Anna M. Hiszpanski
- Materials Chemistry top 5%
- Electrical and Electronic Engineering top 10%
- Polymers and Plastics top 10%
- Electronic, Optical and Magnetic Materials
- Organic Chemistry
- Co-authors
- Yueh‐Lin LooT. Yong-Jin HanBhavya KailkhuraBrian GallagherColin NuckollsShusen LiuXiaoting ZhongElsa Olivetti
- Topics
- Machine Learning in Materials Science (10 papers)Organic Electronics and Photovoltaics (10 papers)Computational Drug Discovery Methods (7 papers)
- Partner nations
- United StatesAustraliaSouth Korea
In The Last Decade
Anna M. Hiszpanski
34 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Materials Chemistry 740
- Electrical and Electronic Engineering 529
- Polymers and Plastics 211
- Electronic, Optical and Magnetic Materials 145
- Organic Chemistry 143
Countries citing papers authored by Anna M. Hiszpanski
This map shows the geographic impact of Anna M. Hiszpanski'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 Anna M. Hiszpanski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anna M. Hiszpanski more than expected).
Fields of papers citing papers by Anna M. Hiszpanski
This network shows the impact of papers produced by Anna M. Hiszpanski. 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 Anna M. Hiszpanski. The network helps show where Anna M. Hiszpanski may publish in the future.
Co-authorship network of co-authors of Anna M. Hiszpanski
This figure shows the co-authorship network connecting the top 25 collaborators of Anna M. Hiszpanski. A scholar is included among the top collaborators of Anna M. Hiszpanski 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 Anna M. Hiszpanski. Anna M. Hiszpanski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 0 | |
| 3 | 8 | |
| 4 | 9 | |
| 5 | Explainable machine learning in materials sciencebreakdown → | 214 |
| 6 | 4 | |
| 7 | 33 | |
| 8 | 52 | |
| 9 | 52 | |
| 10 | 198 | |
| 11 | 1 | |
| 12 | 10 | |
| 13 | 17 | |
| 14 | 3 | |
| 15 | 39 | |
| 16 | 56 | |
| 17 | 32 | |
| 18 | 31 | |
| 19 | 129 | |
| 20 | 2 |
About Anna M. Hiszpanski
Anna M. Hiszpanski is a scholar working on Structural Biology, Materials Chemistry and Physical and Theoretical Chemistry, having authored 35 papers that have together received 1.3k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (10 papers), Organic Electronics and Photovoltaics (10 papers) and Computational Drug Discovery Methods (7 papers). The work is most often cited by research in Materials Chemistry (740 citations), Polymers and Plastics (211 citations) and Physical and Theoretical Chemistry (100 citations). Anna M. Hiszpanski has collaborated with scholars based in United States, Australia and South Korea. Frequent co-authors include Yueh‐Lin Loo, T. Yong-Jin Han, Bhavya Kailkhura, Brian Gallagher, Colin Nuckolls, Shusen Liu, Xiaoting Zhong, Elsa Olivetti, Edward Kim and Jacqueline M. Cole. Their work appears in journals such as Journal of the American Chemical Society, 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.