M. A. Janik

40.5k total citations
12 papers, 68 citations indexed

About

M. A. Janik is a scholar working on Nuclear and High Energy Physics, Computer Vision and Pattern Recognition and Computational Mechanics. According to data from OpenAlex, M. A. Janik has authored 12 papers receiving a total of 68 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Nuclear and High Energy Physics, 1 paper in Computer Vision and Pattern Recognition and 1 paper in Computational Mechanics. Recurrent topics in M. A. Janik's work include Particle physics theoretical and experimental studies (10 papers), High-Energy Particle Collisions Research (10 papers) and Quantum Chromodynamics and Particle Interactions (9 papers). M. A. Janik is often cited by papers focused on Particle physics theoretical and experimental studies (10 papers), High-Energy Particle Collisions Research (10 papers) and Quantum Chromodynamics and Particle Interactions (9 papers). M. A. Janik collaborates with scholars based in Poland, Germany and Switzerland. M. A. Janik's co-authors include P. Foka, L. K. Graczykowski, Ryszard Kozera, A. Kisiel, Sylwester Samborski, Kamil Rafał Deja, Mariusz Kłonica and Monika Joanna Jakubowska and has published in prestigious journals such as SHILAP Revista de lepidopterología, Nuclear Physics A and Measurement Science and Technology.

In The Last Decade

M. A. Janik

9 papers receiving 67 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
M. A. Janik Poland	4	57	8	8	5	3	12	68
A. Rybicki Poland	6	69 1.2×	8 1.0×	20 2.5×	4 0.8×	2 0.7×	24	97
S. K. Chan United Kingdom	4	25 0.4×	4 0.5×	3 0.4×	2 0.4×	3 1.0×	7	56
L. N. Smirnova Russia	6	58 1.0×	8 1.0×	2 0.3×	6 1.2×		16	72
V. A. Kramarenko Russia	5	40 0.7×	8 1.0×	2 0.3×	3 0.6×		15	49
Rui An United States	5	46 0.8×	44 5.5×	6 0.8×	6 1.2×		11	70
V. Murzin Russia	4	20 0.4×	4 0.5×	5 0.6×	2 0.4×		15	34
J.-P. Bähner Germany	5	55 1.0×	29 3.6×	6 0.8×	2 0.4×		12	60
Caio A. G. Prado China	5	78 1.4×	3 0.4×	5 0.6×			9	86
John Terry United States	7	102 1.8×	3 0.4×	6 0.8×			10	109
L.-G. Böttger Germany	3	35 0.6×	19 2.4×	5 0.6×	1 0.2×		3	38

Countries citing papers authored by M. A. Janik

Since Specialization

Citations

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

Fields of papers citing papers by M. A. Janik

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. A. Janik

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

All Works

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12 of 12 papers shown

Samborski, Sylwester, et al.. (2025). Application of machine learning regression algorithms to optimization of CMM measurement strategies. Measurement Science and Technology. 36(11). 115002–115002.

Deja, Kamil Rafał, et al.. (2024). Machine-learning-based particle identification with missing data. The European Physical Journal C. 84(7). 1 indexed citations

Graczykowski, L. K. & M. A. Janik. (2021). Unfolding the effects of final-state interactions and quantum statistics in two-particle angular correlations. arXiv (Cornell University). 5 indexed citations

Janik, M. A., L. K. Graczykowski, & A. Kisiel. (2016). Influence of quantum conservation laws on particle production in hadron collisions. Nuclear Physics A. 956. 886–889.

Foka, P. & M. A. Janik. (2016). An overview of experimental results from ultra-relativistic heavy-ion collisions at the CERN LHC: Hard probes. SHILAP Revista de lepidopterología. 1. 172–194. 13 indexed citations

Foka, P. & M. A. Janik. (2016). An overview of experimental results from ultra-relativistic heavy-ion collisions at the CERN LHC: Bulk properties and dynamical evolution. SHILAP Revista de lepidopterología. 1. 154–171. 35 indexed citations

Janik, M. A.. (2014). Two-particle correlations as a function of relative azimuthal angle and pseudorapidity in proton-proton collisions registered by the ALICE experiment. CERN Bulletin. 1 indexed citations

Foka, P. & M. A. Janik. (2014). ALICE Masterclass on strangeness. SHILAP Revista de lepidopterología. 71. 57–57. 1 indexed citations

Graczykowski, L. K. & M. A. Janik. (2014). Angular correlations of identified charged particles measured in pp collisions by ALICE at the LHC. Nuclear Physics A. 926. 205–212. 3 indexed citations

10.

Janik, M. A.. (2013). Highlights from ALICE at LHC. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8903. 89031Y–89031Y. 1 indexed citations

11.

Janik, M. A., et al.. (2013). REDUCED DATA FOR CURVE MODELING – APPLICATIONS IN GRAPHICS, COMPUTER VISION AND PHYSICS. SHILAP Revista de lepidopterología. 7(18). 28–35. 8 indexed citations

12.

Janik, M. A.. (2012). $\\Delta\\eta\\Delta\\phi$ angular correlations in pp collisions at the LHC registered by the ALICE experiment. CERN Bulletin.

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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