Hamza Fawzi

Hamza Fawzi is a Professor in the Department of Applied Mathematics and Theoretical Physics (DAMTP) at the University of Cambridge, where he leads a research group focused on mathematical optimization with applications in quantum theory. His work bridges theoretical mathematics and practical computational methods for quantum information processing.

Professor Fawzi received his PhD in 2016 from MIT under the supervision of Pablo Parrilo. His research interests span mathematical optimization, quantum information theory, convex optimization, quantum many-body systems, and semidefinite programming. He has developed significant theoretical frameworks and practical algorithms for problems in quantum theory, including the design of optimization algorithms specifically tailored for quantum information applications.

His recent publications demonstrate a strong focus on quantum information processing through the lens of optimization theory. The research trends show consistent advancement in developing certified algorithms for quantum Hamiltonian problems, quantum relative entropy optimization, and quantum conic programming. His work often involves applying convex optimization techniques to solve challenging problems in quantum information theory, with particular emphasis on developing reliable numerical methods and theoretical guarantees.

Professor Fawzi leads a research group with current members Ahmad Al-Sulami, Giorgio Facelli, Samuel O. Scalet, and Shengding Sun. Former group members include Kun Fang (now Assistant Professor at CUHK-Shenzhen) and Oisín Faust (now at Tower Research Capital). He has developed notable software tools including QICS (a convex optimization solver for quantum information theory) and CVXQUAD (a MATLAB-based package for quantum entropies and divergences).

He teaches advanced courses at Cambridge including Part II Numerical Analysis (Michaelmas 2023), Part IB Numerical Analysis (Lent 2020), and Part III Topics in Convex Optimization (Michaelmas 2019). His teaching covers fundamental numerical methods, optimization algorithms, and their applications in mathematical physics.