The Selected Works Of Roderick S C Wong - Volume 4

This book represents a distinguished collection of research papers authored by the esteemed Professor Roderick Wong, a globally recognized mathematician, and a pioneer in the field of applied mathematics. His brilliant academic journey has spanned across different continents, including North America and Hong Kong.

Throughout his illustrious career, Professor Wong has consistently made profound and impactful contributions that have significantly advanced the domain of applied mathematics. His exceptional achievements have been widely acknowledged and celebrated through a multitude of prestigious awards and honors. Notably, he was bestowed with the esteemed title of Fellow of the Royal Society of Canada in 1993, recognized as a foreign member of the Academy of Sciences of Turin (Italy) in 2001, and honored with the Chevalier dans l'Ordre National de la Légion d'Honneur by the French government in 2004. Additionally, Professor Wong's remarkable accomplishments have led to his membership in the European Academy of Sciences in 2007. These accolades serve as a testament to his exemplary contributions to the field.

The book, showcasing Professor Wong's research papers, not only reflects his immense expertise and profound insights but also serves as a tribute to his remarkable achievements.

It is an invaluable resource for researchers and graduate students seeking to explore the frontiers of applied analysis, providing them with a rare opportunity to explore the intellectual legacy of a true luminary in the field.

Dan Dai is an Associate Professor at the Department of Mathematics, City University of Hong Kong, Hong Kong. His research interests include asymptotic analysis, orthogonal polynomials and special functions, integrable systems, random matrix theory, and Riemann–Hilbert problems.

Ding-Xuan Zhou is a Professor and Head at the School of Mathematics and Statistics, The University of Sydney, Australia. His research interests include theory of deep learning, neural networks, statistical learning and applications, approximation theory, data science, and wavelets.