What is he best known for?
The fields of study he is best known for:
- Computer network
- Operating system
- Artificial intelligence
His primary areas of investigation include Computer network, Cloud computing, Distributed computing, The Internet and Energy consumption.
His biological study spans a wide range of topics, including Telecommunications and Scalability.
His study in Cloud computing is interdisciplinary in nature, drawing from both Quality of experience, Mobile device, Mobile computing and Provisioning.
His Distributed computing research is multidisciplinary, relying on both Network virtualization, Virtual network embedding, Communications protocol and Fault detection and isolation.
His The Internet research includes themes of Public-key cryptography, Key distribution, ID-based cryptography, Data science and Big data.
Yonggang Wen combines subjects such as Energy conservation, Virtual machine, Real-time computing, Server and Efficient energy use with his study of Energy consumption.
His most cited work include:
- Toward Scalable Systems for Big Data Analytics: A Technology Tutorial (712 citations)
- A Survey on Software-Defined Networking (530 citations)
- Data Center Energy Consumption Modeling: A Survey (383 citations)
What are the main themes of his work throughout his whole career to date?
Cloud computing, Computer network, Distributed computing, Artificial intelligence and Server are his primary areas of study.
His Cloud computing research is multidisciplinary, incorporating elements of Multimedia, Real-time computing, Data center, Mobile computing and Mobile device.
His studies in Data center integrate themes in fields like Efficient energy use and Reinforcement learning.
His work in Mobile device addresses issues such as Energy consumption, which are connected to fields such as Wireless.
Yonggang Wen has included themes like Network topology, Scheduling, Scalability and Network packet in his Distributed computing study.
His Artificial intelligence study incorporates themes from Machine learning and Metric.
He most often published in these fields:
- Cloud computing (31.42%)
- Computer network (30.41%)
- Distributed computing (21.28%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (20.27%)
- Cloud computing (31.42%)
- Reinforcement learning (6.42%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Artificial intelligence, Cloud computing, Reinforcement learning, Machine learning and Software deployment.
In the field of Artificial intelligence, his study on Deep learning, Artificial neural network and Training set overlaps with subjects such as Joint.
His work carried out in the field of Cloud computing brings together such families of science as Real-time computing, Computation and Data center.
His Reinforcement learning study combines topics from a wide range of disciplines, such as Thermal comfort, Thermal, Energy consumption, Markov decision process and Server.
His Energy consumption research includes themes of Distributed computing, Automotive engineering, Efficient energy use and Heuristics.
Yonggang Wen combines subjects such as Data modeling, Metric, Adversary, Handwriting and Benchmark with his study of Machine learning.
Between 2019 and 2021, his most popular works were:
- A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications (77 citations)
- Transforming Cooling Optimization for Green Data Center via Deep Reinforcement Learning (32 citations)
- DeepQoE: A Multimodal Learning Framework for Video Quality of Experience (QoE) Prediction (10 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Operating system
- Artificial intelligence
His scientific interests lie mostly in Reinforcement learning, Energy consumption, Artificial intelligence, Data center and Cloud computing.
Yonggang Wen has included themes like HVAC, Efficient energy use, Heuristics and Server in his Energy consumption study.
His Server research is multidisciplinary, relying on both Real-time computing and Mathematical optimization.
When carried out as part of a general Artificial intelligence research project, his work on Artificial neural network is frequently linked to work in Scale, therefore connecting diverse disciplines of study.
Yonggang Wen works mostly in the field of Data center, limiting it down to topics relating to Distributed computing and, in certain cases, Constrained optimization, Supercomputer and Cooling energy.
Yonggang Wen works in the field of Cloud computing, namely DevOps.
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