I received an undergraduate degree (1988) and M.S. in Electrical Engineering and Computer Science (1992) from IST, in Lisbon. I received an M.S. (1994) and Ph.D. (1997) in Information and Computer Science from the University of California at Irvine. I spent two years as an assistant professor at IST, before joining the faculty of the University of Washington in 1999. I'm the author or co-author of over 200 technical publications in machine learning, data mining, and other areas. I'm a winner of the SIGKDD Innovation Award, the highest honor in data science. I'm a AAAI Fellow, and I've received a Sloan Fellowship, an NSF CAREER Award, a Fulbright Scholarship, an IBM Faculty Award, several best paper awards, and other distinctions.
My main research interests are in the fields of machine learning and data mining. I'd like to make computers do more with less help from us, learn from experience, adapt effortlessly, and discover new knowledge. We need computers that reduce the information overload by extracting the important patterns from masses of data. This poses many deep and fascinating scientific problems: How can a computer decide autonomously which representation is best for target knowledge? How can it tell genuine regularities from chance occurrences? How can pre-existing knowledge be exploited? How can a computer learn with limited computational resources? How can learned results be made understandable by us?