Alpha A. Lee

6.5k total citations · 5 hit papers
69 papers, 3.8k citations indexed

About

Alpha A. Lee is a scholar working on Materials Chemistry, Computational Theory and Mathematics and Molecular Biology. According to data from OpenAlex, Alpha A. Lee has authored 69 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Materials Chemistry, 21 papers in Computational Theory and Mathematics and 13 papers in Molecular Biology. Recurrent topics in Alpha A. Lee's work include Computational Drug Discovery Methods (19 papers), Machine Learning in Materials Science (17 papers) and Electrochemical Analysis and Applications (9 papers). Alpha A. Lee is often cited by papers focused on Computational Drug Discovery Methods (19 papers), Machine Learning in Materials Science (17 papers) and Electrochemical Analysis and Applications (9 papers). Alpha A. Lee collaborates with scholars based in United Kingdom, United States and Germany. Alpha A. Lee's co-authors include Susan Perkin, Alexander M. Smith, Yao Zhang, Ulrich Stimming, Rhys E. A. Goodall, Yunwei Zhang, Jiabin Wang, Qiaochu Tang, Carla Perez-Martinez and Dominic Vella and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Physical Review Letters.

In The Last Decade

Alpha A. Lee

66 papers receiving 3.7k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning

2020 618 citations Yunwei Zhang, Qiaochu Tang et al. Nature Communications profile →
The Electrostatic Screening Length in Concentrated Electrolytes Increases with Concentration

2016 445 citations Alexander M. Smith, Alpha A. Lee et al. profile →
Impedance-based forecasting of lithium-ion battery performance amid uneven usage

2022 148 citations Ulrich Stimming, Alpha A. Lee et al. Nature Communications profile →
Accelerating antiviral drug discovery: lessons from COVID-19

2023 98 citations Annette von Delft, Matthew D. Hall et al. Nature Reviews Drug Discovery profile →
A framework to evaluate machine learning crystal stability predictions

2025 29 citations Janosh Riebesell, Rhys E. A. Goodall et al. Nature Machine Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Alpha A. Lee United Kingdom	27	1.2k	1.1k	691	686	510	69	3.8k
Rafael Gómez‐Bombarelli United States	35	1.4k 1.2×	2.4k 2.3×	370 0.5×	270 0.4×	147 0.3×	126	5.1k
Jinjin Li China	36	2.0k 1.7×	1.9k 1.8×	298 0.4×	221 0.3×	104 0.2×	276	4.7k
Yoshihiro Kudo Japan	26	1.2k 1.0×	342 0.3×	440 0.6×	356 0.5×	511 1.0×	169	3.6k
Wataru Shinoda Japan	44	1.4k 1.2×	2.1k 2.0×	304 0.4×	782 1.1×	213 0.4×	162	7.4k
Jens Smiatek Germany	32	481 0.4×	489 0.5×	123 0.2×	471 0.7×	160 0.3×	106	2.6k
John A. Pojman United States	46	311 0.3×	2.2k 2.1×	765 1.1×	572 0.8×	109 0.2×	198	7.6k
Dan Luss United States	43	553 0.5×	2.5k 2.4×	257 0.4×	1.4k 2.1×	85 0.2×	281	6.4k
Amir Barati Farimani United States	38	1.1k 0.9×	2.7k 2.5×	156 0.2×	117 0.2×	124 0.2×	142	5.5k
Toon Verstraelen Belgium	36	692 0.6×	2.6k 2.4×	74 0.1×	281 0.4×	96 0.2×	90	4.9k
Maxim V. Fedorov Russia	36	1.2k 1.0×	1.2k 1.1×	41 0.1×	1.6k 2.3×	1.2k 2.3×	127	5.3k

Countries citing papers authored by Alpha A. Lee

Since Specialization

Citations

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

Fields of papers citing papers by Alpha A. Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alpha A. Lee

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Riebesell, Janosh, Rhys E. A. Goodall, Philipp Benner, et al.. (2025). A framework to evaluate machine learning crystal stability predictions. Nature Machine Intelligence. 7(6). 836–847. 29 indexed citations breakdown →

Xu, Zhen, et al.. (2025). Understanding the Mechanism of Electrochemical CO ₂ Capture by Supercapacitive Swing Adsorption. ACS Nano. 19(4). 4242–4250. 6 indexed citations

