Tie-Yan Liu is a principal researcher/research manager at Microsoft Research Asia. His research interests include machine learning, information retrieval, data mining, computational advertising, and algorithmic game theory. He is well known for his work on learning to rank for information retrieval: he authored the first book in this area, and published tens of impactful papers on both algorithms and theories of learning to rank (with over 8000 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) and his paper on video analysis won the most cited paper award of Journal of Visual Communication and Image Representation (2004-2006). Tie-Yan Liu is very active in serving the research community. He is a PC chair of SocInfo (2015), ACML (2015), WINE (2014), AIRS (2013), and RIAO (2010), a local chair of ICML (2014), a tutorial chair of SIGIR (2016) and WWW (2014), a doctorial consortium chair of WSDM (2015), a demo/exhibit chair of KDD (2012), and an area/track chair of many conferences including KDD (2015), SIGIR (2008-2011), and WWW (2011, 2015). He is an associate editor of ACM Transactions on Information System (TOIS), an editorial board member of Information Retrieval (INRT) and Foundations and Trends in Information Retrieval (FnTIR). He is a keynote speaker at ECML/PKDD (2014), ORSC (2014), CCIR (2011, 2014), CCML (2013), and PCM (2010), a tutorial speaker at SIGIR (2008, 2010, 2012), WWW (2008, 2009, 2011), and KDD (2012), and a plenary panelist at KDD (2011). He is a senior member of the IEEE and the ACM, and an adjunct/honorary professor of several universities, including Carnegie Mellon University (LTI), University of Nottingham, Nankai University, Sun Yat-Sen University, and University of Science and Technology of China.
Speaker webpage: http://research.microsoft.com/en-us/people/tyliu/