Helping the NHS cut waiting lists
With East Suffolk and North Essex NHS Foundation Trust, we used machine learning to predict how long operations will take, so theatre lists can be planned more accurately.
Welcome to my website
I am a Reader in the School of Computer Science and Electronic Engineering at the University of Essex, and Faculty Dean (Postgraduate) for the Faculty of Science and Health. My research applies machine learning to finance and economics, and I am particularly interested in evolutionary algorithms and financial forecasting.
I lead a research group of ten PhD students. Eight more have completed their PhDs with me, six at Essex and two at Kent, my previous university.
Alongside my research, I lead industry and public-sector projects that apply machine learning to all kinds of business problems: around 30 since 2020, including 10 Knowledge Transfer Partnerships.
News
- Oct 2026New paper in Applied Soft Computing: Strongly-typed genetic programming with an active trading operator for algorithmic trading using fundamental, sentiment, and technical analysis.
- Sep 2026Sirui Zhu joined the research group as a PhD student.
- Sep 2026New paper in SPEAKABLE workshop at LREC 2026: On the Role of Encoder Depth: Pruning Whisper and LoRA Fine-Tuning in SLAM-ASR.
- Sep 2026New paper in IEEE Spoken Language Technology SLT 2026: CARD: Cross-component Audio Representation Distillation for Encoder-Free Audio Captioning.
- 2026New paper in Artificial Intelligence Review on machine learning for temperature forecasting in weather derivatives.
Research
All researchGenetic programming for trading
Trading strategies built from technical, fundamental and sentiment signals.
Directional changes
Event-based price data for spotting trend reversals and for trading.
Deep RL for high-frequency trading
Trading agents that account for their own position and for costs.
LLMs for finance
Financial filings, sentiment and trading strategies generated by LLMs.
Financial forecasting
Weather derivatives, real estate and company fundamentals.
Latest publications
All publicationsChristodoulaki, E., Kampouridis, M. (2026). Strongly-typed genetic programming with an active trading operator for algorithmic trading using fundamental, sentiment, and technical analysis. Applied Soft Computing, Elsevier.
Barnor, N., Kampouridis, M., Kanellopoulos, P. (2026). Machine Learning for Temperature Forecasting in Weather Derivatives. Artificial Intelligence Review, Springer.
Salman, O., Melissourgos, T., Kampouridis, M. (2026). A genetic algorithm for the optimization of multi-threshold trading strategies in the directional changes paradigm. Artificial Intelligence Review, Vol 59:2, Springer.
Industry and consultancy
All projectsDetecting lighthouse faults with machine learning
Since 2021 we have worked with the General Lighthouse Authorities on machine learning and machine vision that help spot faults in lighthouses and other aids to navigation early.
Organisations I have worked with
General Lighthouse Authorities, Trinity House, ESNEFT, Cooper Parry, Centerprise, Horus Security, IFE Global Logistics, Hivedome, Betascore, DOCME Technologies (now 360Me), Fingerpost Consulting, Footprint Digital, Iceni Projects, Otters.ai, PFE Express, R&B Switchgear Services, Shepherd Compello, Voono.
Working with me
Prospective PhD students
Machine learning for finance: trading, forecasting, directional changes and LLMs for financial text. See what to send me.
Industry and public sector
Knowledge Transfer Partnerships, consultancy projects and sponsored PhDs, on business and public-sector problems of any kind.
Media and events
Comment and talks on AI in finance, algorithmic trading and applied AI in industry.