Tie-Yan Liu is a principal researcher of Microsoft Research Asia, leading the research on artificial intelligence and machine learning. He is very well known for his pioneer work on learning to rank and computational advertising, and his recent research interests include deep learning, reinforcement learning, and distributed machine learning. As a researcher in an industrial lab, Tie-Yan is making his unique contributions to the world. On one hand, many of his technologies have been transferred to Microsoft’s products and online services (such as Bing, Microsoft Advertising, and Azure), and open-sourced through Microsoft Cognitive Toolkit (CNTK), Microsoft Distributed Machine Learning Toolkit (DMTK), and Microsoft Graph Engine. On the other hand, he has been actively contributing to academic communities. He is an adjunct/honorary professor at Carnegie Mellon University (CMU), University of Nottingham, and several other universities in China. His papers have been cited for tens of thousands of times in refereed conferences and journals. He has won quite a few awards, including the best student paper award at SIGIR (2008), the most cited paper award at Journal of Visual Communications and Image Representation (2004-2006), the research break-through award at Microsoft Research (2012), and Top-10 Springer Computer Science books by Chinese authors (2015). He has been invited to serve as general chair, program committee chair, local chair, or area chair for a dozen of top conferences including SIGIR, WWW, KDD, ICML, NIPS, IJCAI, AAAI, ACL, ICTIR, as well as associate editor/editorial board member of ACM Transactions on Information Systems, ACM Transactions on the Web, Neurocomputing, Information Retrieval Journal, and Foundations and Trends in Information Retrieval. Tie-Yan Liu is a fellow of the IEEE, a distinguished member of the ACM, an academic committee member of the CCF, and a vice chair of the CIPS information retrieval technical committee.
刘铁岩博士，微软亚洲研究院首席研究员，领导机器学习和人工智能方向的研究工作。同时他也是美国卡内基-梅隆大学（CMU）客座教授、英国诺丁汉大学荣誉教授、中国科技大学、中山大学、南开大学的博士生导师。刘博士的的先锋性工作促进了机器学习与信息检索之间的融合，被国际学术界公认为“排序学习”领域的代表人物，他在该领域的学术论文已被引用近万次，并受Springer出版社之邀撰写了该领域的首部学术专著（并成为Springer计算机领域华人作者十大畅销书之一）。近年来，刘博士在博弈机器学习、深度学习、分布式机器学习等方面也颇有建树，他的研究工作多次获得最佳论文奖、最高引用论文奖、研究突破奖；被广泛应用在微软的产品和在线服务中、并通过微软认知工具包（CNTK）、微软分布式机器学习工具包（DMTK）、微软图引擎（Graph Engine）等项目开源。他曾受邀担任了包括SIGIR、WWW、KDD、ICML、NIPS、AAAI、ACL在内的顶级国际会议的组委会主席、程序委员会主席、或领域主席；以及包括ACM TOIS、ACM TWEB、Neurocomputing在内的国际期刊副主编。他是国际电子电气工程师学会（IEEE）院士，美国计算机学会（ACM）杰出会员，中国计算机学会（CCF）学术工委，中文信息学会（CIPS）信息检索专委会副主任。