Dino Di Carlo

29.7k total citations · 13 hit papers
294 papers, 22.5k citations indexed

About

Dino Di Carlo is a scholar working on Biomedical Engineering, Molecular Biology and Electrical and Electronic Engineering. According to data from OpenAlex, Dino Di Carlo has authored 294 papers receiving a total of 22.5k indexed citations (citations by other indexed papers that have themselves been cited), including 225 papers in Biomedical Engineering, 58 papers in Molecular Biology and 49 papers in Electrical and Electronic Engineering. Recurrent topics in Dino Di Carlo's work include Microfluidic and Bio-sensing Technologies (136 papers), 3D Printing in Biomedical Research (71 papers) and Microfluidic and Capillary Electrophoresis Applications (66 papers). Dino Di Carlo is often cited by papers focused on Microfluidic and Bio-sensing Technologies (136 papers), 3D Printing in Biomedical Research (71 papers) and Microfluidic and Capillary Electrophoresis Applications (66 papers). Dino Di Carlo collaborates with scholars based in United States, Japan and South Korea. Dino Di Carlo's co-authors include Mehmet Toner, Luke P. Lee, Soojung Hur, Daniel Irimia, Daniel R. Gossett, Westbrook M. Weaver, Hamed Amini, Ronald G. Tompkins, Henry T. K. Tse and Albert J. Mach and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Dino Di Carlo

288 papers receiving 22.2k citations

Hit Papers

Continuous inertial focusing, ordering, and separation of... 2006 2026 2012 2019 2007 2009 2015 2010 2012 400 800 1.2k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Continuous inertial focusing, ordering, and separation of particles in microchannels
    2007 1.4k citations Dino Di Carlo et al. profile →
  2. Inertial microfluidics
    2009 1.3k citations Dino Di Carlo Lab on a Chip profile →
  3. Accelerated wound healing by injectable microporous gel scaffolds assembled from annealed building blocks
    2015 776 citations Donald R. Griffin, Dino Di Carlo et al. profile →
  4. Label-free cell separation and sorting in microfluidic systems
    2010 731 citations Dino Di Carlo et al. profile →
  5. Hydrodynamic stretching of single cells for large population mechanical phenotyping
    2012 605 citations Dino Di Carlo et al. profile →
  6. Inertial microfluidic physics
    2014 582 citations Dino Di Carlo et al. Lab on a Chip profile →
  7. Dynamic single cell culture array
    2006 578 citations Dino Di Carlo et al. Lab on a Chip profile →
  8. Deformability-based cell classification and enrichment using inertial microfluidics
    2011 459 citations Dino Di Carlo et al. Lab on a Chip profile →
  9. Particle Segregation and Dynamics in Confined Flows
    2009 442 citations Dino Di Carlo et al. profile →
  10. Size-selective collection of circulating tumor cells using Vortex technology
    2013 432 citations Dino Di Carlo et al. Lab on a Chip profile →
  11. Tuning Molecular Interactions for Highly Reproducible and Efficient Formamidinium Perovskite Solar Cells via Adduct Approach
    2018 418 citations Dino Di Carlo et al. profile →
  12. Activating an adaptive immune response from a hydrogel scaffold imparts regenerative wound healing
    2020 389 citations Donald R. Griffin, Dino Di Carlo et al. profile →
  13. Machine learning in point-of-care testing: innovations, challenges, and opportunities
    2025 47 citations Gyeo‐Re Han, Merve Eryılmaz et al. Nature Communications profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Dino Di Carlo United States 74 17.9k 5.2k 2.9k 1.7k 1.6k 294 22.5k
David J. Beebe United States 76 21.8k 1.2× 5.4k 1.0× 4.1k 1.4× 776 0.5× 1.2k 0.8× 395 29.4k
Shuichi Takayama United States 75 14.8k 0.8× 3.1k 0.6× 4.7k 1.6× 799 0.5× 490 0.3× 317 22.5k
Tony Jun Huang United States 92 21.8k 1.2× 6.7k 1.3× 4.0k 1.3× 3.2k 1.9× 706 0.4× 393 28.8k
Wilhelm T. S. Huck Netherlands 91 14.4k 0.8× 7.9k 1.5× 5.7k 2.0× 2.3k 1.4× 666 0.4× 367 33.1k
Nam‐Trung Nguyen Australia 91 20.8k 1.2× 11.1k 2.1× 4.6k 1.6× 1.2k 0.7× 2.3k 1.5× 745 32.4k
Albert van den Berg Netherlands 76 16.5k 0.9× 7.7k 1.5× 3.0k 1.0× 1.0k 0.6× 929 0.6× 633 24.2k
Ming Dao United States 68 5.6k 0.3× 1.4k 0.3× 2.8k 1.0× 2.1k 1.2× 881 0.6× 192 20.2k
Chwee Teck Lim Singapore 105 21.5k 1.2× 7.2k 1.4× 5.7k 1.9× 3.3k 1.9× 903 0.6× 578 43.9k
Milan Mrksich United States 84 11.7k 0.7× 4.8k 0.9× 12.0k 4.1× 2.2k 1.3× 324 0.2× 266 27.8k
George M. Whitesides United States 78 20.5k 1.1× 7.9k 1.5× 3.4k 1.2× 3.3k 1.9× 585 0.4× 202 31.2k

Countries citing papers authored by Dino Di Carlo

Since Specialization
Citations

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

Fields of papers citing papers by Dino Di Carlo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dino Di Carlo. 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 Dino Di Carlo. The network helps show where Dino Di Carlo may publish in the future.

