Bing Huang

3.5k citations
55 papers · 2.4k indexed · 2 hit papers · h-index 23
Topics
Electrocatalysts for Energy Conversion (15 papers)Machine Learning in Materials Science (13 papers)Advanced battery technologies research (13 papers)

In The Last Decade

Bing Huang

51 papers receiving 2.3k citations

Hit Papers

Prediction Errors of Molecular Machine Learning Models Lo...201720262020202320172023100200300400

Peers

Bing Huang
Comparison fields: 5 of 128
  • Materials Chemistry 989
  • Molecular Biology 573
  • Computational Theory and Mathematics 518
  • Electrical and Electronic Engineering 483
  • Genetics 445
Replace Fatemeh Khalili‐Araghi with:
Fatemeh Khalili‐Araghi United States
Min Qian China
Ce Zhang China
Yun Huang China
Chuan Liu China
Pascal Dufour France
Kevin Tran United States
Semion K. Saikin United States
Andreas Schuster Germany
Eriko Watanabe Japan
Bing Huang relative to Fatemeh Khalili‐Araghi United States Fatemeh Khalili‐Araghi's profile →
Citations per field
00.5×9.3×
Fatemeh Khalili‐Araghi · 1×
Citations per year

Countries citing papers authored by Bing Huang

Since Specialization
Citations

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

Fields of papers citing papers by Bing Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bing Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Bing Huang. A scholar is included among the top collaborators of Bing Huang 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 Bing Huang. Bing Huang 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
#WorkIndexed citations
1 0
2 1
3 5
4 14
5 0
6 21
7 14
8 3
9 11
10 25
11 2
12
Quantum machine learning in chemical compound space
1
13
The "DNA" of chemistry: Scalable quantum machine learning with "amons"
15
14
Efficient accurate scalable and transferable quantum machine learning with am-ons
6
15
Fast machine learning models of electronic and energetic properties consistently reach approximation errors better than DFT accuracy
5
16
Chemical space exploration with molecular genes and machine learning
2
17 26
18 284
19 3
20 19

About Bing Huang

Bing Huang is a scholar working on Physical and Theoretical Chemistry, Renewable Energy, Sustainability and the Environment and Computational Theory and Mathematics, having authored 55 papers that have together received 2.4k indexed citations. Recurring topics across this work include Electrocatalysts for Energy Conversion (15 papers), Machine Learning in Materials Science (13 papers) and Advanced battery technologies research (13 papers). The work is most often cited by research in Computational Theory and Mathematics (518 citations), Renewable Energy, Sustainability and the Environment (387 citations) and Materials Chemistry (989 citations). Bing Huang has collaborated with scholars based in China, United States and Austria. Frequent co-authors include O. Anatole von Lilienfeld, Lunhui Guan, Shengbiao Wang, James Bartley, Yi Ning, Allen N. Lamb, Justin Gilmer, Luke A. D. Hutchison, Samuel S. Schoenholz and George E. Dahl. Their work appears in journals such as Science, Chemical Reviews and Angewandte Chemie International Edition.

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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