I am an Associate Professor at the Department of Automatic Control. My main research interests lie within optimization and its wide range of applications.

Selected Publications

M. Upadhyaya, S. Banert, A. B. Taylor, and P. Giselsson, Automated tight Lyapunov analysis for first-order methods. Submitted. 2023.

M. Fält and P. Giselsson, Generalized Alternating Projections on Manifolds and Convex Sets. Journal of Nonsmooth Analysis and Optimization, 4, 2023.

M. Morin, S. Banert, and P. Giselsson, Frugal Splitting Operators: Representation, Minimal Lifting and Convergence. Submitted. 2022.

M. Morin, S. Banert, and P. Giselsson, Nonlinear Forward-Backward Splitting with Momentum Correction. Submitted. 2021.

H. Sadeghi, S. Banert, and P. Giselsson, Forward--Backward Splitting with Deviations for Monotone Inclusions. Submitted. 2021.

P. Giselsson, Nonlinear Forward-Backward Splitting with Projection Correction. SIAM Journal on Optimization. Accepted for Publication. 2021.

E. Ryu, A. Taylor, C. Bergeling, and P. Giselsson,Operator Splitting Performance Estimation: Tight contraction factors and optimal parameter selection. SIAM Journal on Optimization, 30(3):2251 - 2271, 2020.

C. Grussler and P. Giselsson, Low-Rank Inducing Norms with Optimality Interpretations. SIAM Journal on Optimization, 28(4):3057 - 3078, 2018.

M. Fält and P. Giselsson,Optimal Convergence Rates for Generalized Alternating Projections. In Proceedings of  the 56th Conference on Decision and Control, Melbourne, Australia, 2017.

P. Giselsson, Tight Global Linear Convergence Rate Bounds for Douglas-Rachford Splitting. Journal of Fixed-Point Theory and Applications, 2017. doi:10.1007/s11784-017-0417-1.

C. Grussler, A. Rantzer, and P. Giselsson, Low-Rank Optimization with Convex Constraints. IEEE Transactions on Automatic Control, 63(11):4000 - 4007, 2018.

P. Giselsson and S. Boyd, Linear Convergence and Metric Selection in Douglas Rachford Splitting and ADMM. Transactions of Automatic Control. 62(2):532 - 544, 2017.

All Publications

Teaching

Master level course on Optimization for Learning. Held Sept.-Oct. every year.

PhD level course on Large-Scale Convex Optimization. Last held 2015.

Misc