What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Electrical engineering
The scientist’s investigation covers issues in Wind power, Control theory, Induction generator, Offshore wind power and Control theory.
His Wind power research integrates issues from Distributed generation, Wind speed, Control engineering, Automotive engineering and Energy storage.
Li Wang has researched Energy storage in several fields, including Electricity generation, Stand-alone power system, Photovoltaic system and Renewable energy.
His research is interdisciplinary, bridging the disciplines of Self excited induction generator and Control theory.
His Induction generator study combines topics from a wide range of disciplines, such as Equivalent circuit, AC power, Electric generator and Nonlinear system.
His Offshore wind power research is multidisciplinary, incorporating elements of PID controller and High-voltage direct current.
His most cited work include:
- Mapping and analysis of chromatin state dynamics in nine human cell types (2286 citations)
- Reversed graph embedding resolves complex single-cell trajectories. (954 citations)
- Intrathoracic Impedance Monitoring in Patients With Heart Failure Correlation With Fluid Status and Feasibility of Early Warning Preceding Hospitalization (594 citations)
What are the main themes of his work throughout his whole career to date?
Li Wang spends much of his time researching Control theory, Electric power system, Induction generator, Offshore wind power and Control theory.
His study looks at the relationship between Control theory and fields such as Permanent magnet synchronous generator, as well as how they intersect with chemical problems.
His study explores the link between Electric power system and topics such as Electrical engineering that cross with problems in Electricity generation.
Within one scientific family, he focuses on topics pertaining to AC power under Induction generator, and may sometimes address concerns connected to Transformer.
His Offshore wind power study is concerned with the larger field of Wind power.
His Wind power research is multidisciplinary, incorporating perspectives in Distributed generation and Automotive engineering.
He most often published in these fields:
- Control theory (35.41%)
- Electric power system (24.90%)
- Induction generator (24.12%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (12.45%)
- Graph (6.61%)
- Algorithm (4.28%)
In recent papers he was focusing on the following fields of study:
His main research concerns Artificial intelligence, Graph, Algorithm, Pattern recognition and Electric power system.
His research in the fields of Probabilistic logic, Feature extraction and Dimensionality reduction overlaps with other disciplines such as Data modeling.
His Electric power system study combines topics in areas such as Offshore wind power, Hybrid power, Control theory, Photovoltaic system and Induction generator.
He interconnects AC power, Submarine and Control theory in the investigation of issues within Induction generator.
As part of one scientific family, Li Wang deals mainly with the area of Transient, narrowing it down to issues related to the Hybrid system, and often Wind power.
His work deals with themes such as Electricity generation and Evolutionary computation, which intersect with Wind power.
Between 2018 and 2021, his most popular works were:
- Inferring Causal Gene Regulatory Networks from Coupled Single-Cell Expression Dynamics Using Scribe. (28 citations)
- Mapping Vector Field of Single Cells (22 citations)
- Mapping Transcriptomic Vector Fields of Single Cells (18 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Electrical engineering
His primary scientific interests are in Artificial intelligence, Wind power, Genetic algorithm, Canonical correlation and Mathematical optimization.
His research in Artificial intelligence intersects with topics in Functional connectivity, Human Connectome Project and Human brain.
His work carried out in the field of Wind power brings together such families of science as Wind speed, Reduction, Support vector machine, Optimization problem and Operations research.
The study incorporates disciplines such as Evolutionary computation and Electricity generation in addition to Genetic algorithm.
Li Wang combines subjects such as Distributed generation, Electric power industry and Voltage with his study of Mathematical optimization.
His Dimensionality reduction research integrates issues from Probabilistic logic, Feature learning and Graph embedding.
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