What is he best known for?
The fields of study he is best known for:
- Computer network
- Artificial intelligence
- Operating system
His main research concerns Computer network, Distributed computing, Wireless, Data science and Wireless sensor network.
His Computer network research is multidisciplinary, relying on both Energy consumption and Relay.
His Distributed computing study combines topics in areas such as Edge computing, Cloud computing, Server and Mobile device.
His Wireless research integrates issues from Quality of service, The Internet and Service.
His work deals with themes such as Duration, Social network, Recommender system, Random walk and Big data, which intersect with Data science.
Feng Xia has researched Wireless sensor network in several fields, including Network topology, Actuator, Embedded system, Cyber-physical system and Robustness.
His most cited work include:
- A survey on virtual machine migration and server consolidation frameworks for cloud data centers (217 citations)
- Vehicular Social Networks: Enabling Smart Mobility (206 citations)
- QoS challenges and opportunities in wireless sensor/actuator networks (181 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Computer network, Distributed computing, Wireless sensor network, Data science and Scheduling.
Within one scientific family, he focuses on topics pertaining to Wireless under Computer network, and may sometimes address concerns connected to Cyber-physical system.
His Distributed computing research is multidisciplinary, incorporating elements of Quality of service, Cloud computing, Communication channel and Mobile device.
His work in Wireless sensor network tackles topics such as Energy consumption which are related to areas like Efficient energy use and Embedded system.
His Data science study integrates concerns from other disciplines, such as Citation and Big data.
In his research, Real-time computing is intimately related to Control system, which falls under the overarching field of Scheduling.
He most often published in these fields:
- Computer network (23.88%)
- Distributed computing (16.12%)
- Wireless sensor network (12.45%)
What were the highlights of his more recent work (between 2019-2021)?
- Theoretical computer science (4.49%)
- Artificial intelligence (8.16%)
- Data science (10.20%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Theoretical computer science, Artificial intelligence, Data science, Node and Network science.
His Theoretical computer science study combines topics from a wide range of disciplines, such as Representation, Network analysis and Link.
His Artificial intelligence study also includes
- Machine learning which connect with Social network,
- Biological network together with Multivariate statistics.
Feng Xia focuses mostly in the field of Data science, narrowing it down to topics relating to Big data and, in certain cases, Citation, Network topology and Network embedding.
His Node study improves the overall literature in Computer network.
His research ties Vehicular ad hoc network and Computer network together.
Between 2019 and 2021, his most popular works were:
- Community-diversified influence maximization in social networks (60 citations)
- Vehicle Trajectory Clustering Based on Dynamic Representation Learning of Internet of Vehicles (25 citations)
- Random Walks: A Review of Algorithms and Applications (19 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer network
- Operating system
Network analysis, Data mining, Node, Exploit and Big data are his primary areas of study.
His Network analysis research also works with subjects such as
- Network model which is related to area like Partition, Empirical research and Public transport,
- Embedding together with Heterogeneous network and Hidden Markov model.
The Data mining study combines topics in areas such as Trajectory, Wavelet and Base station.
His Exploit research incorporates elements of Credibility, Vehicular ad hoc network, Biological network, Transmission delay and Computer network.
The concepts of his Big data study are interwoven with issues in Citation, Mean reciprocal rank, Collaborative filtering, Information overload and Data science.
His work on Computational sociology as part of general Data science research is often related to Social issues, thus linking different fields of science.
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