Research

Active Reseach     -     Publications     -     Google Scholar Profile

Active Research

Selected Works in Progress

“Comparison between multi-target tracking algorithms in high clutter environments with probabilistic data association techniques”

“Automatic literature review toolkit for evaluating societal and economical benefit”

“Fixed lag particle filters in Stone Soup”

titles of the works will change when submitted

Publications

Peer-Reviewed Publications

• “A Survey for Deep Reinforcement Learning Based Network Intrusion Detection”,
  Lead by PhD student Wanrong Yang of the Distributed Algorithm CDT and with Yihang Zhou and Dominik Wojtczak.
  Published in Applied AI Letters, 2026, Suggested citation;
  Keywords: Intrusion Detection, Deep Reinforcement Learning, Cyber-Security, Cyber-Physical Systems.

• “Stone Soup Goes NUTS: Adding Proposals and the No-U-Turn Sampler to Stone Soup”,
  with Lyudmil Vladimirov, Alessandro Varsi, Paul Horrdige and Simon Maskell.
  2025 28th International Conference on Information Fusion (FUSION), Rio de Janeiro, Brazil;
  Suggested citation, Code repo;
  Keywords: Target tracking, Particle Filtering, Bayesian methods.

• “Accounting for the Impact of Real-World Data and Costs in Autonomous Cyber Defence“
  Lead by PhD Student Adam Neal of Distributed Algorithm CDT, with Peter L. Green, Simon Maskell, Chris Lear and Nick Hare from Aleph Insights.
  2025 IEEE International Conference on Cyber Security and Resilience (CSR), Chania, Crete, Greece;
  Suggested citation; Best paper award;
  Keywords: Network security, Cyber-Physical Systems, Autonomous Cyber defence.

• “Defending the unknown: Exploring reinforcement learning agents’ deployment in realistic, unseen networks”
  with Simon Maskell and Jack D.
  Proceedings of Conference of Applied Machine Learning in Information Security (CAMLIS), Arlington, Virginia, USA, (2023);
  Suggested citation, Poster; Code Repo;
  Keywords: Network Security, Machine Learning, Network Simulations, Reinforcement Learning.

• “The BAHAMAS project: evaluating the accuracy of the halo model in predicting the non-linear matter power spectrum”
  with Ian G. McCarthy, Juliana Kwan, Jaime Salcido, Andreea Font and Sam Stafford.
  This paper is part of BAHAMAS ERC project. Published in MNRAS, 2021, suggested citation.
  Keywords: Dark Matter, Large-Scale Structure Cosmology, Baryonic Feedback, Analytical Models, Halo Model.

Academic involvement

Academic journal referee:

• IEEE Transactions on Aerospace and Electronic Systems, TAES;
• IEEE Signal processing Letters, IEEE-SPL;
  

Conference publication referee:

• IEEE International Conference on Information Fusion 2026, FUSION.

PhD Thesis

“Exploring the accuracy of analytic methods in predicting the evolution of large-scale structure”
Supervisor Ian G. McCarthy, 2022, LJMU