What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
His scientific interests lie mostly in Artificial intelligence, Control theory, Information retrieval, Fuzzy logic and Pattern recognition.
His work in Artificial intelligence is not limited to one particular discipline; it also encompasses Machine learning.
He has included themes like Visualization and Process in his Machine learning study.
His Control theory research incorporates themes from Control engineering and Model predictive control.
Xiao Wu interconnects Cluster analysis, Similarity measure, World Wide Web and Image retrieval in the investigation of issues within Information retrieval.
His Pattern recognition research is multidisciplinary, incorporating elements of Contextual image classification and Robustness.
His most cited work include:
- Effectiveness of convalescent plasma therapy in severe COVID-19 patients. (1013 citations)
- Exposure to air pollution and COVID-19 mortality in the United States: A nationwide cross-sectional study. (500 citations)
- Hierarchical spatio-temporal context modeling for action recognition (335 citations)
What are the main themes of his work throughout his whole career to date?
Xiao Wu mainly investigates Artificial intelligence, Control theory, Model predictive control, Computer vision and Information retrieval.
He has researched Artificial intelligence in several fields, including Machine learning and Pattern recognition.
Xiao Wu combines subjects such as Control engineering, Power station and Fuzzy logic with his study of Control theory.
His biological study spans a wide range of topics, including Control system, Stability and Optimal control.
In Computer vision, he works on issues like Coding, which are connected to Perceptual Distortion.
His studies in Information retrieval integrate themes in fields like World Wide Web and Image retrieval.
He most often published in these fields:
- Artificial intelligence (21.83%)
- Control theory (12.68%)
- Model predictive control (10.21%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (21.83%)
- Confidence interval (2.82%)
- Mortality rate (2.11%)
In recent papers he was focusing on the following fields of study:
Artificial intelligence, Confidence interval, Mortality rate, Power station and Sediment are his primary areas of study.
He specializes in Artificial intelligence, namely Deep learning.
His Confidence interval research includes themes of Obesity, Confounding and Environmental health.
Xiao Wu works mostly in the field of Mortality rate, limiting it down to topics relating to Epidemiology and, in certain cases, Toxicology.
His Power station research is multidisciplinary, incorporating perspectives in Time constant, Electric power industry, Electric power system, Process engineering and Renewable energy.
The Internal medicine study combines topics in areas such as Titer and Antibody.
Between 2019 and 2021, his most popular works were:
- Effectiveness of convalescent plasma therapy in severe COVID-19 patients. (1013 citations)
- Exposure to air pollution and COVID-19 mortality in the United States: A nationwide cross-sectional study. (500 citations)
- Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis. (116 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Machine learning
His primary scientific interests are in Environmental health, Mortality rate, Confidence interval, MEDLINE and Control theory.
His Environmental health research includes elements of Cross-sectional study and Obesity.
Xiao Wu has researched Mortality rate in several fields, including Epidemiology, Toxicology and Propensity score matching.
His work on Confidence interval is being expanded to include thematically relevant topics such as Causal inference.
His MEDLINE research is multidisciplinary, incorporating perspectives in Public health, Ageing, Regression analysis, Pediatrics and Confounding.
His Control theory research is multidisciplinary, relying on both Artificial neural network and Power station.
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