Dr Jen-Tzung Chien作主题报告

Dr Jing-Hao Xue作主题报告

鲁东大学信息与电气工程学院讲师于泓博士做分享

北京邮电大学副教授、博士生导师马占宇博士做分享

合影留念

11月18日，伦敦大学学院统计科学系的副教授薛景浩副博士、鲁东大学信息与电气工程学院讲师于泓博士，国立交通大学教授简仁宗博士，以及北京邮电大学副教授、博士生导师马占宇博士应邀来校进行学术交流。

交流期间Jing-Hao Xue博士、于泓博士、Jen-Tzung Chien博士和马占宇博士为学院师生分别做了题目为“Metric learning with Lipschitz continuous functions”、“虚假语音检测算法研究”、“Stochastic Markov Recurrent Neural Networks”和“数据的非高斯建模与分析”的学术报告。Jing-Hao Xue博士分享了他近期关于度量学习的科研工作和取得的学术成果。于泓博士讲述主流的语音合成算法，介绍了如何构建有效的虚假语音检测算法。Jen-Tzung Chien博士介绍一种新的用于深度序列学习的随机马尔可夫递归神经网络。马占宇博士围绕如何充分利用非高斯分布数据的统计特性，探索有别于传统高斯建模的思路。

互动环节中，参会老师介绍了各自学校的相关情况，认真回答了同学们的提问并和他们进行讨论。

Jing-Hao Xue简介：

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.

于泓介绍：

鲁东大学信息与电气工程学院讲师，主要从事语音信号处理、深度神经网络、人工智能等方向的研究。主持省部及项目多项，在国内外重要期刊，会议上表发SCI、EI论文十余篇，获山东省科技进步二等奖一项。

Jen-Tzung Chien简介：

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.

马占宇介绍：

马占宇，瑞典皇家理工学院（KTH-Royal Institute of Technology）博士，现任北京邮电大学副教授、博士生导师，丹麦奥尔堡大学（Aalborg University）兼职副教授、博士生导师，IEEE 高级会员，中国图象图形学学会高级会员、理事、副秘书长，中国计算机学会高级会员、计算机视觉专委会秘书长。主要研究方向是以数据的非高斯建模与分析为代表的模式识别与机器学习基础理论与方法，及其在计算机视觉、城市大数据分析、多媒体信号处理等领域的应用。共在包括IEEE TPAMI 在内的期刊和会议上发表论文80 多篇，Google Scholar 引用1800+次，5 篇论文入选ESI 高被引论文（含3 篇热点论文）。担任IEEE Transactions on Vehicular Technology等多个国际期刊的编委，是SPLINE 2016 Technical Co-Chair，IEEE MLSP 2018 Program Chair 等国际会议职务或委员，授 权发明专利15 项；主持国家自然基金优秀青年科学基金、联合重点基金、国家重点研发计划课题等项目；获中国人工智能学会“第七届吴文俊人工智能科学技术奖”一等奖，“北京市科学技术奖”二等奖，“北京青年优秀科技论文”一等奖；得到自然基金“优青” “北京市科技新星”计划等人才项目计划的支持。