Magnetic Resonance
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AI & ML interests
ML Methods for Magnetic Resonance Spectroscopy and Imaging: NMR, EPR/ESR, spin physics, quantum sensing, noisy magnetic resonance reconstruction, spectral deconvolution, spin-Hamiltonian inference, quantitative relaxation and diffusion estimation, pulse-sequence optimization, optimal control, multidimensional NMR reconstruction, automated peak assignment, spin-dynamics surrogate models, field inhomogeneity correction, hyperpolarization optimization, quantum-sensing spectroscopy, uncertainty quantification, and autonomous magnetic-resonance experiments etc
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