M. Feickert

7.8k citations
13 papers · 119 indexed · h-index 4

Impact in

Papers in

Journals
SHILAP Revista de lepidopterología (6 papers)Zenodo (CERN European Organization for Nuclear Research) (3 papers)Astrophysics Source Code Library (1 paper)Proceedings of 41st International Conference on High Energy physics — PoS(ICHEP2022) (1 paper)arXiv (Cornell University) (1 paper)

In The Last Decade

M. Feickert

10 papers receiving 118 citations

Peers

M. Feickert
Comparison fields: 5 of 28
  • Nuclear and High Energy Physics 93
  • Information Systems and Management 12
  • Statistical and Nonlinear Physics 11
  • Artificial Intelligence 28
  • Computer Networks and Communications 15
Replace Sergei Gleyzer with:
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V.A. Ilyin Russia
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M. Feickert relative to Sergei Gleyzer United States Sergei Gleyzer's profile →
Citations per field
00.5×4.2×
Sergei Gleyzer · 1×
Citations per year

Countries citing papers authored by M. Feickert

Since Specialization
Citations

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

Fields of papers citing papers by M. Feickert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 202154
2 202137
3 202017
4 20213
5 20202
6 20242
7
iminuit: Jupyter-friendly Python interface for C++ MINUIT2
20211
8 20211
9 20221
10 20201
11 20240
12 20240
13 20210

About M. Feickert

M. Feickert is a scholar working on Nuclear and High Energy Physics, Information Systems and Management, Computer Networks and Communications, Artificial Intelligence and Hardware and Architecture, having authored 13 papers that have together received 119 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (6 papers), Computational Physics and Python Applications (4 papers), Distributed and Parallel Computing Systems (4 papers), Particle Detector Development and Performance (3 papers), Scientific Computing and Data Management (3 papers), Lung Cancer Treatments and Mutations (2 papers), Nuclear reactor physics and engineering (1 paper) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (93 citations), Information Systems and Management (12 citations), Statistical and Nonlinear Physics (11 citations), Artificial Intelligence (28 citations) and Computer Networks and Communications (15 citations). M. Feickert has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Benjamin Nachman, L. Heinrich, G. H. Stark, K. Cranmer, H.-P. Dembinski, C. Burr, Nick W. Smith, Pratyush Kumar Das, B. Krikler and J. Pivarski. Their work appears in journals such as SHILAP Revista de lepidopterología, Zenodo (CERN European Organization for Nuclear Research), Astrophysics Source Code Library, Proceedings of 41st International Conference on High Energy physics — PoS(ICHEP2022) 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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