Dr Sharana Shivanand

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sharana

Position

Research Associate

Partner Institution

University of Cambridge
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Research areas

Numerical (Algorithms) Probability Simulation Modelling (Statistical methods & theory) Monte Carlo methods Uncertainty quantification Stochastic optimisation Dynamical systems & differential equations Ensemble (Mathematical modelling) Deterministic (Mathematical modelling)

Bio

Sharana (he/him) is a Postdoctoral Research Associate in AI for science and government, also aligned with the data-centric engineering programme at The Alan Turing Institute. He is also a Visiting Research Fellow in the Department of Engineering at the University of Cambridge. He received his PhD in Applied Mathematics, and his research focused on the stochastic modelling of random materials (such as anisotropic bone tissue) characterised by symmetric and positive definite tensors, and the development of scale-invariant multilevel Monte Carlo estimators. He also holds an MSc in Computational Sciences in Engineering with a major in mathematics and computer science.

Research interests

Sharana is broadly interested in developing probabilistic and statistical methodologies at the intersection of physics and data to solve challenging science and engineering problems. His areas of interest in research include stochastic material modelling, multi-fidelity uncertainty quantification, physics-augmented machine learning, surrogate modelling, and Bayesian inference/data assimilation.

He is currently part of the Digital Twins: Complex Systems Engineering initiative conducting collaborative research with the University of Cambridge to develop uncertainty quantification procedures for system-level digital twins (grey-box methods) for infrastructure.

Turing Research