Big Data and Machine Learning


May 22, 2014


Jonathan Huang, Lihong Li, and Mike Zyskowski


Microsoft, Stanford University


Chair: Steven Drucker, Microsoft Research Speakers: Mike Zyskowski, Microsoft Research Lihong Li, Microsoft Research Jonathan Huang, Stanford University


Jonathan Huang, Lihong Li, and Mike Zyskowski

Lihong Li is a machine-learning researcher at Microsoft Research. Prior to joining Microsoft, he was a Research Scientist at Yahoo! Research. He obtained a PhD degree from Rutgers University, MSc from University of Alberta, and BE from Tsinghua University, all in Computer/Computing Science. His main research interests are in machine learning with interaction, including reinforcement learning, multi-armed bandits, and their numerous applications in the big-data era. He has published over 50 research papers, and won paper awards at ICML’08, WSDM’11, and AISTATS’11. He has served as area chair or senior program committee member at ICML, NIPS, and IJCAI.

Jonathan Huang is an NSF Computing Innovation (CI) postdoctoral fellow at the geometric computing group at Stanford University. He completed his Ph.D. in 2011 with the School of Computer Science at Carnegie Mellon University where he also received a Master’s degree in 2008. He received his B.S. degree in Mathematics from Stanford University in 2005. His research interests lie primarily in statistical machine learning and reasoning with combinatorially structured data with applications such as analyzing real world education data. His research has resulted in a number of publications in premier machine learning conferences and journals, receiving a paper award in NIPS 2007 for his work on applying group theoretic Fourier analysis to probabilistic reasoning with permutations.