What is he best known for?
The fields of study he is best known for:
His primary areas of study are Microfluidics, Nanotechnology, Inertial frame of reference, Mechanics and Lift.
His Microfluidics study combines topics from a wide range of disciplines, such as Microscale chemistry, Analytical chemistry, Biological system and Single-cell analysis.
His research on Nanotechnology focuses in particular on Microchannel.
His Inertial frame of reference research includes elements of Flow velocity and Inertial effect.
His study in Mechanics is interdisciplinary in nature, drawing from both Particle-laden flows, Communication channel, Particle dynamics and Microfluidic channel.
His Lift research incorporates themes from Streamlines, streaklines, and pathlines, Laminar flow, Transverse plane and Fictitious force, Classical mechanics.
His most cited work include:
- Continuous inertial focusing, ordering, and separation of particles in microchannels (1103 citations)
- Label-free cell separation and sorting in microfluidic systems (678 citations)
- Label-free cell separation and sorting in microfluidic systems (678 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Microfluidics, Nanotechnology, Mechanics, Inertial frame of reference and Throughput.
His Microfluidics study combines topics in areas such as Analytical chemistry, Microscale chemistry, Communication channel, Biological system and Biomedical engineering.
His Biomedical engineering study frequently links to adjacent areas such as Cell.
As part of his studies on Nanotechnology, he frequently links adjacent subjects like Sorting.
His Mechanics study typically links adjacent topics like Lift.
Dino Di Carlo performs integrative study on Throughput and Computer hardware.
He most often published in these fields:
- Microfluidics (41.11%)
- Nanotechnology (37.18%)
- Mechanics (16.86%)
What were the highlights of his more recent work (between 2018-2021)?
- Microfluidics (41.11%)
- Artificial intelligence (6.70%)
- Deep learning (3.93%)
In recent papers he was focusing on the following fields of study:
Dino Di Carlo spends much of his time researching Microfluidics, Artificial intelligence, Deep learning, Nanotechnology and Cell sorting.
His Microfluidics research includes themes of Tissue engineering, Microporous material, Self-healing hydrogels, Chemical engineering and Microscale chemistry.
His research investigates the connection between Microscale chemistry and topics such as Dispersity that intersect with issues in Surface energy.
The various areas that he examines in his Artificial intelligence study include Detection limit and Computer vision.
His research on Deep learning also deals with topics like
- Artificial neural network together with Pattern recognition, Synthetic biology and Fluorescence-lifetime imaging microscopy,
- Multiplexing together with Serum samples,
- Antimicrobial susceptibility which connect with Gold standard.
His studies deal with areas such as Sorting, Image and Lab-on-a-chip as well as Cell sorting.
Between 2018 and 2021, his most popular works were:
- Microfluidic-enabled bottom-up hydrogels from annealable naturally-derived protein microbeads. (37 citations)
- Scalable High‐Throughput Production of Modular Microgels for In Situ Assembly of Microporous Tissue Scaffolds (34 citations)
- A practical guide to intelligent image-activated cell sorting. (25 citations)
In his most recent research, the most cited papers focused on:
His primary areas of investigation include Microfluidics, Nanotechnology, Sorting, Cell sorting and Throughput.
With his scientific publications, his incorporates both Microfluidics and Sampling.
His biological study focuses on Lab-on-a-chip.
His Sorting research is multidisciplinary, relying on both Droplet microfluidics, Limiting, Biological system and Dielectrophoretic force.
His Cell sorting research integrates issues from Deep learning and Artificial intelligence.
His Tissue engineering research incorporates elements of Matrix, Mesenchymal stem cell, Stem cell and Microparticle.
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