Riebesell, Janosh, Rhys E. A. Goodall, Philipp Benner, et al.. (2025). Author Correction: A framework to evaluate machine learning crystal stability predictions. Nature Machine Intelligence. 7(9). 1586–1586. 1 indexed citations

London, Nir, et al.. (2024). Deconvoluting low yield from weak potency in direct-to-biology workflows with machine learning. RSC Medicinal Chemistry. 15(3). 1015–1021. 3 indexed citations

Welch, Stephen R., John P. Bilello, Kara Carter, et al.. (2024). Meeting report of the 37th International Conference on Antiviral Research in Gold Coast, Australia, May 20–24, 2024, organized by the International Society for Antiviral Research. Antiviral Research. 232. 106037–106037.

Delft, Annette von, Matthew D. Hall, Ann D. Kwong, et al.. (2023). Accelerating antiviral drug discovery: lessons from COVID-19. Nature Reviews Drug Discovery. 22(7). 585–603. 98 indexed citations breakdown →

Stimming, Ulrich, et al.. (2022). Impedance-based forecasting of lithium-ion battery performance amid uneven usage. Nature Communications. 13(1). 4806–4806. 148 indexed citations breakdown →

Härtel, Andreas, et al.. (2021). Bayesian unsupervised learning reveals hidden structure in concentrated electrolytes. The Journal of Chemical Physics. 154(13). 134902–134902. 12 indexed citations

Robinson, Matthew C., et al.. (2020). Impact of Chemist-In-The-Loop Molecular Representations on Machine Learning Outcomes. Journal of Chemical Information and Modeling. 60(10). 4449–4456. 11 indexed citations

10.

Robinson, Matthew C., Robert C. Glen, & Alpha A. Lee. (2020). Validating the validation: reanalyzing a large-scale comparison of deep learning and machine learning models for bioactivity prediction. Journal of Computer-Aided Molecular Design. 34(7). 717–730. 49 indexed citations

11.

Zhang, Yunwei, Qiaochu Tang, Yao Zhang, et al.. (2020). Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning. Nature Communications. 11(1). 1706–1706. 618 indexed citations breakdown →

12.

Goodall, Rhys E. A. & Alpha A. Lee. (2020). Predicting materials properties without crystal structure: deep representation learning from stoichiometry. Nature Communications. 11(1). 6280–6280. 235 indexed citations

13.

Lee, Alpha A., Qingyi Yang, Christopher R. Butler, et al.. (2019). Ligand biological activity predicted by cleaning positive and negative chemical correlations. Proceedings of the National Academy of Sciences. 116(9). 3373–3378. 22 indexed citations

14.

Smith, Alexander M., Alpha A. Lee, & Susan Perkin. (2017). Switching the Structural Force in Ionic Liquid-Solvent Mixtures by Varying Composition. Physical Review Letters. 118(9). 96002–96002. 70 indexed citations

15.

Lee, Alpha A., Carla Perez-Martinez, Alexander M. Smith, & Susan Perkin. (2017). Scaling Analysis of the Screening Length in Concentrated Electrolytes. Physical Review Letters. 119(2). 26002–26002. 172 indexed citations

16.

Lee, Alpha A., Andreas Münch, & Endre Süli. (2016). Response to “Comment on ‘Degenerate mobilities in phase field models are insufficient to capture surface diffusion’” [Appl. Phys. Lett. 108, 036101 (2016)]. Applied Physics Letters. 108(3). 5 indexed citations

17.

Gebbie, Matthew A., Alexander M. Smith, Howard A. Dobbs, et al.. (2016). Long range electrostatic forces in ionic liquids. Chemical Communications. 53(7). 1214–1224. 304 indexed citations

18.

Lee, Alpha A., Dominic Vella, & Alain Goriely. (2015). Electrokinetic Transport in Ionic Liquids. arXiv (Cornell University). 1 indexed citations

19.

Lee, Alpha A., et al.. (2013). Interionic Interactions in Conducting Nanoconfinement. ChemPhysChem. 14(18). 4121–4125. 40 indexed citations

20.

Lee, Alpha A., Ralph H. Colby, & Alexei A. Kornyshev. (2013). Electroactuation with single charge carrier ionomers: the roles of electrostatic pressure and steric strain. Soft Matter. 9(14). 3767–3767. 22 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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