Imperial College London

Dr Paul A. Bilokon

Faculty of EngineeringDepartment of Computing

Lecturer in Mathematics for Computer Science
 
 
 
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Contact

 

+44 (0)20 7594 8241paul.bilokon01 Website CV

 
 
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Location

 

Huxley BuildingSouth Kensington Campus

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Summary

 

Overview

Mathematical Logic


  • Foundations of mathematics
  • Domain theory
  • Computability theory

Publications


  • Paul Bilokon, Abbas Edalat. A domain-theoretic approach to Brownian motion and general continuous stochastic processes. CSL-LICS '14 Proceedings of the Joint Meeting of the Twenty-Third EACSL Annual Conference on Computer Science Logic (CSL) and the Twenty-Ninth Annual ACM/IEEE Symposium on Logic in Computer Science (LICS), 2014.
  • Paul Bilokon, Abbas Edalat. A domain-theoretic approach to Brownian motion and general continuous stochastic processes. Theoretical Computer Science, 2017, 691, pp. 10-26.

Probability theory


  • Frequentist and Bayesian methods
  • Stochastic filtering
  • Markov chain Monte Carlo methods

Publications


  • Paul Bilokon, James Gwinnutt, and Daniel Jones. Matthias Ehrhardt, Michael Guenther, and Jan ter Maten (Eds.). STRIKE - Novel Methods in Computational Finance. Stochastic Filtering Methods in Electronic Trading. Springer-Verlag, 2017.

Machine Learning


  • Neural networks
  • Reinforcement learning
  • Applications to finance
  • Applications to drug discovery

Publications


  • Matthew Dixon, Igor Halperin, and Paul Bilokon. Machine Learning in Finance: From Theory to Practice. Springer, 2020.

Finance


  • Foreign exchange spot and derivatives
  • Credit cash and derivatives
  • Interest rates
  • Risk analysis: VaR and related risk measures
  • Prime brokerage

Publications


  • Matthew Dixon, Igor Halperin, and Paul Bilokon. Machine Learning in Finance: From Theory to Practice. Springer, 2020.

Algorithmic trading


  • Electronic market making
  • Automation of trading
  • Electronic trading platforms

Publications


  • Jan Novotny, Paul Bilokon, Aris Galiotos, and Frederic Deleze. Machine Learning and Big Data with kdb /q. Wiley, 2019.

High-frequency Trading


  • High-frequency trading strategies
  • Low latency programming
  • Time series databases: kdb /q

Publications


  • Jan Novotny, Paul Bilokon, Aris Galiotos, and Frederic Deleze. Machine Learning and Big Data with kdb /q. Wiley, 2019.

Scientific Computing


  • Python, C, C , Java
  • High-performance computing
  • Quantum computing