What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- Machine learning
The scientist’s investigation covers issues in Artificial intelligence, Control engineering, Fuzzy logic, System of systems and Mobile robot.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning and Computer vision.
Mo Jamshidi is interested in Robust control, which is a branch of Control engineering.
As a part of the same scientific family, Mo Jamshidi mostly works in the field of Fuzzy logic, focusing on Intelligent control and, on occasion, Control theory and Soft computing.
His Mobile robot research entails a greater understanding of Robot.
His Robot research is multidisciplinary, relying on both Control system and Automatic control.
His most cited work include:
- Survey of robust control for rigid robots (343 citations)
- The paradoxical success of fuzzy logic (190 citations)
- Prediction of cloud data center networks loads using stochastic and neural models (113 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Control engineering, Fuzzy logic, Robot and Control theory.
The Artificial intelligence study combines topics in areas such as Machine learning, Computer vision and Pattern recognition.
The various areas that Mo Jamshidi examines in his Control engineering study include Control system, Control, Decentralised system, Simulation and Intelligent control.
His Robot study integrates concerns from other disciplines, such as Swarm behaviour and Real-time computing.
His Real-time computing research is multidisciplinary, incorporating elements of Cloud computing and Distributed computing.
His Mobile robot study combines topics from a wide range of disciplines, such as System of systems and Motion planning.
He most often published in these fields:
- Artificial intelligence (31.23%)
- Control engineering (23.01%)
- Fuzzy logic (20.82%)
What were the highlights of his more recent work (between 2013-2021)?
- Artificial intelligence (31.23%)
- Robot (18.90%)
- Cloud computing (7.95%)
In recent papers he was focusing on the following fields of study:
Mo Jamshidi mostly deals with Artificial intelligence, Robot, Cloud computing, Control engineering and Distributed computing.
His Artificial intelligence study combines topics in areas such as Machine learning and Computer vision.
Mobile robot is the focus of his Robot research.
His Control engineering research incorporates elements of Image processing, Quadcopter, Robot kinematics and Fuzzy logic.
His Fuzzy logic study frequently draws connections to adjacent fields such as Control theory.
His studies in Distributed computing integrate themes in fields like Control system, Virtualization, Software and Swarm robotics.
Between 2013 and 2021, his most popular works were:
- System of Systems and Big Data analytics - Bridging the gap (43 citations)
- Multisatellite Formation Control for Remote Sensing Applications Using Artificial Potential Field and Adaptive Fuzzy Sliding Mode Control (39 citations)
- A New Intelligent Neuro–Fuzzy Paradigm for Energy-Efficient Homes (36 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Machine learning
Mo Jamshidi focuses on Artificial intelligence, Cloud computing, Robot, Control engineering and Computer vision.
Mo Jamshidi has included themes like Machine learning and Data science in his Artificial intelligence study.
His work carried out in the field of Cloud computing brings together such families of science as Middleware, Scalability and Distributed computing, Software-defined networking.
His specific area of interest is Robot, where Mo Jamshidi studies Mobile robot.
His research integrates issues of Control system, Wind power, Image processing, Control and Fuzzy logic in his study of Control engineering.
The concepts of his Fuzzy logic study are interwoven with issues in Efficient energy use, Control theory, Robustness and Demand response.
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