Xi Chen completed his PhD in the Machine Learning Department at Carnegie Mellon University in 2013. He is developing fast and scalable algorithms for parametric and non-parametric structured sparse learning problems with applications to text mining, computational biology and climate modeling. He also investigates machine learning foundations for collective intelligence, in particular crowdsourcing. Prior to his PhD, he obtained his Masters degree in Industry Administration and Operations Research from the Tepper School of Business at CMU. He was the recipient of an IBM PhD Fellowship and American Statistical Association Student Paper Competition Award. He also has interned in several world-leading research labs, including Microsoft Research, IBM Research and NEC Research.