Dhruva V. Raman

March 3, 2016


Dhruva is a DPhil (i.e. PhD) student in the Control Group at the University of Oxford, under the supervision of Antonis Papachristodoulou and James Anderson. He completed an MMath Degree at the University of Warwick (2012) graduating with first class honours. From 2012-present, he has been on the Systems Biology Doctoral Training Centre, University of Oxford, fully funded through an EPSRC scholarship. This involved a year of taught courses in the broad field of Systems Biology, before he began his DPhil proper in October 2013.


The local sensitivity of model predictions to parameter perturbation can be described as ‘sloppy’ when it is highly anisotropic with respect to perturbation direction. We extend the existing quantification of sloppiness to account for non-local perturbation, and find that the degree of sloppiness can be highly affected by perturbation length-scale. We then construct Hamiltonian flows tracing over parameter perturbations with a minimally disruptive effect on reference model predictions for each length scale, uncovering hidden conservation relations. Links to the concept of parametric unidentifiability are also provided.