Andrew William Moore is a British-American computer scientist whose research spans machine learning, Artificial intelligence, robotics, and large-scale statistical data mining. He is the co-founder and CEO of Lovelace AI, a Pittsburgh-based technology company. Moore previously served as Dean of the Carnegie Mellon School of Computer Science from 2014 to 2018 and held senior roles at Google, including leading Google Cloud AI. In 2023, he was appointed the first adviser for artificial intelligence, robotics, and cloud computing to the United States Central Command.
Early life and education
Moore grew up in Bournemouth, on the south coast of England. During his childhood, he developed an early interest in computing by writing video games for 6502-based personal computers, including the Tangerine Microtan 65.
Moore studied mathematics and computer science at the University of Cambridge, where he subsequently completed his doctorate. His 1991 thesis, titled Efficient Memory-based Learning for Robot Control, was supervised by William F. Clocksin and examined machine learning techniques applied to robot control.
Following his doctorate, Moore held a postdoctoral position at the Massachusetts Institute of Technology in Chris Atkeson's Robot Learning group, where his work included research on robot juggling, manipulation, and the application of non-parametric regression to tasks such as pool playing. Before beginning his graduate studies, Moore spent a year as a researcher at Hewlett-Packard Research Labs in Bristol, England.
Career at Carnegie Mellon University (1993-2006)
Moore joined the Carnegie Mellon University faculty in 1993 as an assistant professor, working on machine learning, reinforcement learning, manufacturing, and non-parametric regression. He received tenure in 2000 and held appointments in the Computer Science Department, the Machine Learning Department, and the Robotics Institute.
He founded the Auton Laboratory, which focused on large-scale statistical methods, and co-founded a consultancy applying statistical data mining to manufacturing problems. He left Carnegie Mellon in 2006 to join Google.
Google (2006-2014)
Moore joined Google in 2006 as the founding director of its Pittsburgh engineering office, sited on the Carnegie Mellon campus, which grew to employ hundreds of people. In October 2011, while continuing to lead the Pittsburgh office, he was named vice president of engineering for Google Commerce. He left in August 2014 to return to Carnegie Mellon.
Dean of Carnegie Mellon School of Computer Science (2014-2018)
Moore was appointed Dean of the Carnegie Mellon School of Computer Science in April 2014, succeeding Randal Bryant, who had held the role since 2004. He took up the position in August of that year.
During his tenure, new undergraduate degrees were introduced in computational biology and artificial intelligence, and outreach programs were established for K-12 students and underrepresented minorities in computing. In 2017, Moore established the CMU AI initiative, which drew together more than 200 faculty members from across the university to work on Machine learning, robotics, natural language processing, and the societal implications of AI.
Moore stepped down as dean in August 2018, with his departure effective at the end of the year. CMU President Farnam Jahanian noted his contributions to the school's engagement with technology's societal implications and to Pittsburgh's standing as a center for computing research.
Google Cloud AI (2018-2023)
In September 2018, Google announced that Moore would lead Google Cloud AI, succeeding Fei-Fei Li, who returned to academia. He began in an advisory capacity before taking on the full-time role in January 2019. He held the position until 2023.
Lovelace AI (2023-present)
Moore co-founded Lovelace AI in 2023 and serves as its CEO. The company, based in Pittsburgh's Bakery Square neighborhood, develops AI systems for high-stakes analytical work at the intersection of national security, financial services, defense, and disaster response. In May 2025, the company closed a seed round of $16.2 million led by RRE Ventures.
Government and advisory work
In April 2023, Moore was appointed the first adviser for artificial intelligence, robotics, and cloud computing to the United States Central Command. In this role, Moore assisted CENTCOM on the adoption of AI, data collection and structuring, computer algorithms, and network-related efforts.
In December 2023, Moore was appointed to the Dropbox Board of Directors. Dropbox cited his expertise in AI, machine learning, and robotics, noting that his experience building AI-powered products would offer perspective as the company invested in AI across its product portfolio and through Dropbox Ventures.
Research contributions
Moore's research has focused on statistical machine learning and the application of computational statistics to large-scale data, emphasizing efficient algorithms capable of handling massive datasets. His work applies statistical methods and mathematical formulations to large volumes of data from diverse sources, including web searches, astronomy, and medical records, enabling the identification of subtle patterns and the derivation of actionable insights.
A key aspect of Moore's contributions lies in developing scalable techniques for statistical data mining and computational statistics, particularly through the founding of the Auton Lab at Carnegie Mellon University in 1993. The lab has pioneered methods for performing large-scale statistical operations efficiently, often achieving improvements over prior state-of-the-art performance by several orders of magnitude. These advances have supported applications in areas such as Bayesian networks, data mining, medical informatics, and social network analysis.
Moore has advanced non-parametric regression and related techniques, including kernel methods and locally weighted learning, which provide flexible modeling without rigid parametric assumptions. His research also encompasses density estimation, Gaussian mixture models, and probabilistic frameworks for large-scale inference.
To disseminate knowledge in these fields, Moore created extensive online tutorials covering foundational and advanced topics in statistical machine learning. These include probability and density estimation, Bayesian networks (with coverage of inference, structure learning, and naive Bayes classifiers), non-parametric methods such as instance-based learning, and efficient algorithms for tasks like clustering and regression. These resources have been widely accessed and used.
Through his roles at Carnegie Mellon, Google, and Lovelace AI, Moore has been a major figure in the practical application of AI and machine learning. His work has bridged academic research and industrial deployment, with impacts in both foundational algorithm design and real-world systems serving large user bases. His leadership in launching university-wide AI initiatives and advising on defense applications has shaped the integration of AI into both civilian and military contexts. As of 2025, Moore continues to lead Lovelace AI and remains an influential voice in the field.