Imperial College London


Faculty of EngineeringDepartment of Computing

Professor of Applied Quantitative Analysis



+44 (0)20 7594 8331w.knottenbelt Website




E363ACE ExtensionSouth Kensington Campus





My broad area of research interest is the application of mathematical modelling techniques to real life systems. Specific areas of interest include, but are not limited to, modelling and optimisation in parallel queueing systems (especially split-merge and fork-join systems), modelling of storage systems, stochastic modelling of sport, stochastic modelling of healthcare systems, resource allocation and control in cloud-computing environments, numerical solution of (semi-)Markov models and specification techniques for SLA specification, compliance prediction and monitoring.



Stewart I, Ilie D, Zamyatin A, et al., 2018, Committing to Quantum Resistance: A Slow Defence for Bitcoin against a Fast Quantum Computing Attack., Iacr Cryptology Eprint Archive, Vol:2018, Pages:213-213


Zamyatin A, Stifter N, Judmayer A, et al., 2018, (Short Paper) A Wild Velvet Fork Appears! Inclusive Blockchain Protocol Changes in Practice., Pages:87-87

Mora SV, Knottenbelt WJ, 2017, Deep Learning for Domain-Specific Action Recognition in Tennis, 30th IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), IEEE, Pages:170-178, ISSN:2160-7508

Pesu T, Knottenbelt WJ, 2017, Optimising hidden stochastic PERT networks, Pages:133-136

Zamyatin A, Wolter K, Werner S, et al., 2017, Swimming with Fishes and Sharks: Beneath the Surface of Queue-based Ethereum Mining Pools, 25th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), IEEE COMPUTER SOC, Pages:99-109, ISSN:1526-7539

More Publications