Dr Jen-Tzung Chien作主題報(bào)告

Dr Jing-Hao Xue作主題報(bào)告

魯東大學(xué)信息與電氣工程學(xué)院講師于泓博士做分享

北京郵電大學(xué)副教授、博士生導(dǎo)師馬占宇博士做分享

合影留念

11月18日，倫敦大學(xué)學(xué)院統(tǒng)計(jì)科學(xué)系的副教授薛景浩副博士、魯東大學(xué)信息與電氣工程學(xué)院講師于泓博士，國(guó)立交通大學(xué)教授簡(jiǎn)仁宗博士，以及北京郵電大學(xué)副教授、博士生導(dǎo)師馬占宇博士應(yīng)邀來(lái)校進(jìn)行學(xué)術(shù)交流。

交流期間Jing-Hao Xue博士、于泓博士、Jen-Tzung Chien博士和馬占宇博士為學(xué)院師生分別做了題目為“Metric learning with Lipschitz continuous functions”、“虛假語(yǔ)音檢測(cè)算法研究”、“Stochastic Markov Recurrent Neural Networks”和“數(shù)據(jù)的非高斯建模與分析”的學(xué)術(shù)報(bào)告。Jing-Hao Xue博士分享了他近期關(guān)于度量學(xué)習(xí)的科研工作和取得的學(xué)術(shù)成果。于泓博士講述主流的語(yǔ)音合成算法，介紹了如何構(gòu)建有效的虛假語(yǔ)音檢測(cè)算法。Jen-Tzung Chien博士介紹一種新的用于深度序列學(xué)習(xí)的隨機(jī)馬爾可夫遞歸神經(jīng)網(wǎng)絡(luò)。馬占宇博士圍繞如何充分利用非高斯分布數(shù)據(jù)的統(tǒng)計(jì)特性，探索有別于傳統(tǒng)高斯建模的思路。

互動(dòng)環(huán)節(jié)中，參會(huì)老師介紹了各自學(xué)校的相關(guān)情況，認(rèn)真回答了同學(xué)們的提問(wèn)并和他們進(jìn)行討論。

Jing-Hao Xue簡(jiǎn)介：

Dr Jing-Hao Xuereceived the B.Eng. degree in telecommunication and information systems in 1993 and the Dr.Eng. degree in signal and information processing in 1998, both from Tsinghua University, the M.Sc. degree in medical imaging and the M.Sc. degree in statistics, both from Katholieke Universiteit Leuven in 2004, and the Ph.D. degree in statistics from the University of Glasgow in 2008. He is an Associate Professor in the Department of Statistical Science at University College London and a Turing Fellow in the Alan Turing Institute. His research interests include statistical machine learning, high-dimensional data analysis, pattern recognition and image analysis.

于泓介紹：

魯東大學(xué)信息與電氣工程學(xué)院講師，主要從事語(yǔ)音信號(hào)處理、深度神經(jīng)網(wǎng)絡(luò)、人工智能等方向的研究。主持省部及項(xiàng)目多項(xiàng)，在國(guó)內(nèi)外重要期刊，會(huì)議上表發(fā)SCI、EI論文十余篇，獲山東省科技進(jìn)步二等獎(jiǎng)一項(xiàng)。

Jen-Tzung Chien簡(jiǎn)介：

Jen-Tzung Chienreceived his Ph.D. degree in electrical engineering from National Tsing Hua University, Hsinchu, Taiwan, ROC, in 1997. He is now with the Department ofElectrical and Computer Engineeringand the Department ofComputer Science,National Chiao Tung University, Hsinchu, Taiwan, where he is currently a Chair Professor. He held the Visiting Professor position at theIBM T. J. Watson Research Center, Yorktown Heights, NY, in 2010. His research interests include machine learning, deep learning, natural language processing and computer vision.Dr. Chien served as the associate editor of the IEEE Signal Processing Letters in 2008-2011 and the tutorial speaker of the ICASSP in 2012, 2015, 2017, the INTERSPEECH in 2013, 2016, the COLING in 2018, the AAAI, ACL, KDD, IJCAI in 2019, and the general co-chair of theIEEE International Workshop on Machine Learning for Signal Processingin 2017. He received the Best Paper Award of IEEE Automatic Speech Recognition and Understanding Workshop in 2011 and theAAPM Farrington Daniels Awardin 2018. He has published extensively, including the books "Bayesian Speech and Language Processing", Cambridge University Press, in 2015, and"Source Separation and Machine Learning", Academic Press, in 2018. He is currently serving as an elected member of the IEEEMachine Learning for Signal ProcessingTechnical Committee.

馬占宇介紹：

馬占宇，瑞典皇家理工學(xué)院（KTH-Royal Institute of Technology）博士，現(xiàn)任北京郵電大學(xué)副教授、博士生導(dǎo)師，丹麥奧爾堡大學(xué)（Aalborg University）兼職副教授、博士生導(dǎo)師，IEEE 高級(jí)會(huì)員，中國(guó)圖象圖形學(xué)學(xué)會(huì)高級(jí)會(huì)員、理事、副秘書(shū)長(zhǎng)，中國(guó)計(jì)算機(jī)學(xué)會(huì)高級(jí)會(huì)員、計(jì)算機(jī)視覺(jué)專(zhuān)委會(huì)秘書(shū)長(zhǎng)。主要研究方向是以數(shù)據(jù)的非高斯建模與分析為代表的模式識(shí)別與機(jī)器學(xué)習(xí)基礎(chǔ)理論與方法，及其在計(jì)算機(jī)視覺(jué)、城市大數(shù)據(jù)分析、多媒體信號(hào)處理等領(lǐng)域的應(yīng)用。共在包括IEEE TPAMI 在內(nèi)的期刊和會(huì)議上發(fā)表論文80 多篇，Google Scholar 引用1800+次，5 篇論文入選ESI 高被引論文（含3 篇熱點(diǎn)論文）。擔(dān)任IEEE Transactions on Vehicular Technology等多個(gè)國(guó)際期刊的編委，是SPLINE 2016 Technical Co-Chair，IEEE MLSP 2018 Program Chair 等國(guó)際會(huì)議職務(wù)或委員，授 權(quán)發(fā)明專(zhuān)利15 項(xiàng)；主持國(guó)家自然基金優(yōu)秀青年科學(xué)基金、聯(lián)合重點(diǎn)基金、國(guó)家重點(diǎn)研發(fā)計(jì)劃課題等項(xiàng)目；獲中國(guó)人工智能學(xué)會(huì)“第七屆吳文俊人工智能科學(xué)技術(shù)獎(jiǎng)”一等獎(jiǎng)，“北京市科學(xué)技術(shù)獎(jiǎng)”二等獎(jiǎng)，“北京青年優(yōu)秀科技論文”一等獎(jiǎng)；得到自然基金“優(yōu)青” “北京市科技新星”計(jì)劃等人才項(xiàng)目計(jì)劃的支持。