Samba Ndiaye

22 papers receiving 156 citations

Peers

Samba Ndiaye
Comparison fields: 5 of 78
  • Health 17
  • Health Information Management 8
  • Signal Processing 13
  • Computational Theory and Mathematics 18
  • Artificial Intelligence 33
Replace V. Mohanraj with:
V. Mohanraj India
Kaleb E. Smith United States
Liya Fu China
Davide Sottara Italy
Aamir Saeed Pakistan
A. Vijayalakshmi India
Seungwan Hong South Korea
Gaurav Sethi India
K Ananthajothi India
Suneeta Satpathy India
Samba Ndiaye relative to V. Mohanraj India V. Mohanraj's profile →
Citations per field
00.5×
V. Mohanraj · 1×
Citations per year

Countries citing papers authored by Samba Ndiaye

Since Specialization
Citations

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

Fields of papers citing papers by Samba Ndiaye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Samba Ndiaye, 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 Samba Ndiaye Line = papers co-authored together Samba Ndiaye links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Novel RFE-SVM-based Feature Selection Approach for Classification
201534
2 202017
3 202311
4 201711
5 202110
6 202210
7
[Smoking habits among physicians in Dakar].
20019
8 20029
9 20217
10 20197
11 20097
12
Dynamic heuristics for backtrack search on tree-decomposition of CSPs
20076
13
Privacy Preserving RFE-SVM for Distributed Gene Selection
20126
14
Max-CSP competition 2008: toulbar2 solver description
20085
15 20223
16 20182
17 20142
18 20172
19 20231
20 20141

About Samba Ndiaye

Samba Ndiaye is a scholar working on Computer Networks and Communications, Signal Processing, Information Systems, Civil and Structural Engineering and Artificial Intelligence, having authored 28 papers that have together received 162 indexed citations. Recurring topics across this work include Data Management and Algorithms (5 papers), Constraint Satisfaction and Optimization (4 papers), Advanced Database Systems and Queries (3 papers), Data Mining Algorithms and Applications (3 papers), Concrete and Cement Materials Research (3 papers), Advanced Graph Theory Research (2 papers), Machine Learning and Data Classification (2 papers) and Autopsy Techniques and Outcomes (1 paper). The work is most often cited by research in Health (17 citations), Health Information Management (8 citations), Signal Processing (13 citations), Computational Theory and Mathematics (18 citations) and Artificial Intelligence (33 citations). Samba Ndiaye has collaborated with scholars based in Senegal, France and Belgium. Frequent co-authors include Yahya Slimani, Philippe Jégou, Laurent Cassayre, Patrick Peretti‐Watel, Valérie Seror, Séverine Camy, Ibrahima Gaye, Sébastien Cortaredona, M.-A. Neimat and Florent Bourgeois. Their work appears in journals such as Human Vaccines & Immunotherapeutics, Discrete Mathematics, Data & Knowledge Engineering, ACS Sustainable Chemistry & Engineering and BMC Public Health.

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