K. Wang

6.8k citations
51 papers · 562 indexed · 1 hit paper · h-index 11

Impact in

Papers in

K. Wang

49 papers receiving 543 citations

Hit Papers

DNNGP, a deep neural network-based method for genomic prediction using multi-omics data in plants 2022 · 132 citations
13220222026202320244080120

Peers

K. Wang
Comparison fields: 5 of 109
  • Atomic and Molecular Physics, and Optics 177
  • Radiation 43
  • Statistical and Nonlinear Physics 52
  • Cancer Research 52
  • Genetics 86
Replace Prabhakar Pradhan with:
Prabhakar Pradhan United States
Cong Li China
J. F. Hu China
Jens Decker Germany
Po‐Chia Chen Germany
W. Becker Germany
Jingzhong Guo United States
Ruisi Wang China
Renmin Han China
H.P. Leenhouts Netherlands
K. Wang relative to Prabhakar Pradhan United States Prabhakar Pradhan's profile →
Citations per field
00.5×8.5×
Prabhakar Pradhan · 1×
Citations per year

Countries citing papers authored by K. Wang

Since Specialization
Citations

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

Fields of papers citing papers by K. Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1
DNNGP, a deep neural network-based method for genomic prediction using multi-omics data in plants
Hit paper breakdown →
2022132
2 201684
3 201633
4 200930
5 200430
6 201229
7 199527
8 199420
9 199818
10 200812
11 199912
12 20129
13 20249
14 20189
15 20079
16 20019
17 20158
18 20226
19 19966
20 19905

About K. Wang

K. Wang is a scholar working on Radiation, Statistical and Nonlinear Physics, Atomic and Molecular Physics, and Optics, Nuclear and High Energy Physics and Numerical Analysis, having authored 51 papers that have together received 562 indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (7 papers), Quantum and electron transport phenomena (6 papers), Cold Atom Physics and Bose-Einstein Condensates (6 papers), Quantum Information and Cryptography (6 papers), Nonlinear Waves and Solitons (5 papers), Medical Imaging Techniques and Applications (5 papers), Nonlinear Photonic Systems (4 papers) and Semiconductor Quantum Structures and Devices (3 papers). The work is most often cited by research in Atomic and Molecular Physics, and Optics (177 citations), Radiation (43 citations), Statistical and Nonlinear Physics (52 citations), Cancer Research (52 citations) and Genetics (86 citations). K. Wang has collaborated with scholars based in China, United States and India. Frequent co-authors include Sarah Hearne, Awais Rasheed, Muhammad Abid, José Crossa, Huihui Li, Qing‐Hu Chen, Mang Feng, Shaolong Wan, Zhengkuan Jiao and Yuhang Ren. Their work appears in journals such as Physics Letters A, physica status solidi (b), International Journal of Radiation Oncology*Biology*Physics, Chinese Physics Letters and The European Physical Journal B.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026