Daniel Adams

Daniel Adams

Maths and Stats Developer

London South Bank University

Biography

I am a Maths and Stats Developer working at London South Bank University. In my current role I develop maths and stats learning recources and teach mathematics at the university. My research interests have been in the fields of real and stochastic analysis. A particular focus has been the variational analysis of interacting particle systems, through their associated large deviation principles and gradient flow structures. Recently, I have expanded my expertise to include advanced Machine Learning techniques, such as Reinforcement Learning, Recurrent Neural Networks. I am also interested in Blockchain Technologies and am eager to learn more about them. Outside of work I enjoy rock climbing, cycling and boardgames!

Interests
  • Interacting Particle Systems
  • Large Deviations
  • Optimal Transport and JKO schemes
  • Machine Learning and Algorithmic Trading
Education
  • PhD in Mathematics, 2022

    University of Edinburgh

  • MSc in Mathematics, 2018

    University of Bristol

  • BSc in Mathematics, 2017

    University of Sussex

Recent Publications

(2022). Entropic regularisation of non-gradient systems. SIAM Journal on Mathematical Analysis.

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(2022). Operator-splitting schemes for degenerate, non-local, conservative-dissipative systems. Discrete and Continuous Dynamical Systems-Series A.

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(2022). Large Deviations and Exit-times for reflected McKean–Vlasov equations with self-stabilising terms and superlinear drifts. Stochastic Processes and their Applications.

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