Daniel T. Chang

114 total papers · 796 total citations
40 papers, 422 citations indexed

About

Daniel T. Chang is a scholar working on Computational Theory and Mathematics, Molecular Biology and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Daniel T. Chang has authored 40 papers receiving a total of 422 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computational Theory and Mathematics, 8 papers in Molecular Biology and 8 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Daniel T. Chang's work include Computational Drug Discovery Methods (12 papers), Advanced Chemical Physics Studies (5 papers) and Animal testing and alternatives (4 papers). Daniel T. Chang is often cited by papers focused on Computational Drug Discovery Methods (12 papers), Advanced Chemical Physics Studies (5 papers) and Animal testing and alternatives (4 papers). Daniel T. Chang collaborates with scholars based in United States, Canada and Hong Kong. Daniel T. Chang's co-authors include Rogelio Tornero‐Velez, John C. Light, Michael‐Rock Goldsmith, Yu‐Mei Tan, Gregory K. Schenter, Bruce C. Garrett, Gregory I. Gellene, Chris Grulke, Michael R. Goldsmith and Jeremy A. Leonard and has published in prestigious journals such as The Journal of Chemical Physics, Environmental Science & Technology and Scientific Reports.

In The Last Decade

Daniel T. Chang

38 papers receiving 412 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Daniel T. Chang 122 88 83 78 61 40 422
Nikolai Georgiev Nikolov 136 1.1× 127 1.4× 25 0.3× 8 0.1× 68 1.1× 38 388
Julian Ivanov 72 0.6× 266 3.0× 20 0.2× 10 0.1× 73 1.2× 22 465
Marco Marzo 153 1.3× 217 2.5× 23 0.3× 5 0.1× 65 1.1× 23 376
Christof H. Schwab 56 0.5× 279 3.2× 14 0.2× 10 0.1× 184 3.0× 17 430
G Klopman 113 0.9× 218 2.5× 68 0.8× 3 0.0× 110 1.8× 18 433
Chang‐Hwei Chen 53 0.4× 26 0.3× 72 0.9× 38 0.5× 240 3.9× 42 494
Nitin Dubey 22 0.2× 9 0.1× 83 1.0× 46 0.6× 66 1.1× 40 432
Driss Zakarya 44 0.4× 190 2.2× 22 0.3× 5 0.1× 109 1.8× 36 424
Peter B. Hulbert 16 0.1× 15 0.2× 52 0.6× 8 0.1× 191 3.1× 17 394
Oliver Sacher 55 0.5× 209 2.4× 19 0.2× 2 0.0× 182 3.0× 15 387

Countries citing papers authored by Daniel T. Chang

Since Specialization
Citations

This map shows the geographic impact of Daniel T. Chang'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 Daniel T. Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel T. Chang more than expected).

Fields of papers citing papers by Daniel T. Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel T. Chang. 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 Daniel T. Chang. The network helps show where Daniel T. Chang may publish in the future.

Co-authorship network of co-authors of Daniel T. Chang

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

All Works

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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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