第十三届中国机器学习及其应用研讨会

贾伟中科院合肥

http://lamda.nju.edu.cn/conf/mla15/index.htm

“机器学习及其应用”（MLA）系列研讨会是国内机器学习领域的著名研讨会。会议本着“学术至上、其余从简”的原则，不征文、不收费，迄今已举行12届，近年来每届参会人数超过800人。MLA的更多信息请见：http://lamda.nju.edu.cn/conf/mla/。

第十三届研讨会将由南京大学软件新技术国家重点实验室主办，拟邀请海内外从事机器学习及相关领域研究的10余位专家与会进行学术交流，包括特邀报告、顶会交流、以及Top Conference Review等部分。

该研讨会不征文，但欢迎机器学习及相关领域的学者、研究生前来旁听特邀报告并参加讨论。研讨会不收取注册费，但食宿需自理。

特邀报告专家(陆续增加中)：(按姓氏拼音排序) 耿    新 教授 [Homepage] 东南大学计算机科学与工程学院 耿新，博士，教授，东南大学计算机科学与工程学院副院长、博导。分别于2001年和2004年在南京大学计算机科学与技术系获理学学士学位和工学硕士学位，2008年获得澳大利亚Deakin大学博士学位。主要研究兴趣包括机器学习、模式识别、计算机视觉。近年来，在这些领域发表各类学术论文30余篇。现为中国人工智能学会机器学习专委会委员、江苏省计算机学会人工智能专委会常务委员、江苏省微型电脑应用协会人工智能专委会常务委员。 李    涛 教授 [Homepage] Florida International University Dr. Tao Li is currently a full professor in the School of Computer Science, Florida International University. He received his Ph.D. in computer science from the Department of Computer Science, University of Rochester in 2004. He was a recipient of NSF CAREER Award (2006-2010) and multiple IBM Faculty Research Awards (2005, 2007 & 2008). In 2009, he received FIU's Excellence in Research and Creativities Award. In 2010, he received IBM Scalable Data Analytics Innovation Award. He received the inaugural Graduate Student Mentorship Award from the College of Engineering and Computing at FIU in 2011. He is on the editorial board of ACM Transactions on Knowledge Discovery from Data (ACM TKDD), IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), and Knowledge and Information System Journal (KAIS). 林宙辰 教授 [Homepage] 北京大学智能科学系 Zhouchen Lin received the Ph.D. degree in applied mathematics from Peking University in 2000. He is currently a Professor at Key Laboratory of Machine Perception (MOE), School of Electronics Engineering and Computer Science, Peking University. He is also a Chair Professor at Northeast Normal University and a guest professor at Beijing Jiaotong University. Before March 2012, he was a Lead Researcher at Visual Computing Group, Microsoft Research Asia. He was a guest professor at Shanghai Jiaotong University and Southeast University, and a guest researcher at Institute of Computing Technology, Chinese Academy of Sciences. His research interests include computer vision, image processing, computer graphics, machine learning, pattern recognition, and numerical computation and optimization. He is an associate editor of International J. Computer Vision and IEEE T-PAMI, and a Senior member of the IEEE. He served CVPR2014 as an area chair. 刘铁岩 博士 [Homepage] 微软亚洲研究院 Tie-Yan Liu is a principal researcher and research manager at Microsoft Research Asia, an adjunct professor of Carnegie Mellon University (LTI), and an honorary professor of University of Nottingham. His research interests include artificial intelligence, machine learning, information retrieval, data mining, computational advertising, and algorithmic game theory. He is well known for his pioneer work on learning to rank. He has authored the first book in this area and published tens of impactful papers on both algorithms and theories of learning to rank (with over 9000 citations in the past few years). He has also published extensively on other topics. In particular, his paper on graph mining won the best student paper award of SIGIR (2008); his paper on video shot boundary detection won the most cited paper award of the Journal of Visual Communication and Image Representation (2004-2006); and his work on Internet economics won the research break-through award of Microsoft Research Asia (2012). Tie-Yan is