Hugh Cartwright

5.5k citations
48 papers · 3.9k indexed · 1 hit paper · h-index 16

Impact in

Papers in

Hugh Cartwright

40 papers receiving 3.8k citations

Hit Papers

Machine learning for molecular and materials science 2018 · 3.1k citations
3.1k201820262020202310002.0k3.0k

Peers

Hugh Cartwright
Comparison fields: 5 of 172
  • Materials Chemistry 2.2k
  • Computational Theory and Mathematics 692
  • Metals and Alloys 79
  • Structural Biology 29
  • Catalysis 135
Replace Daniel W. Davies with:
Daniel W. Davies United Kingdom
Chiho Kim United States
Noam Bernstein United States
Rohit Batra United States
Wencong Lu China
Jonathan Schmidt Germany
Joshua Schrier United States
Leslie Vogt-Maranto United States
Katja Hansen Germany
Matthias Rupp Germany
Hugh Cartwright relative to Daniel W. Davies United Kingdom Daniel W. Davies's profile →
Citations per field
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Daniel W. Davies · 1×
Citations per year

Countries citing papers authored by Hugh Cartwright

Since Specialization
Citations

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

Fields of papers citing papers by Hugh Cartwright

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside Hugh Cartwright, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hugh Cartwright Line = papers co-authored together Hugh Cartwright links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20180
2
Machine learning for molecular and materials science
Hit paper breakdown →
20183052
3
Why Should On-line Experiments Form Part of University Science Courses?
20120
4
Using Artificial Intelligence in Chemistry and Biology: A Practical Guide (Chapman & Hall/Crc Research No)
20083
5 200822
6 200737
7 200740
8 20054
9 200325
10 20011
11
Intelligent Data Analysis in Science
20004
12 20000
13 19997
14 199841
15 19982
16 19981
17
The Application of the Genetic Algorithm to Two-Dimensional Strings: The Source Apportionment Problem
19938
18 19882
19 19869
20 197530

About Hugh Cartwright

Hugh Cartwright is a scholar working on Biophysics, Physical and Theoretical Chemistry, Computational Theory and Mathematics, Spectroscopy and Artificial Intelligence, having authored 48 papers that have together received 3.9k indexed citations. Recurring topics across this work include Advanced Chemical Physics Studies (5 papers), Various Chemistry Research Topics (4 papers), Computational Drug Discovery Methods (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Gene expression and cancer classification (3 papers), Advanced Control Systems Optimization (3 papers), Neural Networks and Applications (3 papers) and Process Optimization and Integration (3 papers). The work is most often cited by research in Materials Chemistry (2.2k citations), Computational Theory and Mathematics (692 citations), Metals and Alloys (79 citations), Structural Biology (29 citations) and Catalysis (135 citations). Hugh Cartwright has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Aron Walsh, Olexandr Isayev, Keith T. Butler, Daniel W. Davies, Jason W.H. Wong, Gerard Cagney, Silvia Curteanu, Caterina Durante, Walter J. Balfour and Xi Chen. Their work appears in journals such as Journal of Chemometrics, Industrial & Engineering Chemistry Research, International Journal of Intelligent Systems, Nature and Computers & Education.

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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