Co-authorship network of co-authors of Dino Di Carlo

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

All Works

20 of 20 papers shown
1.
Lee, Kelvin C. M., Fabio Lisi, Tianben Ding, et al.. (2025). Serendipity Engineering with Photonics: Harnessing the Unexpected in Biology and Medicine(Invited paper). Electromagnetic waves. 184. 14–23.
2.
Han, Gyeo‐Re, Merve Eryılmaz, Rajesh Ghosh, et al.. (2025). Machine learning in point-of-care testing: innovations, challenges, and opportunities. Nature Communications. 16(1). 3165–3165. 47 indexed citations breakdown →
3.
Zhang, Tianlong, Dino Di Carlo, Chwee Teck Lim, et al.. (2024). Passive microfluidic devices for cell separation. Biotechnology Advances. 71. 108317–108317. 39 indexed citations
4.
Ghosh, Rajesh, Hyou‐Arm Joung, Kevin Ngo, et al.. (2024). Rapid single-tier serodiagnosis of Lyme disease. Nature Communications. 15(1). 7124–7124. 10 indexed citations
5.
Yang, Xilin, Derek Tseng, Yi Luo, et al.. (2023). Amphiphilic Particle-Stabilized Nanoliter Droplet Reactors with a Multimodal Portable Reader for Distributive Biomarker Quantification. ACS Nano. 17(20). 19952–19960. 12 indexed citations
6.
7.
Joung, Hyou‐Arm, Rajesh Ghosh, Gyeo‐Re Han, et al.. (2023). Deep Learning‐Enabled Multiplexed Point‐of‐Care Sensor using a Paper‐Based Fluorescence Vertical Flow Assay. Small. 19(51). e2300617–e2300617. 25 indexed citations
8.
Ng, Simon K. K., et al.. (2021). Statistical energy minimization theory for systems of drop-carrier particles. Physical review. E. 104(1). 15109–15109. 4 indexed citations
9.
10.
Rutte, Joseph de, et al.. (2021). Selective and Improved Photoannealing of Microporous Annealed Particle (MAP) Scaffolds. ACS Biomaterials Science & Engineering. 7(2). 422–427. 24 indexed citations
11.
Destgeer, Ghulam, Mengxing Ouyang, & Dino Di Carlo. (2021). Engineering Design of Concentric Amphiphilic Microparticles for Spontaneous Formation of Picoliter to Nanoliter Droplet Volumes. Analytical Chemistry. 93(4). 2317–2326. 18 indexed citations
12.
Muñoz, Hector E., Carson T. Riche, Mark van Zee, et al.. (2020). Fractal LAMP: Label-Free Analysis of Fractal Precipitate for Digital Loop-Mediated Isothermal Nucleic Acid Amplification. ACS Sensors. 5(2). 385–394. 35 indexed citations
13.
Destgeer, Ghulam, Mengxing Ouyang, Chueh‐Yu Wu, & Dino Di Carlo. (2020). Fabrication of 3D concentric amphiphilic microparticles to form uniform nanoliter reaction volumes for amplified affinity assays. Lab on a Chip. 20(19). 3503–3514. 32 indexed citations
14.
Wu, Chueh‐Yu, Mengxing Ouyang, Bao Wang, et al.. (2020). Monodisperse drops templated by 3D-structured microparticles. Science Advances. 6(45). 28 indexed citations
15.
Stoecklein, Daniel, et al.. (2019). FlowSculpt: software for efficient design of inertial flow sculpting devices. Lab on a Chip. 19(19). 3277–3291. 10 indexed citations
16.
Joung, Hyou‐Arm, Zachary S. Ballard, Alice Ma, et al.. (2019). Paper-based multiplexed vertical flow assay for point-of-care testing. Lab on a Chip. 19(6). 1027–1034. 57 indexed citations
17.
Zhang, Yibo, Mengxing Ouyang, Aniruddha Ray, et al.. (2019). Computational cytometer based on magnetically modulated coherent imaging and deep learning. Light Science & Applications. 8(1). 91–91. 24 indexed citations
18.
Wei, Qingshan, et al.. (2018). Ferrodrop Dose-Optimized Digital Quantification of Biomolecules in Low-Volume Samples. Analytical Chemistry. 90(15). 8881–8888. 7 indexed citations
19.
Carlo, Dino Di, et al.. (2018). Integration of inertial microchannels and droplet generators for controlled encapsulation of single cells. Bulletin of the American Physical Society. 2018. 1 indexed citations
20.
Wei, Qingshan, Derek Tseng, Jingzi Zhang, et al.. (2017). Highly Stable and Sensitive Nucleic Acid Amplification and Cell-Phone-Based Readout. ACS Nano. 11(3). 2934–2943. 106 indexed citations

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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