Mathematics: data and modeling
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Continuous time stochastic processes,, Stylized models for financial markets, Discrete time models for asset pricing,
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management science, business analytics, sustainable mobility, optimization for logistics, optimization for human
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Analysis in Lie groups and subriemannian structures, surfaces in subriemannian setting, subelliptic equations,
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mathematical physics, statistical mechanics, disordered and complex systems, machine learning and artificial
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quantum information theory, quantum computing, quantum machine learning, quantum statistical mechanics
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Topological machine learning, Geometric deep learning, Natural pseudodistance, Shape comparison, Pattern recognition,
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Harmonic Analysis, Complex Analysis, Compressed Sensing Theory for MRI
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Ill-Posed Inverse Problems, Numerical Modeling, Deep Learning, Landslides
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numerical methods for non-linear, non-differentiable and non-convex optimization, inverse problems in imaging,
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Quantitative finance,, High frequency finance, Market microstructure, Financial networks, Systemic risk, Financial
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mathematical physics, statistical mechanics, disordered and complex systems, spin glasses, monomer- dimer models,
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Numerical Analysis, Numerical Linear Algebra, Matrix Equations
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Stochastic analysis, Stochastic (ordinary and partial) differential equations, Hypoelliptic equations,
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matrix equations, iterative methods for the solution of algebraic linear systems and for eigenvalue problems,
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Statistical Mechanics, Spin Glasses, Neural Networks, Random Graphs, Quantitative Finance, Statistical Inference,
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mathematical models of AD, Carnot groups, differential forms, compensated compactness, homogenization, statistical
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Parameter estimation algorithms, NMR data inversion, regularization methods, finite difference schemes, nonlinear
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