Ivan Pushkarsky
Impact in
- Biophysics top 10%
-
- Asthma and respiratory diseases
Papers in
-
- 3D Printing in Biomedical Research 5
- Microfluidic and Bio-sensing Technologies 4
- Microfluidic and Capillary Electrophoresis Applications 2
- Nanoplatforms for cancer theranostics 1
- Optical Coherence Tomography Applications 1
-
- Cellular Mechanics and Interactions 6
- Co-authors
- Dino Di Carlo (13 shared papers)Peter Tseng (3 shared papers)Robert Damoiseaux (6 shared papers)Reynold A. Panettieri (3 shared papers)Ting‐Wei Su (2 shared papers)Yunbo Liu (2 shared papers)Westbrook M. Weaver (2 shared papers)Aydogan Özcan (2 shared papers)
- Journals
- Lab on a Chip (5 papers)Scientific Reports (2 papers)British Journal of Pharmacology (2 papers)Nature Biomedical Engineering (1 paper)Assay and Drug Development Technologies (1 paper)
- Partner nations
- United StatesGermanyItaly
In The Last Decade
Ivan Pushkarsky
15 papers receiving 289 citations
Peers
Comparison fields: 5 of 69
- Biophysics 30
- Physiology 70
- Cell Biology 46
- Biomedical Engineering 107
- Pulmonary and Respiratory Medicine 59
Countries citing papers authored by Ivan Pushkarsky
This map shows the geographic impact of Ivan Pushkarsky'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 Ivan Pushkarsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Pushkarsky more than expected).
Fields of papers citing papers by Ivan Pushkarsky
This network shows the impact of papers produced by Ivan Pushkarsky. 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 Ivan Pushkarsky. The network helps show where Ivan Pushkarsky may publish in the future.
Co-authors
The 25 scholars most cited alongside Ivan Pushkarsky, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 62 | |
| 2 | 2018 | 48 | |
| 3 | 2018 | 44 | |
| 4 | 2016 | 38 | |
| 5 | 2017 | 30 | |
| 6 | 2014 | 27 | |
| 7 | 2015 | 9 | |
| 8 | 2014 | 9 | |
| 9 | 2015 | 6 | |
| 10 | 2014 | 5 | |
| 11 | 2017 | 4 | |
| 12 | 2014 | 4 | |
| 13 | 2014 | 3 | |
| 14 | 2019 | 1 | |
| 15 | 2022 | 1 | |
| 16 | 2023 | 0 |
About Ivan Pushkarsky
Ivan Pushkarsky is a scholar working on Biomedical Engineering, Cell Biology, Molecular Biology, Pulmonary and Respiratory Medicine and Biophysics, having authored 16 papers that have together received 291 indexed citations. Recurring topics across this work include Cellular Mechanics and Interactions (6 papers), 3D Printing in Biomedical Research (5 papers), Microfluidic and Bio-sensing Technologies (4 papers), Advanced Fluorescence Microscopy Techniques (2 papers), Microfluidic and Capillary Electrophoresis Applications (2 papers), Nanoplatforms for cancer theranostics (1 paper), Microbial Inactivation Methods (1 paper) and Optical Coherence Tomography Applications (1 paper). The work is most often cited by research in Biophysics (30 citations), Physiology (70 citations), Cell Biology (46 citations), Biomedical Engineering (107 citations) and Pulmonary and Respiratory Medicine (59 citations). Ivan Pushkarsky has collaborated with scholars based in United States, Germany and Italy. Frequent co-authors include Dino Di Carlo, Peter Tseng, Robert Damoiseaux, Reynold A. Panettieri, Ting‐Wei Su, Yunbo Liu, Westbrook M. Weaver, Aydogan Özcan, Onur Mudanyali and Gaoyuan Cao. Their work appears in journals such as Lab on a Chip, Scientific Reports, British Journal of Pharmacology, Nature Biomedical Engineering and Assay and Drug Development Technologies.
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.