Rosemary Renaut

Rosemary Renaut is a Professor and Associate Director for Faculty Development at the School of Mathematical and Statistical Sciences, Arizona State University. Her research focuses on computational algorithms for solving inverse problems in medical and geophysical applications, emphasizing regularization techniques and numerical linear algebra. She holds a Ph.D. in Applied Mathematics from the University of Cambridge (1985).

Education:

• Ph.D. in Applied Mathematics, University of Cambridge, UK (1985)

Research Interests: Dr. Renaut specializes in developing algorithms for solving ill-posed inverse problems, particularly in medical imaging (e.g., PET, MRI) and geophysics (e.g., gravity/magnetic data inversion). Her work addresses challenges like data noise, model ill-posedness, and parameter regularization. She has contributed to methods like total variation regularization, χ²-based parameter estimation, and iterative solvers (e.g., LSQR).

Articles Trends: Recent publications (2020–2025) emphasize large-scale inversion techniques, sparsity-driven reconstruction, and efficient regularization parameter estimation. Key applications include geophysical exploration (e.g., iron oxide deposits, kimberlites) and medical imaging (e.g., EEG source localization). Her work often combines numerical methods with domain-specific challenges, such as joint inversion of multimodal geophysical data.

Awards:

• SIAM Fellow (2022)
• Technische Universitaet Muenchen Ambassador (2013)
• J.T. Knight Prize in Mathematics (1982)

Grants & Service: Dr. Renaut has led numerous grants (e.g., NSF, DOD) on inverse problems and computational methods. She serves on editorial boards (BIT, SIAM News) and has held roles like Program Director at the NSF. Her service also includes mentoring junior faculty and advancing computational biosciences education.

Labs/Teams: Collaborates with interdisciplinary teams in geophysics (e.g., gravity/magnetic data inversion) and biomedical imaging (e.g., PET parametric imaging). Active in conferences like International Conference on Spectral and High Order Methods.