1999 - Fellow of the American Association for the Advancement of Science (AAAS)
1994 - Fellow, The World Academy of Sciences
1989 - IEEE Fellow For contributions to the theory and applications of large-scale systems and control system education.
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 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.
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.
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.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Survey of robust control for rigid robots
C. Abdallah;D.M. Dawson;P. Dorato;M. Jamshidi.
IEEE Control Systems Magazine (1991)
The paradoxical success of fuzzy logic
C. Elkan;H.R. Berenji;B. Chandrasekaran;C.J.S. de Silva.
IEEE Intelligent Systems (1994)
Prediction of cloud data center networks loads using stochastic and neural models
John J. Prevost;KranthiManoj Nagothu;Brian Kelley;Mo Jamshidi.
international conference on system of systems engineering (2011)
System of systems engineering - New challenges for the 21st century
M. Jamshidi.
IEEE Aerospace and Electronic Systems Magazine (2008)
Mobile robot navigation and target tracking system
Patrick Benavidez;Mo Jamshidi.
international conference on system of systems engineering (2011)
Robust Control Systems with Genetic Algorithms
Mo Jamshidi;Renato A. Krohling;Leandro dos S. Coelho;Peter J. Fleming.
(2002)
A Modified Probabilistic Neural Network for Partial Volume Segmentation in Brain MR Image
Tao Song;M.M. Jamshidi;R.R. Lee;Mingxiong Huang.
IEEE Transactions on Neural Networks (2007)
Soft computing for autonomous robotic systems
M.-R. Akbarzadeh-T;K. Kumbla;E. Tunstel;M. Jamshidi.
Computers & Electrical Engineering (2000)
Introduction to System of Systems
Mo Jamshidi.
(2008)
Guaranteed-cost design of continuous-time Takagi-Sugeno fuzzy controllers via linear matrix inequalities
A. Jadbabaie;M. Jamshidi;A. Titli.
ieee international conference on fuzzy systems (1998)
Profile was last updated on December 6th, 2021.
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