Meifeng Lin

2.6k total citations
49 papers, 1.2k citations indexed

About

Meifeng Lin is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Meifeng Lin has authored 49 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Nuclear and High Energy Physics, 4 papers in Artificial Intelligence and 3 papers in Computer Networks and Communications. Recurrent topics in Meifeng Lin's work include Particle physics theoretical and experimental studies (30 papers), Quantum Chromodynamics and Particle Interactions (27 papers) and High-Energy Particle Collisions Research (22 papers). Meifeng Lin is often cited by papers focused on Particle physics theoretical and experimental studies (30 papers), Quantum Chromodynamics and Particle Interactions (27 papers) and High-Energy Particle Collisions Research (22 papers). Meifeng Lin collaborates with scholars based in United States, United Kingdom and Japan. Meifeng Lin's co-authors include Sergey Syritsyn, George Fleming, Huey-Wen Lin, David Schaich, Massimiliano Procura, John Negele, W. Schroers, Ph. Hägler, Thomas Appelquist and Michael Engelhardt and has published in prestigious journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Physical review. D.

In The Last Decade

Meifeng Lin

41 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Meifeng Lin United States 17 965 92 75 71 44 49 1.2k
M. Williams United States 10 573 0.6× 127 1.4× 67 0.9× 17 0.2× 24 0.5× 24 724
Igor Dremin Russia 14 627 0.6× 57 0.6× 55 0.7× 28 0.4× 11 0.3× 83 822
L. Ristori Italy 11 385 0.4× 32 0.3× 23 0.3× 14 0.2× 52 1.2× 30 497
K. Ueno United States 15 1.3k 1.3× 47 0.5× 90 1.2× 30 0.4× 34 0.8× 37 1.4k
A. S. Ito Japan 16 1.1k 1.2× 46 0.5× 60 0.8× 50 0.7× 22 0.5× 80 1.4k
L. Garrido Spain 11 173 0.2× 34 0.4× 86 1.1× 17 0.2× 92 2.1× 76 509
Claudius Krause United States 17 897 0.9× 198 2.2× 29 0.4× 42 0.6× 18 0.4× 32 1.0k
M. Regler Austria 11 312 0.3× 19 0.2× 44 0.6× 15 0.2× 95 2.2× 40 455
Jiří Novotný Czechia 16 833 0.9× 338 3.7× 76 1.0× 9 0.1× 15 0.3× 77 1.0k
R. Richter Germany 17 890 0.9× 227 2.5× 37 0.5× 5 0.1× 152 3.5× 68 1.0k

Countries citing papers authored by Meifeng Lin

Since Specialization
Citations

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

Fields of papers citing papers by Meifeng Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Meifeng Lin

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

All Works

20 of 20 papers shown
1.
Ladeinde, Foluso, Yangang Liu, Fan Yang, et al.. (2025). The Impact of Scalar Forcing on Cloud Microphysics Based on Direct Numerical Simulations.
2.
López, Vanessa, Tao Zhang, Kwangmin Yu, et al.. (2024). Towards accelerating particle‐resolved direct numerical simulation with neural operators. Statistical Analysis and Data Mining The ASA Data Science Journal. 17(3). 1 indexed citations
3.
Zhang, Tao, Vanessa López, Meifeng Lin, et al.. (2024). Emulator of PR‐DNS: Accelerating Dynamical Fields With Neural Operators in Particle‐Resolved Direct Numerical Simulation. Journal of Advances in Modeling Earth Systems. 16(2). 3 indexed citations
4.
Dubey, P. K., Vanessa López, Tao Zhang, et al.. (2024). Fourier neural operators for spatiotemporal dynamics in two-dimensional turbulence. 41–48. 2 indexed citations
5.
Torbunov, D., Yi Huang, Meifeng Lin, et al.. (2024). Effectiveness of denoising diffusion probabilistic models for fast and high-fidelity whole-event simulation in high-energy heavy-ion experiments. Physical review. C. 110(3). 2 indexed citations
6.
Tong, Bing, Jianheng Tang, Jing Tang, et al.. (2024). Galaxybase: A High Performance Native Distributed Graph Database for HTAP. Proceedings of the VLDB Endowment. 17(12). 3893–3905.
7.
Leggett, C., et al.. (2024). Porting ATLAS Fast Calorimeter Simulation to GPUs with Performance Portable Programming Models. SHILAP Revista de lepidopterología. 295. 11018–11018.
8.
Yu, H., et al.. (2021). Evaluation of Portable Acceleration Solutions for LArTPC Simulation Using Wire-Cell Toolkit. SHILAP Revista de lepidopterología.
9.
Blum, Thomas, Taku Izubuchi, Chulwoo Jung, et al.. (2020). Nucleon mass and isovector couplings in 2+1-flavor dynamical domain-wall lattice QCD near physical mass. Physical review. D. 101(3). 11 indexed citations
10.
Boyle, Peter A., et al.. (2018). Performance Portability Strategies for Grid C++ Expression Templates. Springer Link (Chiba Institute of Technology). 7 indexed citations
11.
Syritsyn, Sergey, Tom Blum, Michael Engelhardt, et al.. (2015). Initial nucleon structure results with chiral quarks at the physical point. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 134–134. 3 indexed citations
12.
Appelquist, Thomas, Michael I. Buchoff, M. Cheng, et al.. (2014). Two-Color Gauge Theory with Novel Infrared Behavior. Physical Review Letters. 112(11). 111601–111601. 22 indexed citations
13.
Appelquist, Thomas, Richard C. Brower, George Fleming, et al.. (2014). Lattice simulations with eight flavors of domain wall fermions in SU(3) gauge theory. Physical review. D. Particles, fields, gravitation, and cosmology. 90(11). 58 indexed citations
14.
Appelquist, Thomas, Evan Berkowitz, R. C. Brower, et al.. (2014). Composite bosonic baryon dark matter on the lattice:SU(4)baryon spectrum and the effective Higgs interaction. Physical review. D. Particles, fields, gravitation, and cosmology. 89(9). 43 indexed citations
15.
Bratt, Jonathan, Robert G. Edwards, Ph. Hägler, et al.. (2010). Nucleon structure from mixed action calculations using 2+1 flavors of asqtad sea and domain wall valence fermions. DSpace@MIT (Massachusetts Institute of Technology). 26 indexed citations
16.
Antonio, D. J., P. A. Boyle, Thomas Blum, et al.. (2008). Neutral-Kaon Mixing from (2+1)-Flavor Domain-Wall QCD. Physical Review Letters. 100(3). 32001–32001. 42 indexed citations
17.
Aubin, Christopher, J. Laiho, S. Li, & Meifeng Lin. (2008). K→πandK→0in2+1flavor partially quenched chiral perturbation theory. Physical review. D. Particles, fields, gravitation, and cosmology. 78(9). 3 indexed citations
18.
Lin, Meifeng. (2006). Chiral extrapolations in 2+1 flavor domain wall fermion simulations. 185–185. 2 indexed citations
19.
Aoki, Yasumichi, Tom Blum, Norman H. Christ, et al.. (2005). Lattice QCD with two dynamical flavors of domain wall fermions. Physical review. D. Particles, fields, gravitation, and cosmology. 72(11). 45 indexed citations
20.
Lin, Meifeng. (2004). Rough Gauge Fields, Smearing and Domain Wall Fermions. 1 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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