What is he best known for?
The fields of study he is best known for:
- Computer network
- The Internet
- Statistics
The scientist’s investigation covers issues in Computer security, Information privacy, Distributed computing, Wireless sensor network and Algorithm.
Computer security is frequently linked to Crowdsourcing in his study.
His Information privacy research includes elements of Information sensitivity, Private information retrieval, Cyber-physical system and Big data.
His Distributed computing research is multidisciplinary, incorporating elements of Scheduling, Computer network and Dynamic priority scheduling.
His Wireless sensor network study incorporates themes from Energy consumption, Time complexity, Sampling, Key distribution in wireless sensor networks and Real-time computing.
His Algorithm research incorporates elements of Missing value imputation, Iterated function and Data mining.
His most cited work include:
- Collective Data-Sanitization for Preventing Sensitive Information Inference Attacks in Social Networks (218 citations)
- A stable gene selection in microarray data analysis. (148 citations)
- Cost-Efficient Strategies for Restraining Rumor Spreading in Mobile Social Networks (139 citations)
What are the main themes of his work throughout his whole career to date?
Zhipeng Cai mainly focuses on Computer network, Distributed computing, Wireless sensor network, Computer security and Scheduling.
His work deals with themes such as Cognitive radio and Wireless network, which intersect with Computer network.
The Distributed computing study combines topics in areas such as Bandwidth, Dynamic priority scheduling, Data transmission and Fair-share scheduling.
His biological study spans a wide range of topics, including Energy consumption, Algorithm, Approximation algorithm, Key distribution in wireless sensor networks and Distributed algorithm.
While the research belongs to areas of Computer security, Zhipeng Cai spends his time largely on the problem of Social network, intersecting his research to questions surrounding Mathematical optimization and Node.
The Job shop scheduling research Zhipeng Cai does as part of his general Scheduling study is frequently linked to other disciplines of science, such as Schedule, therefore creating a link between diverse domains of science.
He most often published in these fields:
- Computer network (24.91%)
- Distributed computing (18.43%)
- Wireless sensor network (18.77%)
What were the highlights of his more recent work (between 2019-2021)?
- Theoretical computer science (5.80%)
- Distributed computing (18.43%)
- Computer security (12.29%)
In recent papers he was focusing on the following fields of study:
His main research concerns Theoretical computer science, Distributed computing, Computer security, Enhanced Data Rates for GSM Evolution and Scheduling.
His work in the fields of Distributed computing, such as Load balancing, intersects with other areas such as Crowdsensing.
Zhipeng Cai has included themes like Recommender system, Focus, Data collection and Social network in his Computer security study.
His Enhanced Data Rates for GSM Evolution research includes themes of Algorithm, Data processing and Data transmission.
His biological study spans a wide range of topics, including Wireless network, Real-time computing and Mobile edge computing.
Zhipeng Cai combines subjects such as Data aggregator, Wireless sensor network and Computer network with his study of Wireless network.
Between 2019 and 2021, his most popular works were:
- A Private and Efficient Mechanism for Data Uploading in Smart Cyber-Physical Systems (120 citations)
- Stochastic Load Balancing for Virtual Resource Management in Datacenters (68 citations)
- Privacy-Preserved Data Sharing Towards Multiple Parties in Industrial IoTs (51 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- The Internet
- Statistics
His scientific interests lie mostly in Information privacy, Data science, Distributed computing, Crowdsensing and Crowdsourcing.
His Information privacy study incorporates themes from Quality of service, Algorithm design, Information sensitivity and Information retrieval.
His Data science research is multidisciplinary, incorporating perspectives in Federated learning, Server, Usability and Reinforcement learning.
His research in Distributed computing intersects with topics in Exploit and Common value auction.
His Crowdsensing investigation overlaps with other disciplines such as Baseline, Sensitivity, Path, Set and Nash equilibrium.
Zhipeng Cai has researched Crowdsourcing in several fields, including Blockchain and Smart contract.
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