Amr Ahmed is a Senior Research Scientist at Google. He received his M.Sc and PhD degrees from the School of Computer Science, Carnegie Mellon University in 2009 and 2011, respectively. He is the recipient of 2012 ACM SIGKDD Doctoral Dissertation Award in addition to several best paper awards at KDD 2014, WSDM 2014, and WSDM 2012 (runner up). His research interests include big data, large-scale machine learning, data/web mining, user modeling, personalization, social networks and content analysis. He published over 50 papers and co-presented 5 tutorials at (WWW'11,NIPS'11, WWW'12, KDD'13 and AAAI'14) on these topics. He will serve as an Area Chair for ICML 2014, ICDM 2014 and WSDM 2015.
Ankur Moitra is an Assistant Professor in the Department of Mathematics at MIT and a Principal Investigator in the Computer Science and Artificial Intelligence Lab (CSAIL). Prior to that, he was an NSF CI Fellow at the Institute for Advanced Study, and also a senior postdoc at Princeton University. He completed his PhD and MS at MIT in 2011 and 2009 respectively, where he was a Hertz Fellow and received best thesis awards for his doctoral and masters dissertations.
Misha Belkin is an Associate Professor at the Dept. of Computer Science and Engineering and Dept. of Statistics at the Ohio State University. His research focuses on the theoretical foundations of machine learning and its applications. He received his Ph.D degree from the Mathematics Dept. at University of Chicago in 2003. He was a postdoctoral fellow at the Computer Science Dept. at the University of Chicago from 2003-2005. He has also been a visiting research fellow at a number of research institutions, including MPI Tubingen, University of California, Berkeley, Institute for Pure and Applied mathematics at UCLA, Statisticaland Applied Mathematical Science Institute (SAMSI) and Austrian Institute of Science and Technology (ISTA). He received the U.S National Science Foundation (NSF) Career Award in 2007, and the Lumley Research Award at the College of Engineering of the Ohio State University in 2011. He is currently serving on the Editorial boards for the Journal of Machine Learning Research (JMLR) and IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI).
Stefanie Jegelka is a postdoctoral researcher at UC Berkeley. She received a Ph.D. from ETH Zurich in collaboration with the Max Planck Institute for Intelligent Systems in Tuebingen, and a Diplom in Bioinformatics from the University of Tuebingen, Germany. She has received several fellowships, including one by the German National Academic Foundation, and an ICML 2013 Best Paper Award. Her research interests lie in algorithmic machine learning.