J. Yu

27.6k total citations
10 papers, 23 citations indexed

About

J. Yu is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, J. Yu has authored 10 papers receiving a total of 23 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Nuclear and High Energy Physics, 3 papers in Artificial Intelligence and 2 papers in Computer Networks and Communications. Recurrent topics in J. Yu's work include Particle physics theoretical and experimental studies (5 papers), High-Energy Particle Collisions Research (2 papers) and Particle Detector Development and Performance (2 papers). J. Yu is often cited by papers focused on Particle physics theoretical and experimental studies (5 papers), High-Energy Particle Collisions Research (2 papers) and Particle Detector Development and Performance (2 papers). J. Yu collaborates with scholars based in United States, South Korea and Germany. J. Yu's co-authors include Walter T. Giele, E. W. N. Glover, Jong‐Min Yeom, Jonghan Ko, J. Chapman, K. Ikado, E. Etzion, J. R. Beene, D.S. Levin and C. Ferretti and has published in prestigious journals such as Neurocomputing, IEEE Geoscience and Remote Sensing Letters and IEEE Transactions on Nuclear Science.

In The Last Decade

J. Yu

9 papers receiving 23 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
J. Yu United States	3	15	4	3	3	2	10	23
P. Schleper Germany	2	13 0.9×	3 0.8×	2 0.7×	2 0.7×		8	15
A. Rivetti Italy	3	9 0.6×	5 1.3×	2 0.7×	3 1.0×		6	16
C. I. Ciobanu United States	3	8 0.5×	5 1.3×	2 0.7×	4 1.3×	1 0.5×	9	15
B. Scurlock United States	3	24 1.6×	5 1.3×	6 2.0×	3 1.0×		5	27
B. Burkle United States	3	27 1.8×	2 0.5×	4 1.3×	3 1.0×		5	31
P. U. E. Onyisi United States	3	12 0.8×	5 1.3×	4 1.3×	1 0.3×		8	19
Henry Day-Hall United Kingdom	3	11 0.7×	4 1.0×	3 1.0×			5	13
K. Biery United States	3	15 1.0×	2 0.5×	2 0.7×	3 1.0×		8	20
M. Stolarski Poland	4	15 1.0×	3 0.8×	1 0.3×	4 1.3×		12	26
Y. Fu China	5	28 1.9×	2 0.5×	2 0.7×	2 0.7×		16	37

Countries citing papers authored by J. Yu

Since Specialization

Citations

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

Fields of papers citing papers by J. Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Yu

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Yu, J., et al.. (2025). HeLPNet: Facial structure-aware landmark coordinate regression with heatmap-guided local patch embedding. Neurocomputing. 650. 130860–130860.

2.

Yu, J., et al.. (2024). Enhanced Short-Term Prediction of Solar Radiation Using HRNet Model With Geostationary Satellite Data. IEEE Geoscience and Remote Sensing Letters. 21. 1–5. 2 indexed citations

3.

Yu, J., et al.. (2024). Looping In: Exploring Feedback Strategies to Motivate Human Engagement in Interactive Machine Learning. International Journal of Human-Computer Interaction. 41(14). 8666–8683. 2 indexed citations

4.

Yu, J., et al.. (2022). Deep Learning based Prediction of Solar Surface Irradiance with Geostationary Satellite Images. 21. 311–315. 1 indexed citations

5.

Kovařı́k, K., T. Stavreva, A. Kusina, et al.. (2012). A Survey of Heavy Quark Theory for PDF Analyses. Nuclear Physics B - Proceedings Supplements. 222-224. 52–60. 2 indexed citations

6.

Ball, Richard D., D.S. Levin, Y. Silver, et al.. (2010). Progress in the development of a Plasma Panel Detector. 1536–1539. 2 indexed citations

7.

Canal, Philippe, Jim Kowalkowski, K. Maeshima, et al.. (2003). Online monitoring in the upcoming Fermilab Tevatron runII. 291–294. 1 indexed citations

8.

Adams, T., T. Alexander, S. Avvakumov, J. A. Formaggio, & J. Yu. (2001). Search for the Lepton Family Number Violating Process overline( nu )µe --> µoverline( nu )e. Technische Universität Dortmund Eldorado (Technische Universität Dortmund). 2 indexed citations

9.

Canal, Philippe, Jim Kowalkowski, K. Maeshima, et al.. (2000). Online monitoring in the upcoming Fermilab Tevatron run II. IEEE Transactions on Nuclear Science. 47(2). 240–243. 3 indexed citations

10.

Giele, Walter T., E. W. N. Glover, & J. Yu. (1996). Determination ofαSat hadron colliders. Physical review. D. Particles, fields, gravitation, and cosmology/Physical review. D. Particles and fields. 53(1). 120–130. 8 indexed citations

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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