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1229434138新虫 (初入文坛)
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PhD position at Telecom Sud Paris - Institut Polytechnique de Paris
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professor afifi and moungla propose a new phd position at telecom sud paris - institut polytechnique de paris. thesis title: machine learning enablers for autonomous vehicles ph.d directors: h.afifi, h.moungla abstract autonomous vehicles require a large set of control and guidance information. keeping the vehicle cost low and its performance and safety as high as possible requires to introduce machine learning in many stages of the vehicle operation and journey. edge cloud is a virtual technology that can be used for such a purpose. yet, it requires to be adapted to the vehicle constraints such as realtime decision making, agregation and data fusion of different information sources. manage particular elements of autonomous vehicles to improve their performance. examples of such collaborative decision making can be traffic fluidification. autonomy management. safety and hasard improvment. remote control of driving in emergency situations. training and transfer learning of new driving algorithms. this ph.d. will study the introduction of edge computing and virtualization in autonomous vehicle driving, including drones. the thesis covers theoretical aspects such as optimization techniques and applied aspects such as using neural networks for training , reinforcement and classification and finally it have applications on cloud plateforms. email: hassine.moungla@u-paris.fr, hossam.afifi@telecom-sudparis.eu deadline application : 18/04/2021 Professor Afifi and Moungla propose a new PhD at Telecom Sud Paris - Institut Polytechnique de Paris. Thesis title: Machine Learning Enablers for Autonomous Vehicles Ph.D directors: H.Afifi, H. Moungla Abstract Autonomous vehicles require a large set of control and guidance information. Keeping the vehicle cost low and its performance and safety as high as possible requires to introduce machine learning in many stages of the vehicle operation and journey. Edge cloud is a virtual technology that can be used for such a purpose. Yet, it requires to be adapted to the vehicle constraints such as realtime decision making, agregation and data fusion of different information sources. Manage particular elements of autonomous vehicles to improve their performance. Examples of such collaborative decision making can be traffic fluidification. Autonomy management. Safety and hasard improvment. Remote control of driving in emergency situations. Training and transfer learning of new driving algorithms. This Ph.D. will study the introduction of edge computing and virtualization in autonomous vehicle driving, including drones. The thesis covers the theoretical aspects such as optimization techniques and applied aspects such as using neural networks for training, reinforcement and classification and finally it have applications on cloud plateforms. Deadline application : 11/2021 Contact email: hassine.moungla@u-paris.fr, hossam.afifi@telecom-sudparis.eu |
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2楼2021-04-17 08:59:38
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