Simon Axelrod

1.1k total citations · 1 hit paper
17 papers, 654 citations indexed

About

Simon Axelrod is a scholar working on Materials Chemistry, Molecular Biology and Computational Theory and Mathematics. According to data from OpenAlex, Simon Axelrod has authored 17 papers receiving a total of 654 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Materials Chemistry, 9 papers in Molecular Biology and 6 papers in Computational Theory and Mathematics. Recurrent topics in Simon Axelrod's work include Machine Learning in Materials Science (9 papers), Computational Drug Discovery Methods (6 papers) and Photoreceptor and optogenetics research (4 papers). Simon Axelrod is often cited by papers focused on Machine Learning in Materials Science (9 papers), Computational Drug Discovery Methods (6 papers) and Photoreceptor and optogenetics research (4 papers). Simon Axelrod collaborates with scholars based in United States, Canada and United Kingdom. Simon Axelrod's co-authors include Rafael Gómez‐Bombarelli, Daniel Schwalbe‐Koda, Somesh Mohapatra, Wujie Wang, Eugene I. Shakhnovich, Kevin P. Greenman, James Damewood, Eugene I. Shakhnovich, Nathan C. Frey and Connor W. Coley and has published in prestigious journals such as Science, Nature Communications and The Journal of Chemical Physics.

In The Last Decade

Simon Axelrod

17 papers receiving 641 citations

Hit Papers

GEOM, energy-annotated molecular conformations for proper... 2022 2026 2023 2024 2022 40 80 120
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.

  1. GEOM, energy-annotated molecular conformations for property prediction and molecular generation
    2022 141 citations Simon Axelrod, Rafael Gómez‐Bombarelli Scientific Data profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Simon Axelrod United States 12 387 219 213 93 85 17 654
Riccardo Petraglia Switzerland 7 263 0.7× 131 0.6× 170 0.8× 57 0.6× 41 0.5× 10 439
Dávid Péter Kovács United Kingdom 9 506 1.3× 100 0.5× 167 0.8× 52 0.6× 188 2.2× 10 687
Dongseon Lee South Korea 14 481 1.2× 319 1.5× 239 1.1× 272 2.9× 20 0.2× 19 893
Riccardo Capelli Italy 15 298 0.8× 399 1.8× 95 0.4× 211 2.3× 65 0.8× 45 823
Jinxiao Zhang China 12 278 0.7× 87 0.4× 94 0.4× 34 0.4× 77 0.9× 29 481
Siqin Cao China 14 204 0.5× 407 1.9× 49 0.2× 86 0.9× 110 1.3× 32 703
Leonardo Medrano Sandonas Germany 15 461 1.2× 110 0.5× 117 0.5× 24 0.3× 99 1.2× 41 626
Samuel M. Blau United States 16 338 0.9× 110 0.5× 132 0.6× 27 0.3× 103 1.2× 30 897
Hythem Sidky United States 13 277 0.7× 303 1.4× 79 0.4× 118 1.3× 102 1.2× 19 657
Jiajing Zhang China 7 210 0.5× 455 2.1× 86 0.4× 47 0.5× 337 4.0× 16 819

Countries citing papers authored by Simon Axelrod

Since Specialization
Citations

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

Fields of papers citing papers by Simon Axelrod

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Simon Axelrod

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

All Works

17 of 17 papers shown
1.
Pfau, David, et al.. (2024). Accurate computation of quantum excited states with neural networks. Science. 385(6711). eadn0137–eadn0137. 19 indexed citations
2.
Frey, Nathan C., Ryan Soklaski, Simon Axelrod, et al.. (2023). Neural scaling of deep chemical models. Nature Machine Intelligence. 5(11). 1297–1305. 54 indexed citations
3.
Axelrod, Simon & Rafael Gómez‐Bombarelli. (2023). Molecular machine learning with conformer ensembles. Machine Learning Science and Technology. 4(3). 35025–35025. 15 indexed citations
4.
Axelrod, Simon, Eugene I. Shakhnovich, & Rafael Gómez‐Bombarelli. (2023). Mapping the Space of Photoswitchable Ligands and Photodruggable Proteins with Computational Modeling. Journal of Chemical Information and Modeling. 63(18). 5794–5802. 2 indexed citations
5.
Axelrod, Simon, Eugene I. Shakhnovich, & Rafael Gómez‐Bombarelli. (2023). Thermal Half-Lives of Azobenzene Derivatives: Virtual Screening Based on Intersystem Crossing Using a Machine Learning Potential. ACS Central Science. 9(2). 166–176. 35 indexed citations
6.
Axelrod, Simon & Rafael Gómez‐Bombarelli. (2022). GEOM, energy-annotated molecular conformations for property prediction and molecular generation. Scientific Data. 9(1). 185–185. 141 indexed citations breakdown →
7.
Axelrod, Simon, Eugene I. Shakhnovich, & Rafael Gómez‐Bombarelli. (2022). Excited state non-adiabatic dynamics of large photoswitchable molecules using a chemically transferable machine learning potential. Nature Communications. 13(1). 3440–3440. 60 indexed citations
8.
Frey, Nathan C., Simon Axelrod, Michael Jones, et al.. (2022). Energy-aware neural architecture selection and hyperparameter optimization. 732–741. 1 indexed citations
9.
Axelrod, Simon, Daniel Schwalbe‐Koda, Somesh Mohapatra, et al.. (2022). Learning Matter: Materials Design with Machine Learning and Atomistic Simulations. Accounts of Materials Research. 3(3). 343–357. 80 indexed citations
10.
Nguyen, Hung V.‐T., Yivan Jiang, Somesh Mohapatra, et al.. (2021). Bottlebrush polymers with flexible enantiomeric side chains display differential biological properties. Nature Chemistry. 14(1). 85–93. 70 indexed citations
11.
Wang, Wujie, et al.. (2021). Active learning accelerates ab initio molecular dynamics on reactive energy surfaces. Chem. 7(3). 738–751. 63 indexed citations
12.
Jiang, Yivan, Gökhan Yilmaz, Hung V.‐T. Nguyen, et al.. (2021). Synthetic Glycomacromolecules of Defined Valency, Absolute Configuration, and Topology Distinguish between Human Lectins. SHILAP Revista de lepidopterología. 1(10). 1621–1630. 35 indexed citations
13.
Wang, Wujie, et al.. (2020). Temperature-transferable coarse-graining of ionic liquids with dual graph convolutional neural networks. The Journal of Chemical Physics. 153(16). 164501–164501. 46 indexed citations
14.
Axelrod, Simon & Paul Brumer. (2019). Multiple time scale open systems: Reaction rates and quantum coherence in model retinal photoisomerization under incoherent excitation. The Journal of Chemical Physics. 151(1). 14104–14104. 6 indexed citations
15.
Axelrod, Simon & Paul Brumer. (2018). An efficient approach to the quantum dynamics and rates of processes induced by natural incoherent light. The Journal of Chemical Physics. 149(11). 114104–114104. 8 indexed citations
16.
Dezfouli, Mohsen Kamandar, et al.. (2017). Theory of hyperbolic stratified nanostructures for surface-enhanced Raman scattering. Physical review. B.. 96(20). 2 indexed citations
17.
Axelrod, Simon, et al.. (2017). Hyperbolic metamaterial nanoresonators make poor single-photon sources. Physical review. B.. 95(15). 17 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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