Pedro Domingos was born in 1965. He is a retired professor of computer science and engineering at the University of Washington. He is a researcher in machine learning who developed a method called Markov logic networks that help computers make decisions when they aren't sure.
Education
Domingos earned an undergraduate degree and a Master of Science degree from Instituto Superior Técnico (IST). He then went to the University of California, Irvine, where he earned another Master of Science degree and later completed his PhD.
Research and career
After working for two years as an assistant professor at IST, he became an assistant professor of Computer Science and Engineering at the University of Washington in 1999. He was promoted to full professor in 2012. In 2018, he began leading a machine learning research group at the hedge fund D. E. Shaw & Co., but he left this position in 2019.
He helped create the International Machine Learning Society. As of 2018, he was part of the editorial board for the Machine Learning journal.
- Pedro Domingos, The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World, New York, Basic Books, 2015, ISBN 978-0-465-06570-7.
- Pedro Domingos, "Our Digital Doubles: AI will serve our species, not control it," Scientific American, vol. 319, no. 3 (September 2018), pp. 88–93. "AIs are like autistic savants and will remain so for the foreseeable future…. AIs lack common sense and can easily make errors that a human never would… They are also liable to take our instructions too literally, giving us precisely what we asked for instead of what we actually wanted." (p. 93.)
- Pedro Domingos, 2040: A Silicon Valley Satire, BookBaby, 2024, ISBN 979-8-350-96334-2.
- 2014: ACM SIGKDD Innovation Award. This was given for his foundational research in data stream analysis, cost-sensitive classification, adversarial learning, and Markov logic networks, as well as applications in viral marketing and information integration.
- 2010: Elected an Association for the Advancement of Artificial Intelligence (AAAI) Fellow. This was for significant contributions to the field of machine learning and to the unification of first-order logic and probability.
- 2003: Sloan Fellowship
- 1992–1997: Fulbright Scholarship