معرفی
Chrysoula Tsogka is a Professor in the Department of Applied Mathematics at the University of California, Merced (since 2019). Previously, she held academic positions at the University of Crete (2007-2019), including Professor (2014-2019) and Associate Professor (2007-2014). She also served as a Visiting Professor at Stanford University (2016-2019) and a Project Scientist at UC Merced (2017-2019). Her research focuses on numerical methods for wave propagation, inverse problems, and imaging in complex media, with applications in geophysics, radar, and structural health monitoring.
Education:
- Ph.D. in Applied Mathematics, University Paris IX (Dauphine), France (1999)
- M.S. in Applied Mathematics, University Paris IX, France (1996)
- B.Eng. in Chemical Engineering, National Technical University of Athens, Greece (1995)
Research Interests: Tsogka specializes in developing and analyzing numerical methods for direct and inverse wave propagation problems, including coherent interferometry, passive ambient noise correlation-based imaging, and sparse recovery techniques. Her work addresses challenges in imaging through complex and random media, such as turbulence and scattering effects, with applications in synthetic aperture radar (SAR), satellite imaging, and non-destructive evaluation of materials. She emphasizes robustness in imaging systems under environmental uncertainties.
Grants and Awards:
- ERC Starting Grant (2010-2015)
- SIGEST Paper Award (2009)
- Principal Investigator (PI) on Air Force Office of Scientific Research grants (e.g., FA9550-21-0196, $284K, 2021-2024)
Advising and Mentorship: Tsogka has supervised six Ph.D. students and advised numerous MSc and Ph.D. committees. Her current team includes a graduate student and four committee members. She has also mentored postdoctoral researchers and undergraduate students in her research groups.
Labs and Teams: As coordinator of the Imaging and Sensing SMaRT team at UC Merced, she leads a group of 6 faculty, 2 postdocs, and 12 graduate students. The team focuses on forward/inverse imaging problems, optimization, and uncertainty quantification, with weekly seminars alternating between the Optimization and Waves groups. They collaborate on data-driven methods for remote sensing and radar applications.
