Andersen Ang

Dr Andersen Ang is a Lecturer at the University of Southampton, specializing in mathematical optimization, nonnegative matrix/tensor factorization, and machine learning applications. His research focuses on developing advanced algorithms for signal processing, convex optimization, and data analysis. He is actively supervising two PhD students in Computer Science and has published extensively in top-tier journals/conferences like IEEE Transactions on Signal Processing and SIAM Journal on Optimization.

Dr Ang's work spans theoretical algorithm development (e.g., MGProx multigrid optimization, sparse NMF) and practical applications in source separation, biomedical interfaces, and educational technology. His recent publications emphasize graph signal processing, convex relaxation techniques, and scalable optimization methods for high-dimensional data. He maintains an active Google Scholar profile and a personal research website at https://angms.science/.

While no specific awards were listed, his prolific publication record (over 25 articles since 2014) and focus on impactful optimization techniques demonstrate significant contributions to computational mathematics and machine learning communities. Current research includes inhomogeneous graph trend filtering and Riemannian optimization approaches for constrained problems.