Kai‐Tai Chang

23 total papers · 710 total citations
20 papers, 557 citations indexed

About

Kai‐Tai Chang is a scholar working on Molecular Medicine, Pharmacology and Applied Microbiology and Biotechnology. According to data from OpenAlex, Kai‐Tai Chang has authored 20 papers receiving a total of 557 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Medicine, 18 papers in Pharmacology and 6 papers in Applied Microbiology and Biotechnology. Recurrent topics in Kai‐Tai Chang's work include Antibiotic Resistance in Bacteria (19 papers), Antibiotics Pharmacokinetics and Efficacy (18 papers) and Antibiotic Use and Resistance (6 papers). Kai‐Tai Chang is often cited by papers focused on Antibiotic Resistance in Bacteria (19 papers), Antibiotics Pharmacokinetics and Efficacy (18 papers) and Antibiotic Use and Resistance (6 papers). Kai‐Tai Chang collaborates with scholars based in United States, Spain and Belgium. Kai‐Tai Chang's co-authors include Vincent H. Tam, Kimberly R. Ledesma, Kamilia Abdelraouf, Kevin W. Garey, Henrietta Abodakpi, Song Gao, Michael Nikolaou, Jaye Weston, Magdalene Ameka and Ana María Sánchez‐Díaz and has published in prestigious journals such as Antimicrobial Agents and Chemotherapy, Journal of Antimicrobial Chemotherapy and Clinical Microbiology and Infection.

In The Last Decade

Kai‐Tai Chang

20 papers receiving 536 citations

Author Peers

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

Author Last Decade Papers Cites
Kai‐Tai Chang 401 318 155 146 116 20 557
Concepción Segura 437 1.1× 266 0.8× 181 1.2× 92 0.6× 92 0.8× 12 549
Pablo A. Fraile-Ribot 556 1.4× 335 1.1× 153 1.0× 203 1.4× 167 1.4× 31 648
Anna Vickers 499 1.2× 326 1.0× 199 1.3× 188 1.3× 145 1.3× 23 687
Henrietta Abodakpi 487 1.2× 347 1.1× 156 1.0× 190 1.3× 78 0.7× 12 551
Georgios L. Voulgaris 311 0.8× 289 0.9× 247 1.6× 112 0.8× 56 0.5× 10 554
Dimitris Goukos 424 1.1× 277 0.9× 242 1.6× 141 1.0× 99 0.9× 15 690
Ellen G Kline 517 1.3× 388 1.2× 192 1.2× 186 1.3× 67 0.6× 38 689
Anima Poudyal 528 1.3× 329 1.0× 173 1.1× 78 0.5× 131 1.1× 10 633
Stephania Stump 319 0.8× 210 0.7× 108 0.7× 76 0.5× 126 1.1× 12 525
Joseph Rutter 386 1.0× 221 0.7× 105 0.7× 117 0.8× 155 1.3× 18 633

Countries citing papers authored by Kai‐Tai Chang

Since Specialization
Citations

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

Fields of papers citing papers by Kai‐Tai Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kai‐Tai 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 Kai‐Tai Chang. The network helps show where Kai‐Tai Chang may publish in the future.

Co-authorship network of co-authors of Kai‐Tai Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Kai‐Tai Chang. A scholar is included among the top collaborators of Kai‐Tai 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 Kai‐Tai Chang. Kai‐Tai 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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