David McIntyre
- Biomedical Engineering top 10%
- Electrical and Electronic Engineering
- Molecular Biology
- Artificial Intelligence
- Materials Chemistry
- Co-authors
- Ali LashkaripourDouglas DensmorePolly M. FordyceNoushin MehdipourJoshua D. CampbellLuis OrtizSamuel M. D. OliveiraK. Kawata
- Topics
- Innovative Microfluidic and Catalytic Techniques Innovation (8 papers)Microfluidic and Capillary Electrophoresis Applications (8 papers)Electrowetting and Microfluidic Technologies (6 papers)
- Journals
- Nature CommunicationsLab on a ChipIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
- Partner nations
- United States
In The Last Decade
David McIntyre
7 papers receiving 307 citations
Peers
Comparison fields: 5 of 61
- Biomedical Engineering 270
- Electrical and Electronic Engineering 131
- Molecular Biology 29
- Artificial Intelligence 28
- Materials Chemistry 19
Countries citing papers authored by David McIntyre
This map shows the geographic impact of David McIntyre'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 David McIntyre with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David McIntyre more than expected).
Fields of papers citing papers by David McIntyre
This network shows the impact of papers produced by David McIntyre. 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 David McIntyre. The network helps show where David McIntyre may publish in the future.
Co-authorship network of co-authors of David McIntyre
This figure shows the co-authorship network connecting the top 25 collaborators of David McIntyre. A scholar is included among the top collaborators of David McIntyre 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 David McIntyre. David McIntyre is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 35 | |
| 3 | 0 | |
| 4 | 4 | |
| 5 | 97 | |
| 6 | 156 | |
| 7 | Active learning for efficient microfluidic design automation | 1 |
| 8 | 18 | |
| 9 | Modular microfluidic design automation using machine learning | 1 |
About David McIntyre
David McIntyre is a scholar working on Biomedical Engineering, Electrical and Electronic Engineering and Artificial Intelligence, having authored 9 papers that have together received 312 indexed citations. Recurring topics across this work include Innovative Microfluidic and Catalytic Techniques Innovation (8 papers), Microfluidic and Capillary Electrophoresis Applications (8 papers) and Electrowetting and Microfluidic Technologies (6 papers). The work is most often cited by research in Biomedical Engineering (270 citations), Electrical and Electronic Engineering (131 citations) and Biophysics (9 citations). David McIntyre has collaborated with scholars based in United States. Frequent co-authors include Ali Lashkaripour, Douglas Densmore, Polly M. Fordyce, Noushin Mehdipour, Joshua D. Campbell, Luis Ortiz, Samuel M. D. Oliveira and K. Kawata. Their work appears in journals such as Nature Communications, Lab on a Chip and IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.
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.