
Sharp Bounds for the Probability of the Union of Events Under Unimodality Condition
5
9 1
10 9
11 34
12 11
13
DUAL METHODS FOR THE NUMERICAL SOLUTION OF THE UNIVARIATE POWER MOMENT PROBLEM
2
14 24
15 6
16 37
17
Studies in applied stochastic programming : 1.
2
18 12
19
Planning in interconnected power systems: An example of two-stage programming under uncertainty
1
20 7

About András Prékopa

András Prékopa is a scholar working on Management Science and Operations Research, Statistics and Probability and Numerical Analysis, having authored 93 papers that have together received 2.7k indexed citations. Recurring topics across this work include Risk and Portfolio Optimization (31 papers), Optimization and Mathematical Programming (16 papers) and Probabilistic and Robust Engineering Design (9 papers). The work is most often cited by research in Management Science and Operations Research (1.3k citations), Statistics and Probability (534 citations) and Statistics, Probability and Uncertainty (326 citations). András Prékopa has collaborated with scholars based in United States, Hungary and Netherlands. Frequent co-authors include Andrzej Ruszczyński, Darinka Dentcheva, Endre Boros, Tamás Szántai, József Bukszár, Wenzhong Li, Tamás Rapcsák, Tiina Heikkinen, István Zsuffa and Gabriela Alexe. Their work appears in journals such as Journal of the American Statistical Association, Technometrics and Water Resources Research.

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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