Andrei Paleyes

698 citations
10 papers · 303 indexed · 1 hit paper · h-index 5
Topics
Software Engineering Research (3 papers)Software System Performance and Reliability (3 papers)Advanced Multi-Objective Optimization Algorithms (2 papers)
Journals
SHILAP Revista de lepidopterologíaACM Computing SurveysRoyal Society Open Science

In The Last Decade

Andrei Paleyes

8 papers receiving 289 citations

Hit Papers

Challenges in Deploying Machine Learning: A Survey of Cas...2022202620232024202250100150200250

Peers

Andrei Paleyes
Comparison fields: 5 of 93
  • Artificial Intelligence 140
  • Information Systems 54
  • Computer Networks and Communications 49
  • Management Information Systems 31
  • Management Science and Operations Research 26
Replace Raoul-Gabriel Urma with:
Raoul-Gabriel Urma United Kingdom
Dinithi Nallaperuma Australia
Josef Küng Austria
Ali. H. Shareef Malaysia
Michele Ianni Italy
Isma Farah Siddiqui South Korea
Saad Razzaq Pakistan
Mervat Abu-Elkheir Egypt
Gourav Roy India
Andrei Paleyes relative to Raoul-Gabriel Urma United Kingdom Raoul-Gabriel Urma's profile →
Citations per field
00.5×1.5×
Raoul-Gabriel Urma · 1×
Citations per year

Countries citing papers authored by Andrei Paleyes

Since Specialization
Citations

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

Fields of papers citing papers by Andrei Paleyes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrei Paleyes

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

All Works

10 of 10 papers shown
#WorkIndexed citations
1 0
2 2
3 6
4 2
5 0
6
Challenges in Deploying Machine Learning: A Survey of Case Studiesbreakdown →
259
7 3
8 16
9 4
10 11

About Andrei Paleyes

Andrei Paleyes is a scholar working on Information Systems and Management, Software and Information Systems, having authored 10 papers that have together received 303 indexed citations. Recurring topics across this work include Software Engineering Research (3 papers), Software System Performance and Reliability (3 papers) and Advanced Multi-Objective Optimization Algorithms (2 papers). The work is most often cited by research in Health Informatics (10 citations), Artificial Intelligence (140 citations) and Management Information Systems (31 citations). Andrei Paleyes has collaborated with scholars based in United Kingdom, Germany and Finland. Frequent co-authors include Neil D. Lawrence, Raoul-Gabriel Urma, Javier González, Aki Vehtari, Christian Cabrera, Tom Diethe, Borja Balle, Bernhard Schölkopf, Siyuan Guo and Michael Hutchinson. Their work appears in journals such as SHILAP Revista de lepidopterología, ACM Computing Surveys and Royal Society Open Science.

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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