Chenye WU

Assistant Professor
School of Science and Engineering
The Chinese University of Hong Kong, Shenzhen








TC 404A, 2001 Longxiang Blvd
Shenzhen, Guangdong 518172

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Chenye Wu

I am actively recruiting students, postdocs, and visiting scholars! If you are interested, please do not hesitate to contact me via email for further information.

As an Assistant Professor and the Presidential Young Fellow at the School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, I am committed to advancing the field of power systems, and I am leading the ENLIGHT (ENergy analyticaL insIGHTs) Lab at CUHK-Shenzhen. ENLIGHT symbolizes insights inspiring innovation in energy. I completed my bachelor's degree in Electronic Engineering at Tsinghua University in 2009 and subsequently obtained my Ph.D. degree in Computer Science and Engineering from Tsinghua University in 2013, under the esteemed guidance of Prof. Andrew Yao, a Turing Award Laureate.

My research has resulted in over 100 publications in leading journals and conferences, such as IEEE Transactions on Power Systems, IEEE Transactions on Smart Grid, and IEEE Transactions on Sustainable Energy. Since February 2022, I have been contributing to IEEE Systems Journal as an Editorial Board Member. I have also served as the Symposium Co-Chair for IEEE SmartGridComm 2022, the Digital Conference Co-Chair for ACM e-Energy 2022, the Symposium Co-Chair for IEEE SmartGridComm 2023, and the Publicity co-Chair for ACM e-Energy 2024. My work has been recognized with three best paper awards, including those from IEEE SmartGridComm 2012, IEEE PES General Meeting 2013, and IEEE PES General Meeting 2020.

My research focuses on pioneering a new paradigm for power grid operation, driven by data and innovative computer science approaches. I aim to capture the essence of power systems and derive theoretical guarantees for the performance of proposed methods, whether in terms of cost-effectiveness, robustness, or efficiency.

I challenge conventional wisdom in power system operations, revisiting fundamental questions to uncover misinterpretations and myths that may hinder optimal performance. Here are a few examples of commonly-held beliefs that my research challenges: