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AI-Powered Time Series Analytics:Unlocking Predictive Intelligence for Industry AI驅動的時間序列分析:為工業解鎖預測智能

時間:2025-04-17 16:51    來源:     閱讀:

光華講壇——社會名流與企業家論壇第6736期

主題:AI-Powered Time Series Analytics:Unlocking Predictive Intelligence for Industry AI驅動的時間序列分析:為工業解鎖預測智能

主講人:新加坡科學技術研究所(A*STAR)信息與通信研究所部門負責人兼高級首席科學家 李曉黎教授

主持人:計算機與人工智能學院副院長 楊新教授

時間4月23日10:00-11:00

地點柳林校區通博樓B514

主辦單位計算機與人工智能學院 科研處

主講人簡介:

Xiaoli is currently the Department Head and Senior Principal Scientist at the Institute for Infocomm Research, A*STAR, Singapore. He also serves as an adjunct full professor at the School of Computer Science and Engineering, Nanyang Technological University, Singapore. With a diverse range of research interests, Xiaoli focuses on cutting-edge areas such as AI, data mining, machine learning, and bioinformatics. His contributions to these fields are evident through his extensive publication record, boasting over 370 peer-reviewed papers, and the recognition he has received, including over ten best paper awards. He has been serving as Editor-in-chief of the Annual Review of Artificial Intelligence and an Associate Editor for prestigious journals like IEEE Transactions on Artificial Intelligence and Knowledge and Information Systems, as well as conference chairs and area chairs of leading AI, machine learning, and data science conferences, such as AAAI, IJCAI, ICLR, NeurIPS, KDD, ICDM etc. Beyond academia, Xiaoli possesses extensive industry experience, where he has successfully spearheaded over 10 R&D projects in collaboration with major industry players across diverse sectors, such as aerospace, telecom, insurance, and professional service companies. Xiaoli is an IEEE Fellow and Fellow of Asia-Pacific Artificial Intelligence Association (AAIA). He has been recognized as one of the world's top 2% scientists in the AI domain by Stanford University, and Clarivate's Highly Cited Researcher.

李曉黎目前是新加坡科學技術研究所(A*STAR)信息與通信研究所的部門負責人兼高級首席科學家。他還在新加坡南洋理工大學計算機科學與工程學院擔任兼職正教授。他擁有多樣化的研究興趣,專注于人工智能、數據挖掘、機器學習和生物信息學等前沿領域。他在這些領域的貢獻通過其豐富的出版記錄得以體現,他發表了超過370篇經過同行評審的論文,并獲得了包括十多項最佳論文獎在內的諸多認可。他目前擔任《人工智能年度評論》的主編,以及《IEEE人工智能匯刊》和《知識與信息系統》等知名期刊的副主編,同時還擔任AAAI、IJCAI、ICLR、NeurIPS、KDD、ICDM等頂尖人工智能、機器學習和數據科學會議的會議主席和領域主席。除了學術領域,李曉黎還擁有豐富的行業經驗,他成功領導了10多個與航空航天、電信、保險和專業服務公司等不同行業主要參與者合作的研發項目。李曉黎是電氣與電子工程師協會(IEEE)會士和亞太人工智能協會(AAIA)會士。他被斯坦福大學評為全球人工智能領域排名前2%的科學家,并且是Clarivate高被引學者。

內容提要:

The explosion of sensor data across industries—ranging from manufacturing and aerospace to transportation and education—has unlocked immense potential for AI-driven time series analytics. This talk explores how cutting-edge AI techniques are transforming real-world applications, enabling predictive maintenance, optimizing decision-making, and enhancing learning experiences.

隨著傳感器數據在各行業的爆炸性增長——從制造業、航空航天到交通運輸和教育——為人工智能驅動的時間序列分析解鎖了巨大的潛力。本次演講探討了尖端人工智能技術如何變革現實世界的各類應用,助力實現預測性維護、優化決策制定以及提升學習體驗。

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