Feng Dai

Feng Dai is a Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta. His research focuses on harmonic analysis, approximation theory, and related areas such as orthogonal expansions, cubature formulas, and spherical harmonics. He serves as an editor for the Journal of Approximation Theory.

His research interests include harmonic analysis, approximation theory, orthogonal expansions, cubature formulas on spheres and other domains, N-widths, nonlinear approximation, weighted polynomial inequalities, moduli of smoothness, spherical harmonics, wavelet frames, and radial basis functions. He has authored books on approximation theory and harmonic analysis on spheres and balls, and analysis on h-harmonics and Dunkl transforms.

Dr. Dai has secured multiple NSERC Research Grants of Canada, spanning from 2005 to 2020, and a University of Alberta Startup Fund. His work emphasizes theoretical advancements with applications in numerical analysis and functional analysis.

His recent publications explore topics such as discretization of integral norms, sampling recovery, and inequalities in function spaces. His contributions bridge harmonic analysis and approximation theory, addressing both foundational and applied mathematical challenges.