very active in serving the research community. He is a program committee co-chair or area chair of many conferences including ACML (2015), WINE (2014), AIRS (2013), AAAI (2016), NIPS (2015), KDD (2015), ACML (2014), SIGIR (2008-2011), AIRS (2009-2011), IJCAI (2013, 2015), and WWW (2011, 2015). He is an associate editor of ACM Transactions on Information System (TOIS), an editorial board member of Information Retrieval Journal (INRT) and Foundations and Trends in Information Retrieval (FnTIR). He is a senior member of the IEEE and the ACM, as well as a senior member and distinguished speaker of the CCF. He is also an adjunct professor/PhD supervisor of several universities in China, including Nankai University, Sun Yat-Sen University, and University of Science and Technology of China. 孟德宇 副教授 [Homepage] 西安交通大学 孟德宇，博士，西安交通大学数学与统计学院副教授，博导。 曾于2006年赴英国Essex大学进行学术访问，于2009年赴香港中文大学进行博士后研究,2012-2014年赴卡内基梅隆大学进行学术合作。在TIP, TKDE, TSMCB, TNNLS, PR, Neural Computation等国际期刊与CVPR, ICCV, ECCV, AAAI, ICML, NIPS, ACM MM等国际学术会议发表论文多篇。担任ICML, NIPS, CVPR, ICCV, ACM MM, AAAI等会议程序委员会委员。2010年获陕西省青年科技奖，陕西省优秀博士论文奖。目前主要聚焦于机器学习、数据挖掘、计算机视觉、多媒体分析等方面的研究。 Prof. Stephen Muggleton [Homepage] Imperial College RAE/MSR Chair Professor, 帝国理工学院英国工程院院士，AAAI fellow, IET fellow, BCS fellow. Stephen Muggleton is Director of the Syngenta University Innovation Centre at Imperial College and holds a Royal Academy of Engineering/Syngenta Research Chair. He received his BSc in Computer Science at the University of Edinburgh in 1982. His PhD research, on the topic Inductive Acquisition of Expert Knowledge was carried out at Edinburgh University under the supervision of Prof. Donald Michie He was awarded his PhD in 1986. During the period 1986-1990 he was a Turing Institute Research Fellow. In 1990 he was awarded a British SERC Postdoctoral Fellowship. In 1993 he was awarded a 5-year EPSRC Adanced Research Fellowship at Oxford University Computing Laboratory, where he founded and headed the Machine Learning Research Group. During the same year he took up an invitation to the Fujitsu Chair as Visiting Associate Professor at the University of Tokyo. While working at the University of Oxford he was awarded honorary MA status, elected Research Fellow at Wolfson College and was tutor at Corpus Christi College. In 1997 he was made Reader by the Distinctions Committee of the University of Oxford. In October 1997 he took up the Chair of Machine Learning at the University of York and set up and headed a new research group for the University. In July 2001 he took up the Joint Research Council Funded Chair of Computational Inference and Bioinformatics at the Department of Computing, Imperial College. He was elected a Fellow of the American Association for Artificial Intelligence in 2002. In 2005 he became Director of Modelling at the new Centre for Integrative Systems Biology at Imperial College (CISBIC) and in 2008 was elected as both a Fellow of the Institution of Engineering and Technology (IET) and a Fellow of the British Computer Society (BCS). In 2010 he was elected a Fellow of the Royal Academy of Engineering. In 2011 he was elected a board member of the International Machine Learning Society and a Fellow of the Society for Biology. In 2014 he was elected as a Fellow of ECCAI. 