為了推進視頻大數據理論研究和工程技術的應用開發。金融大數據研究院邀請美國貝爾實驗室首席專家姜洪博士將在10月15日到10月25日之間在犀浦校區進行短期培訓（具體時間和地點另行通知）。
本期講學內容主要針對研究生、相關研究人員和高年級本科生而設置，主要涉及到視頻數據處理的基本數學理論，算法技術實現和相關大數據最新研究進展，目的在於快速的將聽眾引領到相關研究領域。
主要課程信息如下：
Applied Math in Computational Imaging and Machine Learning
These lectures are intended for students who are interested in Applied Math, Computer Vision and Machine Learning and have taken undergraduate courses in Calculus, Partial Differential Equations and Linear Algebra. The lectures will cover applied mathematics topics in solving real world problems, primarily in the fields of computational imaging, wireless communications and machine learning, including the topics of iterative solutions of systems of linear equations, compressed sensing and Lipschitz learning. The materials presented in the lectures are related to recent research results in computational imaging.
Preliminary agenda:
1 Introduction
2 Basics of computational imaging
3 Basics of matrix computations
4 Lensless imaging
5 Iterative solutions of linear systems
6 Imaging with structured illumination
7 Noise analysis
8 Compressive imaging
9 Introduction to theory of compressed sensing
10 Lipschitz learning
姜洪博士簡介
Hong Jiang is a Department Head in Bell Labs. His research interests include signal processing, digital communications, and image and video compression. He invented key algorithms for VSB demodulation and HDTV video processing in the first generation receiver chipset for the North America HDTV ATSC system. He pioneered hierarchical modulation for satellite communication that resulted in the commercialization of video transmission over satellite and made key contributions to applications of the hierarchical modulation in the DVS-SH standard. He led the Bell Labs team that invented the lensless compressive imaging as a new way to record the world around us. He has published more than 70 articles in peer reviewed scientific and engineering journals, and more than 40 U.S. patents in digital communications and video processing.
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