What is he best known for?
The fields of study he is best known for:
- Statistics
- Computer network
- Artificial intelligence
Estimator, Mathematical optimization, Kalman filter, Covariance and Scheduling are his primary areas of study.
His Estimator study integrates concerns from other disciplines, such as Upper and lower bounds, Real-time computing, State and Control theory.
His Mathematical optimization study incorporates themes from Covariance matrix and Markov process.
Ling Shi has included themes like Algorithm and Network packet in his Kalman filter study.
His studies examine the connections between Covariance and genetics, as well as such issues in Estimation theory, with regards to Job shop scheduling and Analysis of covariance.
His work on Rate-monotonic scheduling, Dynamic priority scheduling and Fair-share scheduling is typically connected to Denial-of-service attack as part of general Scheduling study, connecting several disciplines of science.
His most cited work include:
- Optimal DoS Attack Scheduling in Wireless Networked Control System (320 citations)
- Event-Based Sensor Data Scheduling: Trade-Off Between Communication Rate and Estimation Quality (317 citations)
- Optimal Denial-of-Service Attack Scheduling With Energy Constraint (267 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Estimator, Mathematical optimization, Control theory, Kalman filter and Scheduling.
His study in Estimator is interdisciplinary in nature, drawing from both Covariance, Real-time computing, State and Network packet.
The various areas that he examines in his Mathematical optimization study include Markov decision process, Markov process, Communication channel and Dynamic priority scheduling.
Ling Shi interconnects Upper and lower bounds and Bounded function in the investigation of issues within Control theory.
Ling Shi combines subjects such as Algorithm, Covariance matrix and Sensor fusion with his study of Kalman filter.
His studies in Scheduling integrate themes in fields like Minimum mean square error and Energy constraint.
He most often published in these fields:
- Estimator (35.86%)
- Mathematical optimization (29.66%)
- Control theory (25.86%)
What were the highlights of his more recent work (between 2019-2021)?
- Estimator (35.86%)
- Mathematical optimization (29.66%)
- Control theory (25.86%)
In recent papers he was focusing on the following fields of study:
Ling Shi focuses on Estimator, Mathematical optimization, Control theory, State and Scheduling.
His Estimator research incorporates themes from Wireless sensor network, Data transmission and Covariance.
His Mathematical optimization study combines topics in areas such as Markov decision process and Communication channel.
When carried out as part of a general Control theory research project, his work on PID controller is frequently linked to work in Stiffness, therefore connecting diverse disciplines of study.
The Job shop scheduling research Ling Shi 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.
His work focuses on many connections between Network packet and other disciplines, such as Kalman filter, that overlap with his field of interest in State.
Between 2019 and 2021, his most popular works were:
- Deep reinforcement learning for wireless sensor scheduling in cyber-physical systems (25 citations)
- Distributed Kalman Filters With State Equality Constraints: Time-Based and Event-Triggered Communications (21 citations)
- Learning Optimal Scheduling Policy for Remote State Estimation Under Uncertain Channel Condition (9 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Computer network
Ling Shi mostly deals with Estimator, Mathematical optimization, Kalman filter, Network packet and Scheduling.
His Estimator research includes themes of Wireless sensor network, Computer network, Markov decision process and Observability.
His Wireless sensor network study which covers Linear system that intersects with Covariance.
The concepts of his Mathematical optimization study are interwoven with issues in Communication channel and Monotonic function.
His Kalman filter research includes elements of Probability distribution, State variable and Algorithm.
His Job shop scheduling study in the realm of Scheduling interacts with subjects such as Schedule, Invariant and Global Positioning System.
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