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O. Hugo Schuck Award

The Hugo Schuck Award is given to recognize the best two papers presented at the previous ACC. One award is for a paper emphasizing contributions to theory and the other emphasizing significant or innovative applications. The papers must have been presented by the awardee or a coauthor. Criteria for selection include the quality of the written and oral presentation, the technical contribution, timeliness, and practicality.

2021 ACC Paper (Theory): Accuracy Prevents Robustness in Perception-based Control

Year: 
2021
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Paper: 

Abed AlRahman Al Makdah is a Ph.D. candidate in the Department of Electrical and Computer Engineering at the University of California, Riverside. He received his B.Eng. and M.Eng. in Mechanical Engineering from the American University of Beirut in 2014 and 2016, respectively. His research interests include analysis and control of dynamical systems, machine learning, and data driven control.

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Chao Ning and Fengqi You

Year: 
2020
Citation: 
Paper: 
2019 ACC Paper (Application): Data-Driven Adaptive Robust Optimization Framework for Unit Commitment under Renewable Energy Generation Uncertainty
Chao Ning received the B.Eng. degree in Automation from University of Electronic Science and Technology of China in 2012, and M.S. degree in Control Science and Engineering from Tsinghua University, China, in 2015. He is currently working toward the Ph.D. degree at Cornell University, USA. His research interests include data-driven optimization under uncertainty, learning for dynamics and control, big data analytics and machine learning, power systems operations, and renewable energy systems.
 
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