Sharana Shivanand

Dr. Sharana Kumar Shivanand

About me

Hi, I am Sharana!

I am a Computational and Data scientist passionate about development of predictive algorithms based on data, simulation & AI.

Previously, I was a Postdoctoral Researcher in the Uncertainty Quantification (UQ) group at the Karlsruhe Institute of Technology (KIT), led by Prof. Sebastian Krumscheid. I was also a Postdoctoral Research Associate at The Alan Turing Institute, the UK's national institute for Data Science and AI, where I conducted research with the advisory of Prof. Adam Sobey, director of the Data-Centric Engineering programme. During this time, I was also a Visiting Research Fellow in the Department of Engineering at the University of Cambridge.

I received my Ph.D. (Dr.-Ing.) from the Technical University of Braunschweig, where I was advised by Prof. Hermann Matthies. I also obtained my M.Sc. in Computational Sciences in Engineering from the same institution.

Please click here to view my CV (last updated June 2026).

Email: sharana.shivanand@gmail.com

Research Interests

My interests lie in developing statistical and probabilistic techniques for physics and data-driven numerical predictions. My research is at the intersection of uncertainty quantification (UQ), computational physics, and data sciences, to address challenges in computational materials science, mechanics, and related areas of science and engineering.

In recent times, I have been developing multi-fidelity Bayesian statistical inference algorithms for the identification of latent parameters in compute-intensive simulations. I am also actively engaged in development of methods for random material tensor fields, multi-level Monte Carlo methods, data assimilation and probabilistic machine learning.

Publications

S. Shivanand and B. Rosić. Scale-invariant Monte Carlo and multilevel Monte Carlo estimation of mean and variance: An application to simulation of linear elastic bone tissue. Computers & Structures, 2026.
S. Shivanand, B. Rosić and H. G. Matthies. Stochastic modelling of elasticity tensor fields. Mathematics and Mechanics of Solids, 2025.
S. Shivanand. Covariance estimation using h-statistics in Monte Carlo and multilevel Monte Carlo methods. International Journal for Uncertainty Quantification, 2025.
S. Shivanand, B. Rosić and H. G. Matthies. Stochastic modelling of symmetric positive-definite material tensors. Journal of Computational Physics, 2024.
S. Shivanand and Data Study Group Team. Data Driven Modelling of Chemical Processes: Towards Flexible Production of Energy Carriers for a Net-Zero Society. Technical Report, The Alan Turing Institute, 2024.
S. Shivanand. Stochastic material modelling and multi-fidelity uncertainty quantification of macroscopic bone tissue. PhD thesis, 2022.
F. Fahrendorf, S. Shivanand, B. Rosić, M. S. Sarfaraz, T. Wu, L. De Lorenzis, and H. G. Matthies. Collocation methods and beyond in non-linear mechanics, Lecture Notes in Applied and Computational Mechanics, 2022.
B. Rosić, S. Shivanand, T. Hoang and H. G. Matthies. Iterative spectral identification of bone macroscopic properties described by a probability box. Proc. Appl. Math. Mech., 18: e201800404, 2018.

Latest News

[Jan 2026] Gave invited seminar talk at Dept. of Applied Mechanics and Biomedical Engineering, IIT Madras, Chennai, India
[Sept 2025] Gave invited seminar talk at TIFR-Centre for Applicable Mathematics, Bengaluru, India
[Sept 2025] Gave invited seminar talk at Indian Institute of Technology, Hyderabad, India
[Sept 2025] Organised minisymposia "MS 42 - Uncertainty Quantification for Materials & Mechanics" at ENUMATH, Sept 1-5 2025, Heidelberg, Germany
[Jan 2025] Featured in video documentation A week in the life of a Data Study Group by the Alan Turing Institute, London, United KIngdom