Pedro Domingos (born August 2, 1965 or August 2, 1963 in Lisbon, Portugal, with Persian Wikipedia recording undefined 0, 2000) is a Portuguese computer scientist and Professor Emeritus of computer science and engineering at the University of Washington.^[7,17] Domingos received a Licentiate and Master of Science from Instituto Superior Técnico (IST) at the University of Lisbon, followed by an MS and a Ph.D. from the University of California, Irvine in 1997 with a dissertation titled "A Unified Approach to Concept Learning" advised by Dennis F. Kibler. After spending two years as an assistant professor at IST, he joined the University of Washington in 1999 where he currently serves as professor, with Tessa Lau among his notable students.

Domingos is an expert and researcher in artificial intelligence, machine learning, and data science, and is known for co-developing the Markov logic network enabling uncertain inference.^[9,10] He is the author or co-author of more than 200 technical-scientific publications, and his most widely distributed work, The Master Algorithm, was published in 2015.^[11] His honors include the Fulbright Scholarship / Fulbright Program (1992–1997), a Sloan Fellowship (2003), an AAAI Fellowship (2010), and the SIGKDD Innovation Award (2014), the highest honor in data science.^[18]

Pedro Domingos studied electrical engineering and computer science at the Instituto Superior Técnico (IST) in Lisbon, where he received an undergraduate degree and a Master of Science degree.^[11] He subsequently moved to the University of California, Irvine, where he earned a Master of Science degree followed by a doctorate (PhD) in information and computer science.^[1,11]

He joined the University of Washington, where German Wikipedia states he has been teaching since 1989 (serving as a full professor in 2012), whereas Dutch Wikipedia states he has been working as a researcher and professor there since 1999. In 2018, he founded a machine learning research group at the hedge fund D. E. Shaw & Co.^[2] In The Master Algorithm, Domingos examines the possibility of creating a universal learning machine capable of integrating all other algorithms. The book addresses the implications of such an algorithm for various fields ranging from social networks to warfare and sheds light on its consequences for society.

After spending two years as an assistant professor at IST, he joined the University of Washington as an assistant professor of Computer Science and Engineering in 1999 and became a full professor in 2012.^[12] In 2018, he started a machine learning research group at the hedge fund D. E. Shaw & Co., but left in 2019.^[13,2] He co-founded the International Machine Learning Society. As of 2018, he was on the editorial board of the Machine Learning journal.^[14]

Domingos has observed that an effective system built on learning machines can accomplish things that a million people do today, from the economy to cyber espionage, posing the challenge of a country that produces a thousand times as much knowledge as everyone else.^[3] When Chinese state leader Xi Jinping showed himself to be the owner of The Master Algorithm in his 2018 New Year's address, Domingos interpreted this as a sign of China's will to rise to the status of foremost world power through AI.^[4] In Europe, he sees too little interest in the subject and too much pessimism. His books have not yet been translated into German.^[3]

From 1992 to 1997, he held a Fulbright Scholarship, and he was later awarded a Sloan Fellowship in 2003. In 2010, he was elected an Association for the Advancement of Artificial Intelligence (AAAI) Fellow for significant contributions to the field of machine learning and to the unification of first-order logic and probability. In 2014, he received the ACM SIGKDD Innovation Award 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.

Pedro Domingos authored The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World, published in New York by Basic Books in 2015 (ISBN 978-0-465-06570-7). In September 2018, he published the article "Our Digital Doubles: AI will serve our species, not control it" in Scientific American (vol. 319, no. 3, pp. 88–93), where he argued that "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." He also authored 2040: A Silicon Valley Satire, published by BookBaby in 2024 (ISBN 979-8-350-96334-2).