M. Kaiser

2.3k citations
33 papers · 317 · h-index 8

Impact in

Papers in

    • Fuzzy Logic and Control Systems 5
    • Evolutionary Algorithms and Applications 4
    • Reinforcement Learning in Robotics 4
    • Neural Networks and Applications 4
    • Particle accelerators and beam dynamics 10

M. Kaiser

29 papers receiving 270 citations

Peers

M. Kaiser
Comparison fields: 5 of 44
  • Control and Systems Engineering 157
  • Artificial Intelligence 120
  • Computer Vision and Pattern Recognition 69
  • Aerospace Engineering 76
  • Nuclear and High Energy Physics 34
Replace Hideyuki Uehara with:
Hideyuki Uehara Japan
Masashi Yamada Japan
Haoyang Yang China
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Citations per field
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Citations per year

Countries citing papers authored by M. Kaiser

Since Specialization
Citations

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

Fields of papers citing papers by M. Kaiser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200295
2 199638
3 200934
4 199525
5 199622
6 199420
7 200917
8 19967
9 19947
10 20027
11 20255
12 20025
13
THE HITRAP DECELERATOR PROJECT AT GSI
20065
14
Robot-learning - Three case studies in robotics and machine learning
19944
15 19953
16
UNILAC status and developments
20023
17
Commissioning of the New GSI-Charge State Separator System for High Current Heavy Ion Beams
20083
18 20212
19 19952
20 20022

About M. Kaiser

M. Kaiser is a scholar working on Artificial Intelligence, Aerospace Engineering, Electrical and Electronic Engineering, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 33 papers that have together received 317 indexed citations. Recurring topics across this work include Particle accelerators and beam dynamics (10 papers), Fuzzy Logic and Control Systems (5 papers), Particle Accelerators and Free-Electron Lasers (5 papers), Robotic Path Planning Algorithms (4 papers), Evolutionary Algorithms and Applications (4 papers), Reinforcement Learning in Robotics (4 papers), Neural Networks and Applications (4 papers) and Magnetic confinement fusion research (4 papers). The work is most often cited by research in Control and Systems Engineering (157 citations), Artificial Intelligence (120 citations), Computer Vision and Pattern Recognition (69 citations), Aerospace Engineering (76 citations) and Nuclear and High Energy Physics (34 citations). M. Kaiser has collaborated with scholars based in Germany, Italy and Belgium. Frequent co-authors include R. Dillmann, Marnix Nuttin, Attilio Giordana, Cristina Baroglio, Frank Wallner, Rüdiger Dillmann, L. Groening, L. Dahl, W. Barth and Sascha Mickat. Their work appears in journals such as Physical Review Letters, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, Review of Scientific Instruments, Ocean Engineering and Machine Learning.

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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