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香港中文大學(深圳)未來智聯網絡論壇

  • 2018.10.12
  • 活動
香港中文大學(深圳)將于10月17日成立第二個校級研究院——“香港中文大學(深圳)未來智聯網絡研究院”,并于當天舉行“未來智聯網絡”論壇。

? ? ? 智能和聯接是當前信息科技的兩大主題。這兩個主題的融合,是未來科技發展的主要方向之一。香港中文大學(深圳)在人工智能和網絡聯接方面都有深厚的人才儲備。為了更好地整合這兩方面的資源,融合智能與網絡聯接,在這一前沿方向上建設一個國際一流的科研平臺,香港中文大學(深圳)繼成立數據與運籌科學研究院(iDDA)之后,將于10月17日成立第二個校級研究院——“香港中文大學(深圳)未來智聯網絡研究院”,并于當天舉行“未來智聯網絡”論壇。論壇將邀請多名國內外著名院士、專家、學者和各級政府領導來共同探討智能和聯接兩大主題的融合,為研究院的發展提供戰略咨詢和指導性意見。

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時間:2018年10月17日

地點:香港中文大學(深圳)道遠樓理事會會議室

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日程安排

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參會嘉賓

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題目:深度學習與自然語言理解

演講者:何曉冬博士,京東 AI 研究院常務副院長

日期:2018年10月17日,星期三

時間:11:30-12:15

地點:道遠樓理事會會議室

語言:中文

講座概要:

何曉冬博士會先簡略回顧近年來深度學習技術對語音、語言和視覺等方面的驅動,然后將著重從兩個方面來探討其在自然語言處理(NLP)方面的前沿研究,包括如何讓AI通過NLP技術理解人類,如理解意圖,解析語義,識別情緒,搜索推薦;和如何讓AI的結果能被人類理解接受,如文本摘要,內容生成,話題展開,情感對話等。何博士也會探討在NLP強化學習,語言/視覺跨模態智能,文本內容生成,情感和風格表達,及人機對話這些前沿方向上的最新研究進展。

主講嘉賓簡介:

何曉冬博士為京東技術副總裁、AI研究院常務副院長、深度學習及語音和語言實驗室主任,華盛頓大學(西雅圖)兼職教授。其工作包括DSSM(深度結構語義模型/深度語義匹配模型)、HAN(層次化注意力網絡)、圖像描述機器人CaptionBot等。曾任美國微軟雷德蒙德研究院首席研究員(Principal Researcher)及深度學習技術中心(DLTC)負責人。研究方向主要聚焦在人工智能領域,包括深度學習、自然語言處理、語言及視覺多模態智能等。

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題目:When IoT meets Big Data

演講者:曹建農教授,香港理工大學

日期:2018年10月17日,星期三

時間:14:00-14:45

地點:道遠樓理事會會議室

語言:中文

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講座概要:

In the past decade, applications of Internet of Things (IoT) such as Smart Home, Smart Cities, Smart Healthcare etc. have been deployed where the devices in our surroundings are interconnected to provide better services and comfort to humans. More recently, we witness the emerging applications in industrial internet, supply chains and other areas where the scale of the systems, the number of devices and data being generated continuously increases. As the IoT continues to develop, further potential can be realized by a combination with related technology approaches including Big Data Computing. The intersection of IoT and Big Data is a fascinating area of innovation with tremendous scope for business impact. In this talk, I will describe the evolution of IoT from instrumentation and interconnection to intelligence driven by big data analytics. When IoT meets big data, we see the direction towards smart IoT, which will facilitate and empower advanced applications. I will focus on the current challenges and future development of smart IoT leveraging big data analytics

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主講嘉賓簡介:

