Harmonic Estimation and Forecasting in Sparsely Monitored Uncertain Power Systems: Probabilistic and Machine Learning Approaches
暫譯: 稀疏監測不確定電力系統中的諧波估計與預測：機率與機器學習方法

Dr. Yuqi Zhao holds B.Eng., M.Sc., and Ph.D. degrees in power system engineering from the University of Manchester, UK, where she was supervised by Prof. Jovica V. Milanovic. She is an active member of the IEEE PES, IET, and CIGRE and has undertaken a visiting research position at Universidad Politécnica de Madrid. In recognition of her academic excellence, Dr. Zhao received the Best Student Paper Award at the IET APSCOM 2018 conference. She has also gained professional experience as a power system engineer with both National Grid of UK and the State Grid Corporation of China. Dr. Zhao's research contributions include multiple peer-reviewed publications in top-tier IEEE transactions journals and presentations at prestigious international conferences, such as the IEEE General Meeting, IEEE PowerTech, IEEE ICHQP, IEEE PMAPS, and CIRED. She has played an active role in multiple EU Horizon 2020 projects, including MIGRATE and CROSSBOW.

余琦博士擁有英國曼徹斯特大學的電力系統工程學士、碩士及博士學位，並在喬維卡·米蘭諾維奇教授的指導下完成學業。她是IEEE PES、IET及CIGRE的活躍成員，並曾在馬德里理工大學擔任訪問研究職位。因其學術卓越，余博士於2018年IET APSCOM會議上獲得最佳學生論文獎。她還在英國國家電網和中國國家電網公司擔任電力系統工程師，積累了專業經驗。余博士的研究貢獻包括在頂尖的IEEE期刊上發表多篇同行評審的論文，並在多個國際知名會議上進行報告，如IEEE年會、IEEE PowerTech、IEEE ICHQP、IEEE PMAPS及CIRED。她在多個歐盟Horizon 2020項目中積極參與，包括MIGRATE和CROSSBOW。