What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Algorithm
Hybrid system, Mathematical optimization, Control theory, Control system and Motion planning are his primary areas of study.
His studies in Hybrid system integrate themes in fields like Dynamical systems theory, Stability, Limit cycle, Finite-state machine and Lipschitz continuity.
His study in the field of Optimal control and Bellman equation is also linked to topics like Multipartite.
His work is connected to Lyapunov function and Lyapunov stability, as a part of Control theory.
Scheduling and Rate-monotonic scheduling is closely connected to Network packet in his research, which is encompassed under the umbrella topic of Control system.
His research investigates the link between Networked control system and topics such as Distributed computing that cross with problems in Dropout.
His most cited work include:
- Stability of networked control systems (3067 citations)
- Multiple Lyapunov functions and other analysis tools for switched and hybrid systems (2839 citations)
- Perspectives and results on the stability and stabilizability of hybrid systems (1425 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Hybrid system, Control engineering, Control theory, Control system and Mathematical optimization.
The Hybrid system study combines topics in areas such as Dynamical systems theory, Theoretical computer science, Lyapunov stability, Optimal control and Finite-state machine.
His Control engineering research includes themes of Hybrid automaton and Control.
Control theory is a component of his Control theory, Lyapunov function and Linear system studies.
His work carried out in the field of Control system brings together such families of science as Stability, Scheduling, Distributed computing and Network packet.
His biological study spans a wide range of topics, including Algorithm and Path, Motion planning.
He most often published in these fields:
- Hybrid system (32.67%)
- Control engineering (23.76%)
- Control theory (19.80%)
What were the highlights of his more recent work (between 2009-2021)?
- Artificial intelligence (16.83%)
- Cyber-physical system (5.94%)
- Mathematical optimization (18.81%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Cyber-physical system, Mathematical optimization, Control and Computer vision.
In general Artificial intelligence, his work in Reinforcement learning is often linked to Functional electrical stimulation, Attachment anxiety and Cognition linking many areas of study.
The study incorporates disciplines such as Path, Random tree and Robustness in addition to Mathematical optimization.
Michael S. Branicky combines subjects such as Automation, Rate of convergence, Maximum principle and Interpretation with his study of Control.
His work on Image as part of general Computer vision research is frequently linked to Lawn, Statistic, Binary number and Weighting, thereby connecting diverse disciplines of science.
His Control theory study deals with the bigger picture of Control theory.
Between 2009 and 2021, his most popular works were:
- Training an Actor-Critic Reinforcement Learning Controller for Arm Movement Using Human-Generated Rewards (26 citations)
- Visual segmentation of lawn grass (20 citations)
- A model of exploration and goal-searching in the cockroach, Blaberus discoidalis (14 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Algorithm
His primary scientific interests are in Artificial intelligence, Computer vision, Random search, Onboard camera and Mobile robot.
His Artificial intelligence study often links to related topics such as Overshoot.
His study on Image sensor is often connected to Optical radar, Obstacle and Controller as part of broader study in Computer vision.
The various areas that Michael S. Branicky examines in his Random search study include Real-time computing, Time control and Simulation.
His Onboard camera study incorporates themes from Algorithm, Randomized algorithm and Goal seeking.
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