What is he best known for?
The fields of study he is best known for:
- Quantum mechanics
- Artificial intelligence
- Organic chemistry
Wen Yang focuses on Composite material, Enantioselective synthesis, Michael reaction, Squaramide and Catalysis.
His biological study spans a wide range of topics, including Arapaima and Keratin.
Enantioselective synthesis is a subfield of Organic chemistry that Wen Yang investigates.
His Michael reaction research incorporates elements of Bifunctional, Stereocenter, Stereochemistry, Combinatorial chemistry and Cascade reaction.
His Catalysis study combines topics in areas such as Surface modification, Carbonization, Inorganic chemistry and Carbon nanotube.
The various areas that he examines in his Ultimate tensile strength study include Deformation mechanism, Compressive strength, Shell and Tension.
His most cited work include:
- Efficient metal-free oxygen reduction in alkaline medium on high-surface-area mesoporous nitrogen-doped carbons made from ionic liquids and nucleobases. (663 citations)
- A Mitochondrial Superoxide Signal Triggers Increased Longevity in Caenorhabditis elegans (441 citations)
- Keratin: Structure, mechanical properties, occurrence in biological organisms, and efforts at bioinspiration (279 citations)
What are the main themes of his work throughout his whole career to date?
Wen Yang mostly deals with Artificial intelligence, Pattern recognition, Computer vision, Synthetic aperture radar and Catalysis.
His Pattern recognition study combines topics from a wide range of disciplines, such as Change detection and Cluster analysis.
His work on Object detection and Image resolution as part of general Computer vision research is often related to Event, thus linking different fields of science.
His Synthetic aperture radar study incorporates themes from Radar imaging and Speckle pattern.
His Catalysis research includes elements of Combinatorial chemistry and Inorganic chemistry.
His Enantioselective synthesis research focuses on Michael reaction and how it connects with Squaramide.
He most often published in these fields:
- Artificial intelligence (31.65%)
- Pattern recognition (20.16%)
- Computer vision (17.14%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (31.65%)
- Computer vision (17.14%)
- Chemical engineering (8.27%)
In recent papers he was focusing on the following fields of study:
Wen Yang spends much of his time researching Artificial intelligence, Computer vision, Chemical engineering, Pattern recognition and Event.
His research in Convolutional neural network, Image segmentation, Pixel, Deep learning and Feature are components of Artificial intelligence.
The study incorporates disciplines such as Modality, Line and Asynchronous communication in addition to Computer vision.
His Chemical engineering research includes themes of Electrolyte, Faraday efficiency, Anode, Ion and Carbon.
The study of Carbon is intertwined with the study of Mesoporous material in a number of ways.
The concepts of his Pattern recognition study are interwoven with issues in Synthetic aperture radar and Gaussian.
Between 2019 and 2021, his most popular works were:
- Revealing of Active Sites and Catalytic Mechanism in N-Coordinated Fe, Ni Dual-Doped Carbon with Superior Acidic Oxygen Reduction than Single-Atom Catalyst. (22 citations)
- Learning Center Probability Map for Detecting Objects in Aerial Images (11 citations)
- Pore structure regulation of hard carbon: Towards fast and high-capacity sodium-ion storage. (9 citations)
In his most recent research, the most cited papers focused on:
- Quantum mechanics
- Artificial intelligence
- Organic chemistry
Artificial intelligence, Chemical engineering, Carbon, Feature extraction and Computer vision are his primary areas of study.
As part of one scientific family, Wen Yang deals mainly with the area of Artificial intelligence, narrowing it down to issues related to the Pattern recognition, and often Pixel.
His Chemical engineering research is multidisciplinary, incorporating elements of Doping, Dopant and Electrolyte, Faraday efficiency, Electrode.
His work carried out in the field of Carbon brings together such families of science as Heterogeneous catalysis, Yield, Microporous material, Mesoporous material and Density functional theory.
His work deals with themes such as Semantics, Image segmentation, Discriminative model and Remote sensing, which intersect with Feature extraction.
His research investigates the connection between Computer vision and topics such as Line that intersect with issues in Modality, Projection, Monocular camera and Lidar.
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