What is he best known for?
The fields of study he is best known for:
- Computer network
- The Internet
- Artificial intelligence
Wireless sensor network, Computer network, Approximation algorithm, Efficient energy use and Scheduling are his primary areas of study.
His Wireless sensor network study combines topics in areas such as Distributed algorithm, Distributed computing, Algorithm, Algorithm design and Energy.
In general Computer network study, his work on Multicast and Blocking often relates to the realm of Cost efficiency, Rumor and Electronic mail, thereby connecting several areas of interest.
His Approximation algorithm research is multidisciplinary, relying on both Linear programming, Network model and Discrete mathematics.
As part of the same scientific family, Yingshu Li usually focuses on Scheduling, concentrating on Brooks–Iyengar algorithm and intersecting with Job shop scheduling.
Yingshu Li studied Real-time computing and Visual sensor network that intersect with Sensor node.
His most cited work include:
- Energy-efficient target coverage in wireless sensor networks (877 citations)
- Distributed Data Aggregation Scheduling in Wireless Sensor Networks (234 citations)
- Collective Data-Sanitization for Preventing Sensitive Information Inference Attacks in Social Networks (218 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Wireless sensor network, Computer network, Distributed computing, Wireless network and Key distribution in wireless sensor networks.
The various areas that Yingshu Li examines in his Wireless sensor network study include Distributed algorithm, Scheduling, Real-time computing and Approximation algorithm.
His work in Approximation algorithm addresses subjects such as Discrete mathematics, which are connected to disciplines such as Combinatorics.
His Computer network study combines topics from a wide range of disciplines, such as Wireless and Wireless ad hoc network.
Yingshu Li combines subjects such as Data aggregator, Connected dominating set and Network model with his study of Distributed computing.
Yingshu Li interconnects Network topology, Mobile computing and Graph in the investigation of issues within Wireless network.
He most often published in these fields:
- Wireless sensor network (42.99%)
- Computer network (31.22%)
- Distributed computing (22.62%)
What were the highlights of his more recent work (between 2016-2021)?
- Computer security (9.05%)
- Crowdsourcing (9.50%)
- Mobile device (8.14%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Computer security, Crowdsourcing, Mobile device, Wireless sensor network and Social network.
Probabilistic logic, Location-based service and k-anonymity is closely connected to Server in his research, which is encompassed under the umbrella topic of Computer security.
His Wireless sensor network study incorporates themes from Distributed algorithm, Distributed computing, Scheduling and Approximation algorithm.
The study incorporates disciplines such as Key distribution in wireless sensor networks, Algorithm design and Connected dominating set in addition to Distributed computing.
Computer network covers he research in Scheduling.
His Social network research incorporates themes from Machine learning, Empirical research, Maximization and Artificial intelligence.
Between 2016 and 2021, his most popular works were:
- Collective Data-Sanitization for Preventing Sensitive Information Inference Attacks in Social Networks (218 citations)
- Cost-Efficient Strategies for Restraining Rumor Spreading in Mobile Social Networks (139 citations)
- Deep Learning Based Inference of Private Information Using Embedded Sensors in Smart Devices (112 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- The Internet
- Artificial intelligence
His primary areas of study are Crowdsourcing, Computer security, Mobile device, Social network and Information privacy.
His Computer security research includes themes of Blocking, Differential privacy and Mobile computing.
His Mobile device study integrates concerns from other disciplines, such as Hidden Markov model, Artificial intelligence and Bounded function.
He has researched Information privacy in several fields, including Information sensitivity, Inference attack and User profile.
His study looks at the intersection of Approximation algorithm and topics like Theoretical computer science with Wireless sensor network.
His Wireless sensor network study improves the overall literature in Computer network.
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