What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Organic chemistry
- Catalysis
The scientist’s investigation covers issues in Nanotechnology, Optoelectronics, Artificial intelligence, Photocatalysis and Photochemistry.
The concepts of his Nanotechnology study are interwoven with issues in Carbon, Chemical engineering and Scanning electron microscope.
In Optoelectronics, Fan Yang works on issues like Exciton, which are connected to Photovoltaics.
His Artificial intelligence research is multidisciplinary, relying on both Machine learning, Computer vision and Pattern recognition.
His Photocatalysis research focuses on Visible spectrum and how it connects with Hydrothermal circulation, Catalysis and Composite number.
His research in Heterojunction tackles topics such as Organic solar cell which are related to areas like Perylene.
His most cited work include:
- The molecular structure of green fluorescent protein (1321 citations)
- Evolutionary and biomedical insights from the rhesus macaque genome (1094 citations)
- Superpixel tracking (463 citations)
What are the main themes of his work throughout his whole career to date?
Fan Yang mainly investigates Artificial intelligence, Computer vision, Catalysis, Chemical engineering and Nanotechnology.
His studies in Artificial intelligence integrate themes in fields like Machine learning and Pattern recognition.
He specializes in Pattern recognition, namely Convolutional neural network.
Image processing and Pixel are the subjects of his Computer vision studies.
Catalysis connects with themes related to Inorganic chemistry in his study.
His Nanotechnology study focuses on Graphene in particular.
He most often published in these fields:
- Artificial intelligence (18.80%)
- Computer vision (12.45%)
- Catalysis (9.28%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (18.80%)
- Chemical engineering (8.79%)
- Internal medicine (5.01%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Chemical engineering, Internal medicine, Oncology and Catalysis.
His studies deal with areas such as Machine learning, Computer vision and Pattern recognition as well as Artificial intelligence.
Fan Yang is interested in Graphene, which is a branch of Chemical engineering.
His work deals with themes such as Inorganic chemistry, Cobalt and Benzene, which intersect with Catalysis.
His Convolutional neural network research includes themes of Feature extraction and Feature.
His Carbon research integrates issues from Porosity, Nanotechnology, Photochemistry, Dielectric and Reflection loss.
Between 2019 and 2021, his most popular works were:
- Colorimetric fluorescent paper strip with smartphone platform for quantitative detection of cadmium ions in real samples. (21 citations)
- Towards Fast, Accurate and Stable 3D Dense Face Alignment. (20 citations)
- Production of hierarchical porous carbon nanosheets from cheap petroleum asphalt toward lightweight and high-performance electromagnetic wave absorbents (15 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Organic chemistry
- Catalysis
His primary areas of study are Chemical engineering, Carbon, Catalysis, Internal medicine and Oncology.
He combines subjects such as Slurry, Supercapacitor, Fluid catalytic cracking, Porous graphene and Aqueous solution with his study of Chemical engineering.
His Carbon research incorporates elements of Capacitance, Reflection loss, Graphitic carbon nitride and Dielectric.
His work carried out in the field of Reflection loss brings together such families of science as Porosity, Nanotechnology, Carbonization, Dielectric loss and Crystal.
His research investigates the link between Dielectric and topics such as Absorption that cross with problems in Optoelectronics.
His Catalysis study combines topics in areas such as Combinatorial chemistry, Cobalt, Radical and Intermolecular force.
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