Manuel J. A. Eugster
- Artificial Intelligence top 5%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Cognitive Neuroscience top 10%
- Statistics and Probability top 5%
- Co-authors
- Friedrich LeischSamuel KaskiTuukka RuotsaloGiulio JacucciAnne‐Laure BoulesteixSabine LauerSohan SethIlkka Kosunen
- Topics
- Advanced Text Analysis Techniques (6 papers)Information Retrieval and Search Behavior (6 papers)Machine Learning and Data Classification (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEIEEE Transactions on Pattern Analysis and Machine Intelligence
In The Last Decade
Manuel J. A. Eugster
30 papers receiving 861 citations
Peers
Comparison fields: 5 of 131
- Artificial Intelligence 247
- Information Systems 160
- Computer Vision and Pattern Recognition 120
- Cognitive Neuroscience 107
- Statistics and Probability 83
Countries citing papers authored by Manuel J. A. Eugster
This map shows the geographic impact of Manuel J. A. Eugster'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 Manuel J. A. Eugster with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manuel J. A. Eugster more than expected).
Fields of papers citing papers by Manuel J. A. Eugster
This network shows the impact of papers produced by Manuel J. A. Eugster. 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 Manuel J. A. Eugster. The network helps show where Manuel J. A. Eugster may publish in the future.
Co-authorship network of co-authors of Manuel J. A. Eugster
This figure shows the co-authorship network connecting the top 25 collaborators of Manuel J. A. Eugster. A scholar is included among the top collaborators of Manuel J. A. Eugster 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 Manuel J. A. Eugster. Manuel J. A. Eugster is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | In-Line Documentation for R [R package roxygen2 version 7.1.1] | 1 |
| 2 | 42 | |
| 3 | 35 | |
| 4 | 7 | |
| 5 | 17 | |
| 6 | 22 | |
| 7 | Predicting Relevance of Text from Neuro-Physiology | 2 |
| 8 | 39 | |
| 9 | Interactive Visualization of Search Intent for Exploratory Information Retrieval | 1 |
| 10 | 63 | |
| 11 | 88 | |
| 12 | 59 | |
| 13 | 35 | |
| 14 | 7 | |
| 15 | 10 | |
| 16 | Benchmark Experiments A Tool for Analyzing Statistical Learning Algorithms | 9 |
| 17 | 19 | |
| 18 | From Spider-Man to Hero - Archetypal Analysis in R | 64 |
| 19 | 74 | |
| 20 | 27 |
About Manuel J. A. Eugster
Manuel J. A. Eugster is a scholar working on Statistics and Probability, Computer Science Applications and Information Systems and Management, having authored 31 papers that have together received 884 indexed citations. Recurring topics across this work include Advanced Text Analysis Techniques (6 papers), Information Retrieval and Search Behavior (6 papers) and Machine Learning and Data Classification (5 papers). The work is most often cited by research in Statistics and Probability (83 citations), Artificial Intelligence (247 citations) and Computer Science Applications (40 citations). Manuel J. A. Eugster has collaborated with scholars based in Finland, Germany and Austria. Frequent co-authors include Friedrich Leisch, Samuel Kaski, Tuukka Ruotsalo, Giulio Jacucci, Anne‐Laure Boulesteix, Sabine Lauer, Sohan Seth, Ilkka Kosunen, Petri Myllymäki and Dorota Głowacka. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.