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Assembly Series

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McKelvey School of Engineering

Brown School

ESE Seminar: Zhong-Ping Jiang, PhD

Friday, April 30, 2021 | 10:00 AM - 11:00 AM

This talk presents a new design paradigm, called “learning-based control”, that is fundamentally different from traditional model-based control and model-free machine learning. Learning-based control is aimed at learning real-time optimal controllers directly from input-output data, for stability and robustness of dynamical systems in uncertain environments. Novel tools and methods for data-driven control are proposed as an entanglement of techniques from reinforcement learning and control theory. The effectiveness of learning-based control design is demonstrated via its applications to network systems such as connected and autonomous vehicles and neural science problems such as computational principles of human movement.


Event Type



McKelvey School of Engineering


Science & Technology

Electrical & Systems Engineering
Speaker Information

Zhong-Ping Jiang, PhD
Electrical and Computer Engineering
New York University

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