Jacek Gondzio

Jacek Gondzio is a Professor in the School of Mathematics at the University of Edinburgh. He received his M.Eng. in Electronics (1983) and PhD in Automatic Control and Robotics (1989) from Warsaw University of Technology. His career includes positions at the Polish Academy of Sciences (1989–1993), University of Geneva (1993–1998), and the University of Edinburgh since 1998, where he progressed from Lecturer to Professor.

Research Interests: Gondzio's work spans large-scale optimization techniques, including interior point methods, sparse matrix computations, parallel algorithms, and applications in finance and engineering. Key focus areas include:

• Development of efficient solvers (HOPDM, OOPS) for linear/quadratic/nonlinear programming
• Matrix-free methods and preconditioning for massive-scale problems
• Applications in quantum information, tomography, structural design, and financial planning

Publication Trends: His recent articles emphasize scalable algorithms for optimization, including proximal methods for semidefinite programming, interior-point innovations, and applications in medical imaging and transport. Work frequently integrates regularization, decomposition techniques, and structure-exploiting linear algebra.

Awards:

• EUROPT Fellow (2019) for contributions to continuous optimization

Grants & Advising: Current projects include EPSRC-funded work on building structure optimization (EP/N019652/1), Google-funded LP solvers, and risk modeling with Standard Life Investments. He has supervised 16+ PhD students on topics ranging from interior point methods to machine learning optimization. Software includes HOPDM, PDCGM, and the parallel solver OOPS.

Leadership: Organizes workshops on optimization (e.g., COA, Advances in Preconditioners series) and serves on editorial boards for Mathematical Programming Computation, Computational Optimization and Applications, and other leading journals.