Ion Matei

Sr Manager/Associate Director, Intelligent Systems Lab, Future Concepts Division

Ion Matei is a Principal Scientist and Research Manager known for his expertise in machine learning, optimization, and modeling for system design and resilient (autonomous) systems. Ion Matei has served as (co-)PI and technical lead on numerous government (DARPA A2P, PAI, AIRA, SPiNN, ReMATH, NOMARS) and industry (Hitachi, ESI, Japan Rail East, Mitsubishi) funded projects that use machine learning and physics-based modeling to solve fundamental research and real-world problems. Earlier in his career, Dr. Matei focused on designing and analyzing distributed algorithms for optimization, estimation, and control, which are foundational to various autonomous systems applications. These applications include UAV formation control, sensor networks for tracking, and power grid monitoring.

Before joining SRI, Ion Matei worked as a research scientist at the Institute for Systems Research at the University of Maryland, College Park, and was a guest researcher at the National Institute of Standards and Technology in Gaithersburg, MD. As part of the Systems Engineering group at NIST, Ion contributed to the development of standards for modeling cyber-physical systems, with emphasis on the representation of hybrid dynamical systems.

Dr. Matei holds a Bachelor’s and Master’s degree in Electrical Engineering from the Politehnica University of Bucharest, Romania, earned in 2002 and 2003, respectively. He further pursued his education at the University of Maryland, College Park, where he completed a second Master’s and a Ph.D. in Electrical Engineering in 2009 and 2010, respectively. Ion has made significant contributions to the academic community with over 90 peer-reviewed articles and papers published in leading journals and conferences focused on control, optimization, and signal processing. Additionally, he has been granted 20 patents for his innovative work.

Expertise

  • Optimization and machine learning
  • Physics-based modeling
  • Control
  • Diagnosis and Prognostics

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