Kun Yao
- Materials Chemistry top 5%
- Computational Theory and Mathematics top 1%
- Molecular Biology
- Electrical and Electronic Engineering top 10%
- Biomedical Engineering top 10%
- Co-authors
- John ParkhillJohn E. HerrTao TangJiang GongXin WenKarl LeswingSteven V. JeromeMatthew P. Repasky
- Topics
- Machine Learning in Materials Science (9 papers)Computational Drug Discovery Methods (9 papers)Polymer Nanocomposites and Properties (9 papers)
- Partner nations
- ChinaUnited StatesPoland
In The Last Decade
Kun Yao
65 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 151
- Materials Chemistry 1.4k
- Computational Theory and Mathematics 506
- Molecular Biology 491
- Electrical and Electronic Engineering 391
- Biomedical Engineering 384
Countries citing papers authored by Kun Yao
This map shows the geographic impact of Kun Yao'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 Kun Yao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Yao more than expected).
Fields of papers citing papers by Kun Yao
This network shows the impact of papers produced by Kun Yao. 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 Kun Yao. The network helps show where Kun Yao may publish in the future.
Co-authorship network of co-authors of Kun Yao
This figure shows the co-authorship network connecting the top 25 collaborators of Kun Yao. A scholar is included among the top collaborators of Kun Yao 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 Kun Yao. Kun Yao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 9 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | Epik: p K a and Protonation State Prediction through Machine Learningbreakdown → | 130 |
| 8 | 88 | |
| 9 | 39 | |
| 10 | 19 | |
| 11 | 55 | |
| 12 | 52 | |
| 13 | 19 | |
| 14 | 17 | |
| 15 | 102 | |
| 16 | 69 | |
| 17 | 2 | |
| 18 | 3 | |
| 19 | 3 | |
| 20 | 14 |
About Kun Yao
Kun Yao is a scholar working on Polymers and Plastics, Computational Theory and Mathematics and Materials Chemistry, having authored 68 papers that have together received 2.8k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (9 papers), Computational Drug Discovery Methods (9 papers) and Polymer Nanocomposites and Properties (9 papers). The work is most often cited by research in Computational Theory and Mathematics (506 citations), Materials Chemistry (1.4k citations) and Polymers and Plastics (327 citations). Kun Yao has collaborated with scholars based in China, United States and Poland. Frequent co-authors include John Parkhill, John E. Herr, Tao Tang, Jiang Gong, Xin Wen, Karl Leswing, Steven V. Jerome, Matthew P. Repasky, Zhiwei Jiang and Nana Tian. Their work appears in journals such as The Journal of Chemical Physics, Nano Letters and ACS Nano.
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.