F. Wick

3.4k citations
4 papers · 8 · h-index 2

Impact in

Papers in

    • Quantum Chromodynamics and Particle Interactions 2
    • Particle physics theoretical and experimental studies 2
    • High-Energy Particle Collisions Research 2
    • Machine Learning and Data Classification 1
    • Explainable Artificial Intelligence (XAI) 1
    • Machine Learning in Healthcare 1
Journals
Operations Research Forum (1 paper)arXiv (Cornell University) (2 papers)
Partner nations
Germany

In The Last Decade

F. Wick

3 papers receiving 8 citations

Peers

F. Wick
Comparison fields: 5 of 14
  • Management Science and Operations Research 2
  • Transportation 1
  • Aquatic Science 1
  • Industrial and Manufacturing Engineering 1
  • Artificial Intelligence 3
Replace Vasily Ershov with:
Vasily Ershov Russia
Milica Aleksić Serbia
D. H. Wei China
X. Kui China
Adit Anand United States
Fabian Both Germany
Lav P. Patel United States
Vincent P. Galotti
Arran Schlosberg Australia
Phil Crone United States
F. Wick relative to Vasily Ershov Russia Vasily Ershov's profile →
Citations per field
00.5×1.5×
Vasily Ershov · 1×
Citations per year

Countries citing papers authored by F. Wick

Since Specialization
Citations

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

Fields of papers citing papers by F. Wick

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 3 scholars most cited alongside F. Wick, 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 F. Wick Line = papers co-authored together F. Wick links everyone, so they are left out of the graph.

All Works

4 of 4 papers shown
#Work
1 20194
2 20213
3 20101
4 20110

About F. Wick

F. Wick is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence, Management Science and Operations Research, Electrical and Electronic Engineering and Renewable Energy, Sustainability and the Environment, having authored 4 papers that have together received 8 indexed citations. Recurring topics across this work include Quantum Chromodynamics and Particle Interactions (2 papers), Particle physics theoretical and experimental studies (2 papers), High-Energy Particle Collisions Research (2 papers), Machine Learning and Data Classification (1 paper), Energy, Environment, and Transportation Policies (1 paper), Forecasting Techniques and Applications (1 paper), Explainable Artificial Intelligence (XAI) (1 paper) and Machine Learning in Healthcare (1 paper). The work is most often cited by research in Management Science and Operations Research (2 citations), Transportation (1 citation), Aquatic Science (1 citation), Industrial and Manufacturing Engineering (1 citation) and Artificial Intelligence (3 citations). F. Wick has collaborated with scholars based in Germany. Frequent co-authors include U. Kerzel, M. Wolf and Martin E. Hahn. Their work appears in journals such as Operations Research Forum and arXiv (Cornell University).

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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