Ban Kawas

441 total citations
11 papers, 201 citations indexed

About

Ban Kawas is a scholar working on Management Science and Operations Research, Artificial Intelligence and Management Information Systems. According to data from OpenAlex, Ban Kawas has authored 11 papers receiving a total of 201 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Management Science and Operations Research, 4 papers in Artificial Intelligence and 3 papers in Management Information Systems. Recurrent topics in Ban Kawas's work include Risk and Portfolio Optimization (5 papers), Topic Modeling (4 papers) and Big Data and Business Intelligence (2 papers). Ban Kawas is often cited by papers focused on Risk and Portfolio Optimization (5 papers), Topic Modeling (4 papers) and Big Data and Business Intelligence (2 papers). Ban Kawas collaborates with scholars based in United States, Switzerland and Ireland. Ban Kawas's co-authors include Aurélie Thiele, Kun Qian, Yannis Katsis, Marina Danilevsky, Prithviraj Sen, Ranit Aharonov, Kush R. Varshney, Mark S. Squillante, Dharmashankar Subramanian and Marco Laumanns and has published in prestigious journals such as European Journal of Operational Research, IBM Journal of Research and Development and OR Spectrum.

In The Last Decade

Ban Kawas

11 papers receiving 191 citations

Peers

Ban Kawas
Comparison fields: 5 of 52
  • Artificial Intelligence 110
  • Management Science and Operations Research 56
  • Information Systems 23
  • Finance 22
  • Economics and Econometrics 22
Replace Milija Suknović with:
Milija Suknović Serbia
Iván Pastor Sanz Spain
Nathan Self United States
Elena Dumitrescu France
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Md Shajalal Bangladesh
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Sebastian Klaudiusz Tomczak Poland
Niklas Bussmann Italy
Milija Suknović Serbia View profile →
Citations per field, relative to Ban Kawas
Ban Kawas · 1×
Citations per year, relative to Ban Kawas
Ban Kawas · 1×

Countries citing papers authored by Ban Kawas

Since Specialization
Citations

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

Fields of papers citing papers by Ban Kawas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ban Kawas

This figure shows the co-authorship network connecting the top 25 collaborators of Ban Kawas. A scholar is included among the top collaborators of Ban Kawas 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 Ban Kawas. Ban Kawas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
# Work Indexed citations
1 13
2 3
3 103
4
Learning to Query, Reason, and Answer Questions On Ambiguous Texts
7
5 6
6 7
7 1
8 21
9 3
10 10
11 27

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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2026