2003网站太阳集团将于2019年5月15日周三舉行主題為網絡表示學習、深度學習以及海洋新能源應用的學術報告，敬請光臨！

   報告題目：網絡表示學習、深度學習以及海洋新能源應用
   報告人： 唐宇飛 博士， 美國佛羅裡達大西洋大學助理教授
   報告時間：2019年5月15日 周三 上午  10:00
   報告地點：逸夫樓2樓201會議室

報告摘要：
    Networks are ubiquitous and are a part of our common vocabulary. Network science and engineering has emerged as a formal field over the last twenty years  and has seen explosive growth. Ideas from network science are central to companies such as Google, Twitter, Facebook, and LinkedIn. The concepts have also been used to address fundamental problems in diverse fields, such as biology, economics, social sciences, psychology, power systems, telecommunications, public health and marketing. Recent years have seen a surge in approaches that automatically learn to encode network structure into low-dimensional embeddings, using techniques based on deep learning and nonlinear dimensionality reduction. These network representation learning (NRL) approaches remove the need for painstaking feature engineering and have led to state-of-the-art results in network-based tasks, such as node classification, node clustering, and link prediction. In this talk, we will cover key advancements in NRL with an emphasis on fundamental advancements made in the last several years. We will introduce our related work, including multi-label network representation learning and topical network embedding, as well as very recent advancements in graph neural networks. Finally, we will introduce our recent work on deep learning applications in marine renewable energy generation system prognostic health management.

報告人簡介：
   唐宇飛博士目前是佛羅裡達大西洋大學電氣與計算機學院助理教授，領導智能與韌性系統研究課題組。唐博士于2016年從美國羅德島大學獲得電氣工程博士學位，師從著名計算智能專家何海波教授。唐博士課題組目前主要研究興趣有機器學習，網絡大數據挖掘，以及在空間物理系統應用。唐博士目前與美國國家新能源實驗室（NREL），美國國家東南海洋新能源研究中心（SNMREC）等國際頂尖機構開展緊密合作。唐博士是多種頂級雜志以及會議審稿人，包括IEEE TNNLS，IEEE TSG，IEEE TBD，ICDM,  AAAI等。