Tim Chang

723 citations
26 papers · 590 · h-index 9

Impact in

    • Innovative Microfluidic and Catalytic Techniques Innovation
    • 3D Printing in Biomedical Research
    • Microfluidic and Capillary Electrophoresis Applications
    • Microfluidic and Bio-sensing Technologies
    • Biosensors and Analytical Detection
    • Additive Manufacturing and 3D Printing Technologies

Papers in

Tim Chang

24 papers receiving 577 citations

Peers

Tim Chang
Comparison fields: 5 of 87
  • Biomedical Engineering 412
  • Automotive Engineering 78
  • Biophysics 24
  • Molecular Biology 118
  • Oncology 36
Replace Elena Bianchi with:
Elena Bianchi Italy
Mathias Busek Germany
Daniel E. Shea United States
Helene Zirath Austria
Hongtong Li China
Meitham Amereh Canada
Chae Yun Bae South Korea
Marco Serra France
Alan M. Gonzalez‐Suarez United States
Tim Chang relative to Elena Bianchi Italy Elena Bianchi's profile →
Citations per field
00.5×3.1×
Elena Bianchi · 1×
Citations per year

Countries citing papers authored by Tim Chang

Since Specialization
Citations

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

Fields of papers citing papers by Tim Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Tim Chang, 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 Tim Chang Line = papers co-authored together Tim Chang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015276
2 201475
3 202041
4 201838
5 201928
6 201925
7 201724
8 201711
9 20109
10 20158
11 20218
12 20197
13 20197
14 20167
15 20226
16 20166
17 20153
18 20113
19 20232
20 20222

About Tim Chang

Tim Chang is a scholar working on Biomedical Engineering, Electrical and Electronic Engineering, Control and Systems Engineering, Physiology and Molecular Biology, having authored 26 papers that have together received 590 indexed citations. Recurring topics across this work include Innovative Microfluidic and Catalytic Techniques Innovation (6 papers), Microfluidic and Capillary Electrophoresis Applications (5 papers), Microfluidic and Bio-sensing Technologies (4 papers), Erythrocyte Function and Pathophysiology (4 papers), 3D Printing in Biomedical Research (4 papers), Blood groups and transfusion (3 papers), Risk and Safety Analysis (2 papers) and Microgrid Control and Optimization (2 papers). The work is most often cited by research in Biomedical Engineering (412 citations), Automotive Engineering (78 citations), Biophysics (24 citations), Molecular Biology (118 citations) and Oncology (36 citations). Tim Chang has collaborated with scholars based in United States, Taiwan and Germany. Frequent co-authors include Nirveek Bhattacharjee, Lisa F. Horowitz, Anthony K. Au, Albert Folch, Albert Folch, Raymond J. Monnat, Samantha A. Byrnes, Andrei M. Mikheev, Toan Huynh and Robert Rostomily. Their work appears in journals such as Analytical Chemistry, Lab on a Chip, Cytometry Part A, Journal of Cellular Biochemistry and Blood.

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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