What is he best known for?
The fields of study he is best known for:
- Computer network
- Telecommunications
- Operating system
Computer network, Distributed computing, Network topology, Routing and Provisioning are his primary areas of study.
His study involves Defragmentation, OpenFlow, Blocking, Resource allocation and Bandwidth, a branch of Computer network.
His biological study spans a wide range of topics, including Dynamic network analysis, Heuristic, Integer programming and Backup.
His study focuses on the intersection of Network topology and fields such as Communication complexity with connections in the field of Public-key cryptography, Internet traffic and Scheduling.
His Routing study which covers Multiplexing that intersects with Fiber Bragg grating and Photonics.
He interconnects Cloud computing, The Internet, Dynamic priority scheduling and Bandwidth allocation in the investigation of issues within Provisioning.
His most cited work include:
- Dynamic Service Provisioning in Elastic Optical Networks With Hybrid Single-/Multi-Path Routing (291 citations)
- Virtual Optical Network Embedding (VONE) Over Elastic Optical Networks (201 citations)
- Highly efficient data migration and backup for big data applications in elastic optical inter-data-center networks (187 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Computer network, Distributed computing, Network topology, Provisioning and Electronic engineering.
Many of his studies on Computer network apply to Algorithm design as well.
His Distributed computing study combines topics from a wide range of disciplines, such as Testbed, Routing, Blocking and Integer programming.
In his research on the topic of Routing, Defragmentation is strongly related with Bandwidth.
His Network topology research incorporates elements of Network planning and design, Optical networking, Orchestration and Topology.
In general Electronic engineering study, his work on Optical switch often relates to the realm of Bit error rate, thereby connecting several areas of interest.
He most often published in these fields:
- Computer network (53.10%)
- Distributed computing (42.41%)
- Network topology (17.59%)
What were the highlights of his more recent work (between 2018-2021)?
- Distributed computing (42.41%)
- Computer network (53.10%)
- Artificial neural network (6.21%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Distributed computing, Computer network, Artificial neural network, Reinforcement learning and Virtual network.
His studies deal with areas such as Scalability, Control reconfiguration, Packet switching, Network topology and Orchestration as well as Distributed computing.
His study on Computer network is mostly dedicated to connecting different topics, such as Telemetry.
Zuqing Zhu studied Artificial neural network and Optical performance monitoring that intersect with End-to-end principle, False positive rate, Cluster analysis and Feature extraction.
His study in Reinforcement learning is interdisciplinary in nature, drawing from both Reduction and Blocking.
His Virtual network research focuses on Service and how it connects with Cloud computing.
Between 2018 and 2021, his most popular works were:
- DeepRMSA: A Deep Reinforcement Learning Framework for Routing, Modulation and Spectrum Assignment in Elastic Optical Networks (31 citations)
- Self-Taught Anomaly Detection With Hybrid Unsupervised/Supervised Machine Learning in Optical Networks (27 citations)
- Experimental demonstration of machine-learning-aided QoT estimation in multi-domain elastic optical networks with alien wavelengths (23 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Telecommunications
- Operating system
Zuqing Zhu focuses on Distributed computing, Artificial neural network, Reinforcement learning, Testbed and Network topology.
His study ties his expertise on Predictive analytics together with the subject of Distributed computing.
His Artificial neural network study combines topics in areas such as Optical performance monitoring, Routing and Provisioning.
His study looks at the relationship between Testbed and fields such as Orchestration, as well as how they intersect with chemical problems.
His work focuses on many connections between Quality of service and other disciplines, such as Nash equilibrium, that overlap with his field of interest in Computer network.
His work carried out in the field of Computer network brings together such families of science as Integer programming and Slicing.
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