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Larisa Beilina is a Professor at the University of Gothenburg, specializing in Coefficient Inverse Problems (CIPs) and their applications in various fields such as mathematical modeling and image reconstruction. Her research focuses on CIPs utilizing adaptive finite element methods and globally convergent numerical techniques. She developed a globally convergent method during her PhD thesis in 2003, in collaboration with Professor M.V. Klibanov at the University of North Carolina at Charlotte. Her works have significantly contributed to the field, including verification with blind experimental data and applications in radar imaging. Beilina’s research includes domains such as microwave thermometry, electro-optical applications, and innovative approaches to drug efficacy determination for HIV infections. Her numerous publications demonstrate her extensive expertise, with designs for imaging techniques and adaptive algorithms aimed at enhancing reconstruction stability and accuracy. She has presented her findings at various international conferences and has been involved in collaborative projects that leverage her in-depth knowledge of applied mathematics and numerical analysis.
Chalmers University of Technology • Gothenburg, Sweden
Research in Coefficient Inverse Problems and Numerical Methods.
Administered by the Department of Political Science; focus on International Administration and Global Governance (IAGG).