Simon Olofsson


Simon Olofsson
Marie Curie Early Stage Researcher
Department of Computing
Imperial College London

Supervisors: Dr. Ruth Misener and Dr. Marc Deisenroth

About Me

I am an Early Stage Researcher in the Computational Optimisation Group. My funding comes from a Horizon 2020 Marie Skłodowska-Curie Action grant to the ModLife ITN.



My research focuses on using Gaussian processes for hybridising analytical and data-driven approaches for optimisation, with applications in process engineering.

Papers, publications and conference proceedings


S. Olofsson and R. Misener. GPdoemd: a python package for design of experiments for model discrimination. arXiv pre-print 1810.02561, 2018. Link

S. Olofsson and M. Mehrian and R. Calandra and L. Geris and M. P. Deisenroth and R. Misener. Bayesian Multi-Objective Optimisation with Mixed Analytical and Black-Box Functions: Application to Tissue Engineering. IEEE Transactions on Biomedical Engineering. Accepted July 2018. Early access. Link

S. Olofsson, M. P. Deisenroth, and R. Misener. Design of experiments for model discrimination hybridising analytical and data-driven approaches. In ICML ’18: Proceedings of the International Conference on Machine Learning, Stockholm, Sweden, PMLR 80, 2018. Link

S. Olofsson, M. P. Deisenroth, and R. Misener. Design of experiments for model discrimination using Gaussian process surrogate models. Computer-Aided Chemical Engineering, 44:847-852, 2018. Link

M. Mehrian and Y. Guyot and I. Papantoniou and S. Olofsson and M. Sonnaert and R. Misener and L. Geris. Maximizing neotissue growth kinetics in a perfusion bioreactor: An in silico strategy using model reduction and Bayesian optimization. Biotechnology and Bioengineering, 115(3):617-629, 2018. Link

S. Olofsson, M. Mehrian, L. Geris, R. Calandra, M. P. Deisenroth and R. Misener. Bayesian multi-objective optimisation of neotissue growth in a perfusion bioreactor set-up. Computer-Aided Chemical Engineering, 40:2155–2160, 2017. Link

S. Olofsson. Probabilistic Feature Learning using Gaussian Process Auto-Encoders. Master's thesis, Uppsala University, 2016. Link

J. M. Alonso, A. Nordhamn, S. Olofsson, and T. Voigt. Bounds on the lifetime of wireless sensor networks with lossy links and directional antennas. In J.D. Matyjas, F. Hu and S. Kumar, editors, Wireless Network Performance Enhancement via Directional Antennas: Models, Protocols, and Systems, chapter 16, pages 329 - 361. CRC Press, Boca Raton, FL, USA, December 2015. ISBN 978-1-4987-0753-4. Link