苏文藻 教授 [Homepage] 香港中文大学 Anthony Man-Cho So received his BSE degree in Computer Science from Princeton University in 2000 with minors in Applied and Computational Mathematics, Engineering and Management Systems, and German Language and Culture. He then received his MSc degree in Computer Science in 2002, and his PhD degree in Computer Science with a PhD minor in Mathematics in 2007, all from Stanford University. Dr. So joined The Chinese University of Hong Kong (CUHK) in 2007. He currently serves as Assistant Dean of the Faculty of Engineering and is an Associate Professor in the Department of Systems Engineering and Engineering Management. He also holds a courtesy appointment as Associate Professor in the CUHK-BGI Innovation Institute of Trans-omics. His recent research focuses on the interplay between optimization theory and various areas of algorithm design, such as computational geometry, signal processing, bioinformatics, stochastic optimization, combinatorial optimization, and algorithmic game theory. At present, Dr. So serves on the editorial boards of Optimization Methods and Software, Mathematics of Operations Research, IEEE Transactions on Signal Processing, and Journal of Global Optimization. He received the 2010 Optimization Prize for Young Researchers from the Optimization Society of the Institute for Operations Research and the Management Sciences (INFORMS), and the 2010 Young Researcher Award from CUHK. He also received the 2008 Exemplary Teaching Award and the 2011 and 2013 Dean's Exemplary Teaching Award from the Faculty of Engineering at CUHK, and the 2013 Vice-Chancellor's Exemplary Teaching Award from CUHK. 徐增林 教授 [Homepage] 电子科技大学 徐增林教授于2009年毕业于香港中文大学计算机科学与工程专业，师从香港中文大学工程学院副院长、亚太神经网络协会APPNA常务副会长Irwin King教授和IEEE会士、美国科学促进会AAAS会士Michael R. Lyu教授。并且先后在美国密西根州立大学、德国马克思普朗克信息研究所及萨尔大学、美国普渡大学等著名研究机构访问和从事学术研究工作；主要合作者包括密西根州立大学Rong Jin教授、芬兰科学院院士/IEEE会士Erkki Oja教授、普渡大学Alan Qi教授、Ninghui Li教授等。徐增林教授是2013年中组部“青年千人计划”、2014年四川省“千人计划”入选者。 杨    健 教授 [Homepage] 南京理工大学 杨健，南京理工大学计算机科学与工程学院副院长，长江学者特聘教授，国家杰出青年基金获得者，是国际知名学术期刊《Pattern Recongnition Letters》和《Neurocomputing》的编委(Associate Editor)。2003年以来，在国际期刊论文被SCI收录的论文引用已逾1200次，其中他引超过1000次，单篇论文最高被引用逾400次。根据Scopus的检索结果，其国际期刊论文被引用已逾1600次，其中单篇最高被引用逾600次。2008年入选教育部“新世纪优秀人才支持计划”，2009年，以排名第二的身份获国家自然科学二等奖，获第十一届中国青年科技奖。2010年获国务院政府特殊津贴，2011年获国家杰出青年科学基金，2013年入选国家百千万人才工程并被授予“有突出贡献中青年专家”称号，2014年入选教育部“长江学者”特聘教授。 杨    强 教授 [Homepage] 香港科技大学 杨强，香港科技大学计算机系教授。他是AAAI Fellow, IEEE Fellow, AAAS Fellow, IAPR Fellow和ACM杰出科学家。主要研究兴趣是人工智能和数据挖掘。杨强于1982年毕业于北京大学天体物理专业，获得学士学位。分别于1985年和1987年毕业于美国马里兰大学的计算机系和天文学系，获得双硕士学位。于1989年毕业于马里兰大学计算机系，获得计算机博士学位。自1989年到 1995先后任滑铁卢大学的助理教授和副教授，1995年到2001年在加拿大西蒙·弗雷泽（Simon Fraser)大学先后任副教授，正教授一职，同期担任NSERC工业研究主任。自2001年，在香港科技大学先后任副教授，正教授一职。他出版过三本书，发表了300多篇关于人工智能和数据挖掘的论文。在2004年和2005年，他指导的队伍赢得了KDDCUP等比赛的冠军。他曾受WSDM2013, SDM2012, IJCAI 2009, ACL 2009 和ACML 2009等著名国际会议的邀请在会议上做主题演讲。在2010年7月，当选为ACM 人工智能协会（SIGART）的副主席。杨强是多本国际期刊的编委，是ACM TIST的创始主编，是IEEE Intelligent Systems，IEEE TKDE (2005-2009)，AI Magazine 等期刊的编委。此外，他也是很多人工智能和数据挖掘相关会议的组织者以及程序联合主席，如 2012年在北京举办的ACM 国际数据挖掘大会（KDD) 的会议主席，以及ACM KDD 2010，ACM RecSys 2013, ACM IUI 2010 等会议的主席。他是国际人工智能大会（IJCAI) 的董事会成员和2015年在阿根廷举办 IJCAI 会议的程序委员会主席。 张长水 教授 [Homepage] 清华大学 1986年7月毕业于北京大学数学系,获得理学学士学位。1992年7月获清华大学自动化系博士学位。现为清华大学自动化系教授, 清华大学自动化系副主任，博士生导师。目前担任国际学术杂志“Pattern Recognition”的编委，“计算机学报”编委，中国人工智能学会常务理事。研究兴趣包括模式识别、机器学习、图像处理、计算机视觉复杂网络等研究领域。在2002－2005年间发表学术论文80多篇，其中在《Physical Review E》, 《Physical A》, 《Pattern Recognition》和IEEE Trans.等杂志以及ICML, NIPS, CVPR, ECML和ECCV等会议上发表论文多篇。 张利军 副教授 [Homepage] 南京大学 张利军博士分别于2007年6月和2012年6月在浙江大学获工学学士和工学博士学位；分别于2011年6月至12月、2012年8月至2014年4月，以访问学生、博士后身份在美国密歇根州立大学计算机科学与工程系访问研究；于2014年4月加入南京大学计算机科学与技术系。主要研究方向为大规模机器学习及优化，在国际学术会议和期刊上发表论文近40篇。曾获浙江大学“竺可桢奖学金”、南京大学“登峰人才支持计划”、第26届AAAI人工智能国际会议“最佳论文”等荣誉。