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Junyi Tao

Ministry of Education of the People's Republic of China · CN
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Area of research
Electrical and Electronic Engineering
Research interest
Research topics from publications: Decision-Focused Learning for Power System Decision-Making Under Uncertainty. Representative work: More accurate forecasts may not necessarily lead to better decision-making. To address this challenge, decision-focused learning (DFL) has been proposed as a new branch of machine learning that replaces traditional statistical loss with a decision loss to form an end-to-end paradigm. Applications of DFL in power systems have been developed in recent years. However, existing applications remain fragmented without systematic analysis of methodologies or comparative benchmarks. This review addresses this gap by performing a set of scenario analysis, taxonomy analysis, application analysis and comparative analysis. It first illustrates the inherent mismatch between statistical accuracy and opera
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Recent publications

Decision-Focused Learning for Power System Decision-Making Under Uncertainty
IEEE Transactions on Power Systems 2025cited by 7position: middledoi

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Frequent collaborators

Can Wan · Guangzhou University of Chinese Medicine1 papers (2025–2025)Qintao Du · Ministry of Education of the People's Republic of China1 papers (2025–2025) · 1 papers (2025–2025)Haipeng Zhang · Ministry of Education of the People's Republic of China1 papers (2025–2025)Fei Teng · Jiangsu University1 papers (2025–2025) · 1 papers (2025–2025)Mingyang Sun · Zhejiang University1 papers (2025–2025) · 1 papers (2025–2025) · 1 papers (2025–2025)Ran Li · Ministry of Education of the People's Republic of China1 papers (2025–2025)
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