What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Algorithm
His primary areas of study are Distributed computing, Identification, Cyber-physical system, Electric power system and Network topology.
The concepts of his Distributed computing study are interwoven with issues in Control system, Node, Autonomous agent and Intrusion detection system.
His studies in Control system integrate themes in fields like Attentional control, Secure state, Cognitive science and Biological neural network.
His research in Identification focuses on subjects like Computer security, which are connected to Resilient control systems and Data management.
The study incorporates disciplines such as Kalman filter, Moving horizon estimation, Linear-quadratic-Gaussian control and Metric in addition to Cyber-physical system.
His biological study spans a wide range of topics, including Human Connectome, Connectome and Human brain.
His most cited work include:
- Attack Detection and Identification in Cyber-Physical Systems (1037 citations)
- Controllability Metrics, Limitations and Algorithms for Complex Networks (420 citations)
- Controllability of structural brain networks. (415 citations)
What are the main themes of his work throughout his whole career to date?
Fabio Pasqualetti mostly deals with Distributed computing, Controllability, Topology, Control theory and Network topology.
His Distributed computing research integrates issues from Cyber-physical system and Identification.
His Computer security research extends to the thematically linked field of Cyber-physical system.
His Controllability research includes elements of Mathematical optimization, Metric and Complex network.
Computation is closely connected to Theoretical computer science in his research, which is encompassed under the umbrella topic of Network topology.
His Linear system research incorporates elements of Data-driven, Observability and Leverage.
He most often published in these fields:
- Distributed computing (19.49%)
- Controllability (19.49%)
- Topology (13.85%)
What were the highlights of his more recent work (between 2019-2021)?
- Controllability (19.49%)
- Distributed computing (19.49%)
- Topology (13.85%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Controllability, Distributed computing, Topology, Leverage and Complex network.
His Controllability study necessitates a more in-depth grasp of Control theory.
His Distributed computing research integrates issues from Dynamical systems theory, State, Detection performance, Privacy Level and Cyber-physical system.
He works mostly in the field of Leverage, limiting it down to topics relating to Linear system and, in certain cases, Algorithm, Identifiability, Attack strategy, System dynamics and Optimal control.
His Metric study deals with Control intersecting with Trajectory, Focus, Distributed algorithm and Control system.
The study incorporates disciplines such as Rate of convergence, Dimensional modeling and Identification in addition to Mathematical optimization.
Between 2019 and 2021, his most popular works were:
- Stability Conditions for Cluster Synchronization in Networks of Heterogeneous Kuramoto Oscillators (33 citations)
- Benchmarking Measures of Network Controllability on Canonical Graph Models (28 citations)
- A practical guide to methodological considerations in the controllability of structural brain networks. (21 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Computer network
Fabio Pasqualetti spends much of his time researching Control, Controllability, Control, Trajectory and Structure.
His work on Control theory as part of general Control research is often related to Function and Energy, thus linking different fields of science.
The various areas that he examines in his Controllability study include Biological system and Human brain.
His work is dedicated to discovering how Trajectory, Robot are connected with Real-time computing, Resilience, Spoofing attack and Control theory and other disciplines.
His studies deal with areas such as Models of communication, Bridge, Convergence, Cognitive science and Computational model as well as Structure.
His study in Metric is interdisciplinary in nature, drawing from both Optimization problem, Mathematical optimization, Computation and Gramian matrix.
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