Conference in Mathematics of Random Systems 2023
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| Conference in Mathematics of Random Systems 2023Monday 24 - Wednesday 26 April 2023International Centre for Mathematical Sciences (ICMS) Edinburgh |
This exciting event will feature talks from our final year CDT students showcasing the dynamic and diverse research being carried out in Oxford and Imperial by our students.
Each day will feature a different theme within the CDT with keynote talks from distinguished academics.
The programme will also include a Public Lecture.
Professor Des Higham, University of Edinburgh
Deep Learning: What Could Go Wrong?.
Tuesday 25 April 6-7pm. (Link to abstract)
Download Full Programme for the Conference
We may have a limited number of bursaries available for students working on related topics to support attendance. To apply for these please send your CV and letter of support from you supervisor to melanie.witt@maths.ox.ac.uk.
If you have any questions please contact melanie.witt@maths.ox.ac.uk.
Keynote Speakers:
Ellen Powell
Associate Professor, Durham University
Brownian excursions, conformal loop ensembles and critical Liouville quantum gravity
Ilya Chevyrev
Reader, University of Edinburgh
Stochastic analysis in constructive field theory
Eyal Neuman
Senior lecturer, Imperial College London
New Mathematical Challenges Arising from Propagator Models
Samuel Cohen
Associate Professor, University of Oxford
Neural Q-learning solutions to elliptic PDEs
Day 1, Monday 24 April
Analysis: Stochastic processes, SPDEs, Random Graphs
Keynote Talks: Ellen Powell (Durham), Ilya Chevyrev (Edinburgh)
Student talks
Julian Meier: Particle systems on the positive half-line with boundary interactions
Benedikt Petko: Coarse curvature of weighted Riemannian manifolds with application to random geometric graphs
Julian Sieber: On the (non-)stationary density of fractional SDEs
Harprit Singh: Stochastic Partial Differential Equations (SPDEs) within the framework of Regularity Structures
Zheneng Xie: Directed random graphs and queues
Day 2, Tuesday 25 April
Modelling: Stochastic and data driven finance, mathematical biology
Keynote Talk: Eyal Neuman (Imperial College London)
Public Lecture: Professor Des Higham, University of Edinburgh
Deep Learning: What Could Go Wrong?.
Student Talks
Lancelot Da Costa: From interacting stochastic dynamics to models of cognition and decision-making
Felix Prenzel: Simulation of limit order books
Alain Rossier: Asymptotic analysis of deep learning algorithms
Yihuang Zhang: Random vortex methods for the Navier-Stokes equation
Zan Zuric: Robust option pricing with neural SDEs
Day 3, Wednesday 26 April
Algorithms: Machine learning, stochastic simulation, optimal control
Keynote Talk: Sam Cohen (Oxford)
Student Talks
Jonathan Tam: Stochastic optimal control constrained by costly observations