What is he best known for?
The fields of study he is best known for:
- Operating system
- Programming language
- Central processing unit
His primary areas of investigation include Operating system, Parallel computing, Multi-core processor, Embedded system and Hypervisor.
His is involved in several facets of Operating system study, as is seen by his studies on Transactions per second, Cloud computing, Dynamic software updating and Web server.
His Parallel computing research incorporates elements of Vertex and Computation.
His work carried out in the field of Multi-core processor brings together such families of science as Multiprocessing, Scheduling, Data structure and Concurrency.
The concepts of his Embedded system study are interwoven with issues in Uniprocessor system and Source lines of code.
His Hypervisor study is focused on Virtualization in general.
His most cited work include:
- CloudVisor: retrofitting protection of virtual machines in multi-tenant cloud with nested virtualization (324 citations)
- Corey: an operating system for many cores (273 citations)
- PowerLyra: differentiated graph computation and partitioning on skewed graphs (226 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Operating system, Parallel computing, Distributed computing, Scalability and Embedded system.
His studies in Hypervisor, Virtual machine, Virtualization, Cloud computing and Software are all subfields of Operating system research.
His Cloud computing research is multidisciplinary, incorporating perspectives in Computer security and Computer network.
His research integrates issues of Java and Data structure in his study of Parallel computing.
His work in Distributed computing covers topics such as Online transaction processing which are related to areas like Remote direct memory access.
His Scalability research includes themes of Lock, Latency, Transactional memory, Record locking and Node.
He most often published in these fields:
- Operating system (40.00%)
- Parallel computing (23.13%)
- Distributed computing (19.38%)
What were the highlights of his more recent work (between 2017-2021)?
- Operating system (40.00%)
- Parallel computing (23.13%)
- Overhead (13.75%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Operating system, Parallel computing, Overhead, Scalability and Cloud computing.
His research in the fields of Hypervisor, Virtualization, Cache and Java overlaps with other disciplines such as Page table.
The Parallel computing study combines topics in areas such as Remote direct memory access, Latency, Data structure and Computation.
Haibo Chen has researched Scalability in several fields, including Transactional memory, Workload, Computer architecture and Concurrency control.
As a member of one scientific family, Haibo Chen mostly works in the field of Computer architecture, focusing on Speedup and, on occasion, Multi-core processor.
Haibo Chen has included themes like Virtual machine, Web server, Hardware software and Distributed computing in his Cloud computing study.
Between 2017 and 2021, his most popular works were:
- ShadowEth: Private Smart Contract on Public Blockchain (42 citations)
- PowerLyra: Differentiated Graph Computation and Partitioning on Skewed Graphs (32 citations)
- Deconstructing RDMA-enabled distributed transactions: hybrid is better (28 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Programming language
- Central processing unit
His main research concerns Operating system, Overhead, Parallel computing, Virtualization and Hypervisor.
His work on Operating system is being expanded to include thematically relevant topics such as Programming paradigm.
His Overhead research is multidisciplinary, relying on both CPU cache, Cache, Cache coherence, Side channel attack and Transactional Synchronization Extensions.
His study in Parallel computing is interdisciplinary in nature, drawing from both Remote direct memory access, Graph partition, Graph computation, Asynchronous communication and Heuristics.
His Virtualization study integrates concerns from other disciplines, such as Isolation, Attack surface, Host and Porting.
His Hypervisor study combines topics in areas such as Initialization, x86, Sandbox and Booting.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
