What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Machine learning
Fei-Yue Wang mostly deals with Artificial intelligence, Intelligent transportation system, Environmental chemistry, Sediment and Artificial neural network.
Fei-Yue Wang usually deals with Artificial intelligence and limits it to topics linked to Machine learning and Traffic generation model.
His work in the fields of Intelligent transportation system, such as Advanced Traffic Management System, intersects with other areas such as Poison control.
His study in Environmental chemistry is interdisciplinary in nature, drawing from both Ecological risk, Manganese, Bioavailability, Oxygen and Methylmercury.
His Sediment research also works with subjects such as
- Ecology which intersects with area such as Mercury,
- Environmental engineering most often made with reference to Pollution.
His Artificial neural network research is multidisciplinary, relying on both Mathematical optimization, Relation, Adaptive control and Reinforcement learning.
His most cited work include:
- Traffic Flow Prediction With Big Data: A Deep Learning Approach (1353 citations)
- Data-Driven Intelligent Transportation Systems: A Survey (655 citations)
- Adaptive Dynamic Programming: An Introduction (614 citations)
What are the main themes of his work throughout his whole career to date?
Fei-Yue Wang focuses on Artificial intelligence, Intelligent transportation system, Machine learning, Mercury and Computer vision.
His research links Pattern recognition with Artificial intelligence.
His work carried out in the field of Mercury brings together such families of science as Environmental chemistry and Oceanography.
His study in Oceanography focuses on Sea ice and Arctic.
He most often published in these fields:
- Artificial intelligence (24.76%)
- Intelligent transportation system (7.15%)
- Machine learning (6.30%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (24.76%)
- Deep learning (5.66%)
- Machine learning (6.30%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Deep learning, Machine learning, Pattern recognition and Computer vision.
His work in Image, Segmentation, Object detection, Artificial neural network and Feature extraction are all subfields of Artificial intelligence research.
His Deep learning study incorporates themes from Intelligent transportation system, Data mining and Traffic flow.
His Machine learning study combines topics from a wide range of disciplines, such as Adversarial system and Fuzzy logic.
Pattern recognition is closely attributed to Pascal in his research.
Between 2018 and 2021, his most popular works were:
- Blockchain-Enabled Smart Contracts: Architecture, Applications, and Future Trends (161 citations)
- Characterizing the Propagation of Situational Information in Social Media During COVID-19 Epidemic: A Case Study on Weibo (127 citations)
- Driver Activity Recognition for Intelligent Vehicles: A Deep Learning Approach (63 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Machine learning
The scientist’s investigation covers issues in Artificial intelligence, Deep learning, Machine learning, Pattern recognition and Artificial neural network.
His study connects Computer vision and Artificial intelligence.
Fei-Yue Wang combines subjects such as Intelligent transportation system and Data mining with his study of Deep learning.
His Intelligent transportation system research integrates issues from Complex system, Distributed computing and Traffic flow.
The various areas that he examines in his Machine learning study include Adversarial system and Fuzzy logic.
Automation and Data modeling is closely connected to Field in his research, which is encompassed under the umbrella topic of Adversarial system.
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