What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Programming language
His primary areas of investigation include Control theory, Mobile robot, Control system, Trajectory and Topology.
His study in Control theory is interdisciplinary in nature, drawing from both Control engineering, Motion planning and Nonholonomic system.
Richard M. Murray combines subjects such as Control and Robot control with his study of Control engineering.
Within one scientific family, Richard M. Murray focuses on topics pertaining to State under Trajectory, and may sometimes address concerns connected to Stability.
His work in Topology covers topics such as Graph theory which are related to areas like Laplacian matrix, Distributed computing, Graph and Bounded function.
Richard M. Murray interconnects Telecommunications network, Network topology, Wireless sensor network and Multi-agent system in the investigation of issues within Distributed computing.
His most cited work include:
- Consensus problems in networks of agents with switching topology and time-delays (9263 citations)
- Consensus and Cooperation in Networked Multi-Agent Systems (7575 citations)
- A Mathematical Introduction to Robotic Manipulation (4965 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Control theory, Control engineering, Control theory, Mathematical optimization and Control system.
He works mostly in the field of Control theory, limiting it down to topics relating to Network packet and, in certain cases, Kalman filter.
Richard M. Murray has researched Control engineering in several fields, including Robustness and Mobile robot.
The subject of his Mobile robot research is within the realm of Robot.
His work carried out in the field of Control theory brings together such families of science as Control and Temporal logic.
As part of his studies on Control system, he often connects relevant areas like Hybrid system.
He most often published in these fields:
- Control theory (35.09%)
- Control engineering (14.84%)
- Control theory (12.62%)
What were the highlights of his more recent work (between 2015-2021)?
- Synthetic biology (8.18%)
- Control theory (12.62%)
- Biological system (4.85%)
In recent papers he was focusing on the following fields of study:
Richard M. Murray spends much of his time researching Synthetic biology, Control theory, Biological system, Control theory and Electronic circuit.
Richard M. Murray works mostly in the field of Synthetic biology, limiting it down to concerns involving Modular design and, occasionally, Python.
Control theory is a subfield of Control engineering that Richard M. Murray studies.
His Control engineering research includes themes of Stability and Control.
The study incorporates disciplines such as Quorum sensing, Signal and Bayesian probability in addition to Biological system.
While working on this project, Richard M. Murray studies both Control theory and Negative feedback.
Between 2015 and 2021, his most popular works were:
- End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks (121 citations)
- Systems & Control for the future of humanity, research agenda: Current and future roles, impact and grand challenges (95 citations)
- Biophysical Constraints Arising from Compositional Context in Synthetic Gene Networks. (66 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Statistics
Richard M. Murray mostly deals with Synthetic biology, Control theory, Control engineering, Temporal logic and Control.
His Synthetic biology study also includes
- Electronic circuit that intertwine with fields like Distributed computing,
- Modular design which intersects with area such as Detector, Topology, Feed forward and Chemical reaction,
- Organism, which have a strong connection to Dual, Feedback control, Regulation of gene expression, DNA sequencing and DNA.
His Dual study combines topics in areas such as Quorum sensing, Control theory and Robustness.
His work on Time delays as part of general Control theory study is frequently connected to Theoretical methods, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His study in the fields of Inverted pendulum under the domain of Control theory overlaps with other disciplines such as Gaussian process.
His Control engineering research is multidisciplinary, incorporating elements of Class, Stability, Robustness and Parametric statistics.
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