重量級講者! 現代 5G/6G 無線通訊領域佼佼者來授課啦!
Don’t Miss: Talk by Prof. Trung Q. Duong (IEEE Fellow) on Quantum Machine Learning and 6G
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演講主題:Hybrid Quantum Machine Learning and Optimization for Next Generation Communications Technologies(混合式量子機器學習與最佳化：次世代通訊技術的關鍵)
講者:Trung Q. Duong (IEEE Fellow) Memorial University, Canada
活動時間: 2025/12/10下午 02:00~下午 04:00
活動地點: R70304演講廳
摘要:
量子運算運用量子力學的原理，在解決複雜計算問題上帶來革命性的突破。混合量子—經典機器學習演算法能顯著提升運算效率並實現指數級的速度增長，對於滿足6G網路高服務品質（QoS）需求具有極高潛力。本次演講將介紹量子機器學習與最佳化的最新研究進展，並全面探討其透過機器學習方法實現的潛能。此外，將說明量子啟發式機器學習與最佳化在6G網路中的應用，包含關鍵技術與面臨的挑戰。最後，演講也將闡述該領域主導的研究議題及未來研究方向。
Quantum computing uses the concept of quantum mechanics to offer a massive leap forward in relations to solving complex computation problems. Hybrid quantum-classical machine learning algorithms can significantly enhance the processing efficiency and exponentially computational speed-up, highly capable of guaranteeing high QoS requirements of 6G networks. This talk presents the state-of-the-art in quantum machine learning and optimization and provide a comprehensive overview of its potential, via machine learning approaches. Furthermore, this talk introduces quantum-inspired machine learning/optimization applications for 6G networks considering their enabling technologies and potential challenges. Finally, some dominating research issues and future research directions for the quantum-inspired machine learning/optimization in 6G networks are elaborated.
講者介紹: https://cerc-ngct.ca/
Trung Q. Duong 博士（IEEE Fellow, CAE Fellow, IET Fellow, EIC Fellow, AAIA Fellow）現任加拿大紀念大學 Canada Excellence Research Chair 及正教授，同時兼任英國貝爾法斯特女王大學（Queen’s University Belfast）客座教授。他的研究領域涵蓋量子最佳化與無線通訊中的機器學習。Duong 博士著作超過650篇論文，引用次數超過24,000次，h-index 為84。他曾擔任多份知名 IEEE 期刊編輯（包括 IEEE Trans. on Wireless Communications、IEEE Trans. on Communications、IEEE Trans. on Vehicular Technology、IEEE Communications Surveys & Tutorials 等），並多次獲得IEEE國際會議最佳論文獎（如ICC 2014、GLOBECOM 2016、2019、2022）。
他曾榮獲英國皇家工程院研究獎與講座職位（Research Fellowship & Research Chair），並於2017年獲英國政府頒發 Newton Prize。目前擔任 IEEE Communications Surveys & Tutorials 主編（IF = 46.7），以及 IEEE 通訊學會傑出講者（Distinguished Lecturer），同時為 Quantum Communications and Computing Center (QC3) 的創辦主任。
Dr. Trung Q. Duong (IEEE Fellow, CAE Fellow, IET Fellow, EIC Fellow, and AAIA Fellow) is a Canada Excellence Research Chair and Full Professor at Memorial University of Newfoundland, Canada. He is also an adjunct professor at Queen’s University Belfast, UK. His current research interests include quantum optimisation and machine learning in wireless communications. He is an author/co-author of 650+ publications with 24,000+ citations and h-index 84. He has served as an Editor for many reputable IEEE journals (IEEE Trans on Wireless Communications, IEEE Trans on Communications, IEEE Trans on Vehicular Technology, IEEE Communications Surveys & Tutorials, IEEE Communications Letters, and IEEE Wireless Communications Letters, IEEE Networks Magazine, IEEE Transactions on Network Science and Engineering and has been awarded best paper awards in many flagship conferences including IEEE ICC 2014, IEEE GLOBECOM 2016, 2019, and 2022. He was awarded the Research Fellowship and Research Chair of the Royal Academy of Engineering. In 2017, he was awarded the Newton Prize from the UK government. He is a Fellow of IEEE, IET, CAE, EIC, and AAIA. He is currently the Editor-in-Chief of IEEE Communications Surveys and Tutorials (IF = 46.7) and an IEEE ComSoc Distinguished Lecturer. He is the Founding Director of Quantum Communications and Computing Center (QC3).
