Bin Han

Bin Han is a Professor of Mathematics at the Department of Mathematical and Statistical Sciences, University of Alberta, Canada. He holds a PhD (1998), MSc (1994), and BSc (1991) in Mathematics from the University of Alberta, Chinese Academy of Sciences, and Fudan University, respectively.

Research Interests:

• Computational Mathematics: High-order finite difference methods, numerical solutions of PDEs (Helmholtz, elliptic interface, Burgers' equations), and Fourier/wavelet-based algorithms.
• Applied Harmonic Analysis: Framelets/wavelets with applications in image processing, data sciences, and deep learning, focusing on directional and quasi-tight properties.
• Wavelet Theory: Construction of wavelets on bounded intervals for boundary value problems, Gibbs phenomenon analysis, and stability of refinable functions.
• Computer Aided Geometric Design (CAGD): Subdivision schemes, spline approximation, and isogemetric analysis.

Article Trends: His recent work (2021-2022) emphasizes high-order finite difference methods for Helmholtz and interface problems, directional tensor product complex tight framelets for image processing, and quasi-tight framelets with balancing orders for robustness and sparsity.

Scientific Awards:

• NSERC Postdoctoral Fellowship (1999-2000)

Advising & Grants: He has supervised PhD students Qiwei Feng, Michelle Michelle, Ran Lu, and Chenzhe Diao. His research is supported by NSERC, Westgrid, Compute Canada, and MITACS.