A. Zuranski

37.1k total citations
7 papers, 383 citations indexed

About

A. Zuranski is a scholar working on Computational Theory and Mathematics, Materials Chemistry and Molecular Biology. According to data from OpenAlex, A. Zuranski has authored 7 papers receiving a total of 383 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computational Theory and Mathematics, 4 papers in Materials Chemistry and 2 papers in Molecular Biology. Recurrent topics in A. Zuranski's work include Machine Learning in Materials Science (4 papers), Computational Drug Discovery Methods (4 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). A. Zuranski is often cited by papers focused on Machine Learning in Materials Science (4 papers), Computational Drug Discovery Methods (4 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). A. Zuranski collaborates with scholars based in United States and Sweden. A. Zuranski's co-authors include Abigail G. Doyle, Jesus I. Martinez Alvarado, Benjamin J. Shields, Shivaani S. Gandhi, Stavros K. Kariofillis, Zhichun Guo, Nitesh V. Chawla, Per‐Ola Norrby, John E. Herr and Thierry Kogej and has published in prestigious journals such as Journal of the American Chemical Society, Accounts of Chemical Research and Chemical Science.

In The Last Decade

A. Zuranski

7 papers receiving 375 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
A. Zuranski United States	5	197	137	136	71	69	7	383
Li‐Cheng Xu China	9	226 1.1×	139 1.0×	138 1.0×	70 1.0×	60 0.9×	17	404
Julia E. Borowski United States	5	134 0.7×	82 0.6×	151 1.1×	60 0.8×	58 0.8×	6	337
Marius Kühnemund Germany	4	238 1.2×	173 1.3×	60 0.4×	72 1.0×	78 1.1×	4	339
Babak Mahjour United States	9	102 0.5×	64 0.5×	109 0.8×	109 1.5×	79 1.1×	18	330
Eugene S. Gutman United States	11	110 0.6×	95 0.7×	327 2.4×	95 1.3×	31 0.4×	15	538
Nicholas H. Angello United States	8	204 1.0×	91 0.7×	88 0.6×	84 1.2×	103 1.5×	11	407
A. Buitrago Santanilla United States	4	155 0.8×	90 0.7×	219 1.6×	156 2.2×	236 3.4×	4	547
Ellyn Peters United States	4	168 0.9×	93 0.7×	190 1.4×	67 0.9×	49 0.7×	4	394
William T. Darrow United States	5	361 1.8×	204 1.5×	131 1.0×	109 1.5×	91 1.3×	6	578
Anthony R. Rosales United States	6	155 0.8×	89 0.6×	171 1.3×	67 0.9×	67 1.0×	10	365

Countries citing papers authored by A. Zuranski

Since Specialization

Citations

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

Fields of papers citing papers by A. Zuranski

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of A. Zuranski

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

All Works

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7 of 7 papers shown

1.

Saebi, Mandana, John E. Herr, Zhichun Guo, et al.. (2023). On the use of real-world datasets for reaction yield prediction. Chemical Science. 14(19). 4997–5005. 80 indexed citations

2.

Zuranski, A., Shivaani S. Gandhi, & Abigail G. Doyle. (2023). A Machine Learning Approach to Model Interaction Effects: Development and Application to Alcohol Deoxyfluorination. Journal of the American Chemical Society. 145(14). 7898–7909. 16 indexed citations

3.

Zuranski, A., et al.. (2022). Auto-QChem: an automated workflow for the generation and storage of DFT calculations for organic molecules. Reaction Chemistry & Engineering. 7(6). 1276–1284. 30 indexed citations

4.

Kariofillis, Stavros K., et al.. (2022). Using Data Science To Guide Aryl Bromide Substrate Scope Analysis in a Ni/Photoredox-Catalyzed Cross-Coupling with Acetals as Alcohol-Derived Radical Sources. Journal of the American Chemical Society. 144(2). 1045–1055. 136 indexed citations

5.

Zuranski, A., Jesus I. Martinez Alvarado, Benjamin J. Shields, & Abigail G. Doyle. (2021). Predicting Reaction Yields via Supervised Learning. Accounts of Chemical Research. 54(8). 1856–1865. 117 indexed citations

6.

Alici, A., P. Hopchev, W. Kozanecki, et al.. (2012). Study of the LHC ghost charge and satellite bunches for luminosity calibration.. CERN Document Server (European Organization for Nuclear Research). 2 indexed citations

7.

Anders, C. F., C. Gabaldon, P. Hopchev, et al.. (2012). STUDY OF THE RELATIVE LHC BUNCH POPULATIONS FOR LUMINOSITY CALIBRATION. CERN Document Server (European Organization for Nuclear Research). 2 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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