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PRODID:-//Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系 - ECPv6.15.20//NONSGML v1.0//EN
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X-WR-CALDESC:Events for Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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DTSTART:20250101T000000
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DTSTART;TZID=Asia/Hong_Kong:20260130T153000
DTEND;TZID=Asia/Hong_Kong:20260130T163000
DTSTAMP:20260510T192657
CREATED:20260121T015143Z
LAST-MODIFIED:20260121T015143Z
UID:114655-1769787000-1769790600@ece.hku.hk
SUMMARY:Seminar on AI Methods for Learning Quantum Systems
DESCRIPTION:Abstract\nAs quantum technologies redefine the landscape of modern electronics and communication networks\, the efficient characterisation and monitoring of complex quantum systems have become essential. In this talk\, I will present AI-driven methods to address the challenges in quantum state learning and property characterisation. First\, I will introduce the Generative Query Network for Quantum (GQNQ)\, which constructs succinct\, data-driven representations from measurement data to accurately predict unseen quantum statistics across diverse quantum systems. I will then discuss a multi-task neural network framework that extracts intricate global properties solely from short-range measurement statistics. Crucially\, our findings demonstrate powerful transfer-learning capabilities\, allowing models trained on small-scale\, classically tractable systems to generalise to much larger quantum systems. These approaches provide a scalable and universal toolkit for optimising next-generation quantum-enhanced electronic and networking systems. \nSpeaker\nDr. Amy Yuexuan WANG \nSpeaker’s Biography\nDr. Amy Yuexuan WANG obtained her Ph.D. from Zhejiang University in 2003. She currently holds a dual appointment as a Senior Research Fellow in the Department of Electrical and Electronic Engineering at The University of Hong Kong (HKU)\, with research expertise in Robotics and Artificial Intelligence\, Wireless Communications and Networking\, Distributed Intelligent Systems and AI for science. \nHer distinguished career includes over 20 years of academic leadership\, with previous roles as a professor at Tsinghua University and as the Associate Director of the AI Lab at HKU. Prof. Wang has an exceptional record in competitive research funding\, having successfully secured and directed numerous major national grants. She has served as the principal investigator for multiple National Key R&D Programs of China and National Natural Science Foundation of China (NSFC) projects\, with a cumulative funding record exceeding RMB 80 million. Her recent applied research focuses on blockchain ecosystem security and privacy-preserving computation\, with technologies deployed in major financial and industrial platforms. \nDr. Wang maintains extensive industry collaborations and holds several patents in areas such as collaborative AI models and 3D printing. Her entrepreneurial work includes co-founding a startup that secured significant contracts for domestically developed AI-CAD software. A recipient of the 2014 National Teaching Achievements Award\, she played a key role in designing Tsinghua University’s pioneering “Yao Class”.  Dr. Wang’s deep technical expertise\, proven leadership in large-scale funded projects\, and strong translational experience will be vital for guiding the project’s technical development and ensuring its practical and commercial impact.
URL:https://ece.hku.hk/events/20260130-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2026/01/1280-4.jpg
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