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John Beieler Named Executive Director of UMD’s Applied Research Laboratory for Intelligence and Security

University of Maryland taps the U.S. Intelligence Community’s Chief AI Officer to lead its UARC


Media Relations

image ofARLIS building entrance

COLLEGE PARK, Md - Dr. John Beieler has been named the new Executive Director of the University of Maryland’s Applied Research Laboratory for Intelligence and Security (ARLIS), one of 15 designated Department of Defense University Affiliated Research Centers (UARCs) in the U.S., and the only UARC dedicated to intelligence and national security.

Beieler has served as the Director of Science and Technology (S&T) within the Office of the Director of National Intelligence (ODNI) since July 2019, and was later elevated to Assistant Director of National Intelligence in June 2023. In this role, he served as the science advisor to the Director of National Intelligence and provided strategic guidance for the S&T functions of the Intelligence Community (IC), leading a variety of special efforts, including artificial intelligence (AI) and machine learning (ML) activities, projects related to high-performance computing and microelectronics, and innovation efforts focused on the procurement of novel technologies. In this capacity, he also served as the IC’s first Chief AI Officer, coordinating AI-related strategy and activities across the 18 IC organizations.

“We are extremely fortunate that John’s leadership and experience in the intelligence community is being brought to ARLIS,” said UMD President Darryll J. Pines. “His expertise in artificial intelligence and deep knowledge of evolving national security technology needs will be critical assets in helping ARLIS reach new levels of achievement in addressing the nation’s most important research challenges.”

Prior to his work at ODNI, Beieler was a Program Manager at the Intelligence Advanced Research Projects Activity (IARPA), where he developed and managed AI/ML research and development (R&D) programs in support of IC goals. Previously, he was a research scientist at the Johns Hopkins University Human Language Technology Center of Excellence, engaging in novel research in the field of machine learning, and also served as a data scientist within industry supporting Department of Defense R&D programs. He earned his Ph.D. and M.A. in Political Science at Penn State University, and B.A. in Political Science at Louisiana State University.

Beieler will begin his new role as Executive Director of ARLIS on September 23, 2024. Dr. Craig Lawrence, who has served as Interim Executive Director of ARLIS since August 2023, will serve as Deputy Executive Director.

”We are excited to see John Beieler bring his diverse experience in government, industry, and academia to help advance ARLIS’s mission of tackling complex national security problems,” said Acting Under Secretary of Defense for Intelligence and Security (USD(I&S)) Milancy Harris.

Established in 2018 and located in UMD’s Discovery District, ARLIS serves as a trusted advisor to the federal government, tackling complex problems related to intelligence and national security. Last month, the University of Maryland received a contract with a $500 million ceiling from the Department of Defense to support ARLIS and its human-centered intelligence and security research, the largest research contract in UMD’s history.

John Beieler
John Beieler


The Applied Research Laboratory for Intelligence and Security (ARLIS), based at the University of Maryland, was established in 2018 under the sponsorship of the U.S. Office of the Under Secretary of Defense for Intelligence and Security, intended as a long-term strategic asset for research and development in artificial intelligence, information engineering, and human systems. ARLIS combines expertise, research, and development in human behavior, social science, culture, and language with emerging and advanced technologies. This enables development of problem-focused, evidence-based solutions for security and intelligence challenges that can be operationalized quickly and at scale. Learn more at

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