Rate My Professor James Saunderson

Saunderson’s research focuses on mathematical optimization, particularly convex optimization and semidefinite programming, exploring algebraic and geometric structures to develop efficient algorithms with performance guarantees. Applications include signal processing, machine learning, power systems, quantum information theory, and quantum metrology. He supervises PhD students such as Nimita Shinde (2018–2022), Kerry He (2022–2025), Hin Long (Brian) Ng (2022–present), Shuvayan Banerjee (2021–present), and Sulaiman Al Hasani. He teaches courses including ECE2111 Signals and Systems, ECE3093 Optimisation and Numerical Methods for Engineers, and ECE4132 Control System Design. Saunderson serves as Associate Editor for the SIAM Journal on Applied Algebra and Geometry since 2022 and received the SIAM Activity Group on Optimization Best Paper Prize in 2020. His publications have accumulated over 1,400 citations with an h-index of 21. Key works include “Efficient computation of the quantum rate-distortion function” (Quantum, 2024), “A Bregman Proximal Perspective on Classical and Quantum Blahut-Arimoto Algorithms” (IEEE Transactions on Information Theory, 2024), “Spectral Polyhedra” (Forum of Mathematics, Sigma, 2025), and “Interior Point Methods for Structured Quantum Relative Entropy Optimization Problems” (Mathematical Programming Computation, 2025), all with co-authors Kerry He and Hamza Fawzi where noted.