Hazar Harmouch
- Computer Networks and Communications top 10%
- Artificial Intelligence
- Management Science and Operations Research top 10%
- Information Systems top 10%
- Signal Processing
- Co-authors
- Felix NaumannLaure Berti‐ÉquilleSaravanan ThirumuruganathanThorsten PapenbrockSebastian KruseLan JiangLisa EhrlingerDivesh Srivastava
- Topics
- Data Quality and Management (9 papers)Data Mining Algorithms and Applications (6 papers)Data Management and Algorithms (3 papers)
- Cited by
- Management Science and Operations ResearchSignal ProcessingComputer Networks and Communications
- Partner nations
- GermanyNetherlandsQatar
In The Last Decade
Hazar Harmouch
8 papers receiving 164 citations
Hit Papers
Peers
Comparison fields: 5 of 37
- Computer Networks and Communications 80
- Artificial Intelligence 74
- Management Science and Operations Research 68
- Information Systems 51
- Signal Processing 40
Countries citing papers authored by Hazar Harmouch
This map shows the geographic impact of Hazar Harmouch'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 Hazar Harmouch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hazar Harmouch more than expected).
Fields of papers citing papers by Hazar Harmouch
This network shows the impact of papers produced by Hazar Harmouch. 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 Hazar Harmouch. The network helps show where Hazar Harmouch may publish in the future.
Co-authorship network of co-authors of Hazar Harmouch
This figure shows the co-authorship network connecting the top 25 collaborators of Hazar Harmouch. A scholar is included among the top collaborators of Hazar Harmouch 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 Hazar Harmouch. Hazar Harmouch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | The effects of data quality on machine learning performance on tabular databreakdown → | 29 |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 10 | |
| 7 | 40 | |
| 8 | 24 | |
| 9 | 55 | |
| 10 | Data Anamnesis: Admitting Raw Data into an Organization. | 8 |
About Hazar Harmouch
Hazar Harmouch is a scholar working on Management Science and Operations Research, Information Systems and Signal Processing, having authored 10 papers that have together received 170 indexed citations. Recurring topics across this work include Data Quality and Management (9 papers), Data Mining Algorithms and Applications (6 papers) and Data Management and Algorithms (3 papers). The work is most often cited by research in Management Science and Operations Research (68 citations), Signal Processing (40 citations) and Computer Networks and Communications (80 citations). Hazar Harmouch has collaborated with scholars based in Germany, Netherlands and Qatar. Frequent co-authors include Felix Naumann, Laure Berti‐Équille, Saravanan Thirumuruganathan, Thorsten Papenbrock, Sebastian Kruse, Lan Jiang, Lisa Ehrlinger, Divesh Srivastava, David R. Jackson and Paul Groth. Their work appears in journals such as Proceedings of the VLDB Endowment, ACM SIGMOD Record and Information Systems.
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.