Carlos Guestrin's current research spans the areas of planning,
reasoning and learning in uncertain dynamic environments, focusing 
on applications in sensor networks, manycore computing, and addressing
the challenge of information overload. 
He is the Finmeccanica Assistant Professor in the Machine Learning 
and in the Computer Science Departments at Carnegie Mellon University. 
Previously, he was a senior researcher at the Intel Research Lab in 
Berkeley. Carlos received his PhD in Computer Science from Stanford 
University and a Mechatronics Engineer degree from the University of 
Sao Paulo, Brazil.  Carlos' work received awards at a number of
conferences and two journals: KDD 2007, IPSN 2005 and 2006, VLDB 2004, 
NIPS 2003 and 2007, UAI 2005, ICML 2005, JAIR in 2007, and JWRPM in 2009.  
He is also a recipient of the ONR Young Investigator Award, the NSF Career 
Award, the Alfred P. Sloan Fellowship, the IBM Faculty Fellowship and 
the Siebel Scholarship.  He was named one of the 2008 `Brilliant 10' 
by Popular Science Magazine, received the IJCAI Computers and
Thought Award, and the Presidential Early Career Award for
Scientists and Engineers (PECASE).  Carlos is currently a member of 
the Information Sciences and Technology (ISAT) advisory group for DARPA.