Alex Aussem

874 citations
25 papers · 501 · h-index 14

Impact in

    • Neural Networks and Applications
    • Text and Document Classification Technologies
    • Bayesian Modeling and Causal Inference
    • Machine Learning and Data Classification

Papers in

Alex Aussem

25 papers receiving 468 citations

Peers

Alex Aussem
Comparison fields: 5 of 97
  • Artificial Intelligence 299
  • Signal Processing 56
  • Computer Vision and Pattern Recognition 104
  • Management Science and Operations Research 63
  • Computational Mathematics 2
Replace I. Cloete with:
I. Cloete South Africa
Long Thanh Ngo Vietnam
Héctor Allende Chile
Yunjie Zhang China
Alireza Farhangfar Canada
Yangguang Liu China
Xuewen Chen United States
M. Carmen Garrido Spain
Hanen Borchani Spain
Claudio Moraga Germany
Alex Aussem relative to I. Cloete South Africa I. Cloete's profile →
Citations per field
00.5×2.7×
I. Cloete · 1×
Citations per year

Countries citing papers authored by Alex Aussem

Since Specialization
Citations

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

Fields of papers citing papers by Alex Aussem

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Alex Aussem, 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 Alex Aussem Line = papers co-authored together Alex Aussem links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199772
2 201462
3 201359
4 201641
5 199939
6 201237
7 199530
8 200920
9 201019
10 200118
11 200918
12 201613
13 200013
14 201113
15 201011
16 20137
17 19997
18 20026
19 20194
20 20033

About Alex Aussem

Alex Aussem is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Signal Processing and Statistical and Nonlinear Physics, having authored 25 papers that have together received 501 indexed citations. Recurring topics across this work include Neural Networks and Applications (6 papers), Text and Document Classification Technologies (5 papers), Bayesian Modeling and Causal Inference (5 papers), Machine Learning and Data Classification (5 papers), Face and Expression Recognition (3 papers), Gene expression and cancer classification (3 papers), Neural Networks and Reservoir Computing (2 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). The work is most often cited by research in Artificial Intelligence (299 citations), Signal Processing (56 citations), Computer Vision and Pattern Recognition (104 citations), Management Science and Operations Research (63 citations) and Computational Mathematics (2 citations). Alex Aussem has collaborated with scholars based in France, United Kingdom and United States. Frequent co-authors include Haytham Elghazel, Fionn Murtagh, Maxime Gasse, M. Sarazin, Fionn Murtagh, David A. Hill, David R.C. Hill, André Tchernof, Sophie Rome and Antoine Mahul. Their work appears in journals such as Neurocomputing, Expert Systems with Applications, International Journal of Intelligent Systems, Pattern Analysis and Applications and BMC Bioinformatics.

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