Kevin McCloskey

2.2k total citations · 1 hit paper
13 papers, 1.2k citations indexed

About

Kevin McCloskey is a scholar working on Global and Planetary Change, Materials Chemistry and Molecular Biology. According to data from OpenAlex, Kevin McCloskey has authored 13 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Global and Planetary Change, 4 papers in Materials Chemistry and 2 papers in Molecular Biology. Recurrent topics in Kevin McCloskey's work include Machine Learning in Materials Science (4 papers), Advanced Aircraft Design and Technologies (2 papers) and Computational Drug Discovery Methods (2 papers). Kevin McCloskey is often cited by papers focused on Machine Learning in Materials Science (4 papers), Advanced Aircraft Design and Technologies (2 papers) and Computational Drug Discovery Methods (2 papers). Kevin McCloskey collaborates with scholars based in United States, United Kingdom and Switzerland. Kevin McCloskey's co-authors include Patrick Riley, Steven Kearnes, Vijay S. Pande, Marc Berndl, Lucy J. Colwell, Michael P. Brenner, Ankur Taly, Federico Monti, Betty Chan and Matthew Clark and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Remote Sensing of Environment and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Kevin McCloskey

12 papers receiving 1.2k citations

Hit 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.

Molecular graph convolutions: moving beyond fingerprints

2016 995 citations Steven Kearnes, Kevin McCloskey et al. Journal of Computer-Aided Molecular Design profile →

Peers

Kevin McCloskey

CTM

MC

MB

AI

BE

Timothy Hirzel United States

Caleb Geniesse United States

Steven Kearnes United States

Dejun Jiang China

Yuyang Wang United States

Nathan O. Hodas United States

Sergio Decherchi Italy

Marcus Olivecrona Sweden

Zhenqin Wu United States

Xutong Li China

Timothy Hirzel United States

Kevin McCloskey

795 ×1.0

CTM

797 ×1.2

MC

550 ×1.0

MB

122 ×0.6

AI

102 ×1.7

BE

Citations per year, relative to Kevin McCloskey Kevin McCloskey (= 1×) peers Timothy Hirzel

Countries citing papers authored by Kevin McCloskey

Since Specialization

Citations

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

Fields of papers citing papers by Kevin McCloskey

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kevin McCloskey

This figure shows the co-authorship network connecting the top 25 collaborators of Kevin McCloskey. A scholar is included among the top collaborators of Kevin McCloskey 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 Kevin McCloskey. Kevin McCloskey 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:

13 of 13 papers shown

1.

Sarna, Aaron, et al.. (2025). Benchmarking and improving algorithms for attributing satellite-observed contrails to flights. Atmospheric measurement techniques. 18(14). 3495–3532. 1 indexed citations

2.

Platt, John, Marc Shapiro, Kevin McCloskey, et al.. (2024). The effect of uncertainty in humidity and model parameters on the prediction of contrail energy forcing. Environmental Research Communications. 6(9). 95015–95015. 3 indexed citations

3.

Geraedts, Scott, Thomas Dean, Sebastian D. Eastham, et al.. (2023). A scalable system to measure contrail formation on a per-flight basis. Environmental Research Communications. 6(1). 15008–15008. 13 indexed citations

4.

Ng, Joe Yue-Hei, et al.. (2023). Contrail Detection on GOES-16 ABI With the OpenContrails Dataset. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–14. 6 indexed citations

5.

Vieira, Fernando G., Subhashini Venugopalan, Aren Jansen, et al.. (2022). A machine-learning based objective measure for ALS disease severity. npj Digital Medicine. 5(1). 45–45. 24 indexed citations

6.

McCloskey, Kevin, et al.. (2022). Estimates of broadband upwelling irradiance from GOES-16 ABI. Remote Sensing of Environment. 285. 113376–113376. 2 indexed citations

7.

McCloskey, Kevin, et al.. (2021). A human-labeled Landsat-8 contrails dataset. International Conference on Machine Learning. 1 indexed citations

8.

Sánchez-Lengeling, Benjamín, Jennifer N. Wei, Brian K. Lee, et al.. (2020). Evaluating Attribution for Graph Neural Networks. Neural Information Processing Systems. 33. 5898–5910. 31 indexed citations

9.

McCloskey, Kevin, Eric A. Sigel, Steven Kearnes, et al.. (2020). Machine Learning on DNA-Encoded Libraries: A New Paradigm for Hit Finding. Journal of Medicinal Chemistry. 63(16). 8857–8866. 85 indexed citations

10.

Cubuk, Ekin D., Evan J. Reed, Gowoon Cheon, et al.. (2020). Crystal Structure Search with Random Structure Relaxations Using Graph Networks. 1 indexed citations

11.

McCloskey, Kevin, Ankur Taly, Federico Monti, Michael P. Brenner, & Lucy J. Colwell. (2019). Using attribution to decode binding mechanism in neural network models for chemistry. Proceedings of the National Academy of Sciences. 116(24). 11624–11629. 60 indexed citations

12.

Kearnes, Steven, Kevin McCloskey, Marc Berndl, Vijay S. Pande, & Patrick Riley. (2016). Molecular graph convolutions: moving beyond fingerprints. Journal of Computer-Aided Molecular Design. 30(8). 595–608. 995 indexed citations breakdown →

13.

McCloskey, Kevin. (2016). The Real Poop on Pigeons. 1 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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