معرفی
Felix Herrmann is a Professor at the Georgia Institute of Technology, holding a joint appointment between the Schools of Earth & Atmospheric Sciences, Computational Science & Engineering, and Electrical & Computer Engineering within the College of Computing. He leads the Seismic Laboratory for Imaging and Modeling (SLIM) and co-directs the Center for Machine Learning for Seismic (ML4Seismic). His research focuses on computational imaging, inverse problems, and machine learning applications in geophysics, particularly in seismic and medical imaging. Herrmann has pioneered innovations in compressive sensing for time-lapse seismic data acquisition, earning the SEG Reginald Fessenden Award in 2020. His work emphasizes Bayesian inference, uncertainty quantification, and scalable computational methods for subsurface monitoring, including carbon sequestration and reservoir characterization.
Education: Ph.D. in Engineering Physics (Delft University of Technology, 1997), followed by postdoctoral roles at Stanford University and MIT before joining the University of British Columbia (2002). He transitioned to Georgia Tech in 2017 as a Georgia Research Alliance Eminent Scholar in Energy.
Research Interests: Herrmann’s cross-disciplinary program integrates randomized linear algebra, PDE-constrained optimization, and high-performance computing. Key areas include digital twin technologies for subsurface monitoring, generative AI for geostatistical modeling, and scalable inversion algorithms (e.g., wavefield reconstruction inversion). His methodologies aim to reduce costs and improve reliability in seismic imaging and carbon storage monitoring.
Scientific Contributions: Over 150+ peer-reviewed articles, including seminal work on compressive sensing in seismic acquisition and Bayesian experimental design. His software contributions include InvertibleNetworks.jl and Devito, advancing computational geophysics.
Labs & Collaborations: Directs SLIM, fostering industry partnerships through ML4Seismic to develop AI-driven seismic imaging tools. Active in cloud-based scalable workflows and event-driven seismic imaging systems.