Dr. Cao is currently a Chair Professor of Department of Computing at The Hong Kong Polytechnic University, Hong Kong. He is also the director of the Internet and Mobile Computing Lab in the department and the director of University’s Research Facility in Big Data Analytics. His research interests include parallel and distributed computing, wireless sensing and networks, pervasive and mobile computing, and big data and cloud computing. He has co- authored 5 books, co-edited 9 books, and published over 600 papers in major international journals and conference proceedings. He received Best Paper Awards from conferences including IEEE DSAA 2017, IEEE SMARTCOMP 2016, IEEE ISPA 2013, IEEE WCNC 2011,etc. Dr. Cao served the Chair of the Technical Committee on Distributed Processing of IEEE Computer Society from 2012 to 2014, a member of IEEE Fellows Evaluation Committee of the Computer Society and the Reliability Society, a member of IEEE Computer Society Education Awards Selection Committee, a member of IEEE Communications Society Awards Committee, and a member of Steering Committee of IEEE Transactions on Mobile Computing. He has also served as chairs and members of organizing and technical committees of many international conferences, and as associate editor and member of the editorial boards of many international journals. Dr. Cao is a fellow of IEEE and ACM distinguished member. In 2017, he received the Overseas Outstanding Contribution Award from China Computer Federation.

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題目:Mobility-Enhanced Edge in Telligence for Ultra-reliable and Low-Latency Communications (MEET-U)

演講者:牛志升教授,清華大學

日期:2018年10月17日,星期三

時間:14:45-15:30

地點:道遠樓理事會會議室

語言:中文

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講座概要:

As the Internet of Things (IoT) and 5G mobile communications technologies develops, a hyper-connected society that makes everything in the planet connected is becoming a reality.? This will necessitate the future mobile networks to more flexibly and intelligently adapt to a wide range of services.? Among them, the most critical and challenging ones are the so-called mission-critical applications such as industrial Internet, networked robotics, VR/AR/MR, and connected vehicles, which require ultra-reliable and low-latency communications (URLLC). To realize that, the future mobile networks need to be fueled with additional resources (not only spectrum and energy resources, but also compute and cache resources) and enhanced intelligence in a distributed manner so that the networks can be smart enough. As a result, big data analytics, mobile edge computing/caching (MEC) and artificial intelligence (AI) will play key roles.

Meanwhile, mobility has been considering as a major obstacle to mobile communications because it may cause fading, shadowing, near-far effect, handover, roaming, etc. However, as the electric vehicles and autonomous cars are getting more and more powerful with rich capabilities of sensing, communicating, computing, caching, and powering, they can be used as movable edge servers not only to provide task-offloading services opportunistically but also to disseminate the edge intelligence to the whole network while moving.? In this regard, mobility is in fact exploited to enhance the network intelligence so that the URLLC services can be realized by making the critical applications meet with the movable intelligent servers opportunistically.? The key questions then include (but not limit to): 1) how to collect and process the big data in a distributed manner and generate the edge intelligence locally? 2) how to disseminate the distributed intelligence across the whole network effectively? 3) how to find and assign the best opportunities to the moving users? 4) how to efficiently provide reliability and latency guarantees to mission-critical applications??????????????

This talk will explore advanced artificial intelligence (AI) techniques for autonomous and smart decision-makings in future wireless networks.? In particular, we will combine expertise on mobile communications and AI to leverage recent advances, such as in the field of deep learning, to develop traffic and network condition prediction methods that can be used for smart task-offloading and content-caching and optimized resource allocation. We are particularly interested in the development of autonomously evolving models of network sharing that aggregates resources across technologies, different operators, and service requirements.

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主講嘉賓簡介:

Zhisheng Niu graduated from Beijing Jiaotong University, China, in 1985, and got his M.E. and D.E. degrees from Toyohashi University of Technology, Japan, in 1989 and 1992, respectively.? During 1992-94, he worked for Fujitsu Laboratories Ltd., Japan, and in 1994 joined with Tsinghua University, Beijing, China, where he is now a professor at the Department of Electronic Engineering. His major research interests include queueing theory, traffic engineering, mobile Internet, radio resource management of wireless networks, and green communication and networks.?

Dr. Niu has served as Chair of Emerging Technologies Committee (2014-15), Director for Conference Publications (2010-11), and Director for Asia-Pacific Board (2008-09) in IEEE Communication Society, and currently serving as Director for Online Contents (2018-19) and Area Editor of IEEE Trans. Green Commun. & Networks. ?He received the Outstanding Young Researcher Award from Natural Science Foundation of China in 2009 and the Best Paper Award from IEEE Communication Society Asia-Pacific Board in 2013.? He was also selected as a distinguished lecturer of IEEE Communication Society (2012-15) as well as IEEE Vehicular Technologies Society (2014-18).? He is a fellow of both IEEE and IEICE.