Premathas Somasekaram
Associate Staff

Interests

My research revolves primarily around augmenting the availability and dependability of intricate systems, those which hold paramount importance in business and safety-critical operations. The principal methodological approach I employ for this undertaking is probabilistic reasoning, with a focus on utilizing Bayesian networks in an array of manifestations, such as dynamic and decision networks.

The primary challenge I address pertains to the component level, which necessitates the capture of changes at a granular level. The objective is to emulate these alterations at a more comprehensive level, propagating them accordingly, with the ultimate aim of predicting the potential ramifications at a system-wide scope.

In addition, my research extends beyond the solitary functioning of individual components. I give equal emphasis to the interaction dynamics among various system components, scrutinizing the ripple effects instigated by alterations in a single component on the functionality of its counterparts.

In essence, my academic pursuit is a holistic exploration of system reliability, taking into account both individual component behaviors and their interactive dynamics within a complex system.

Qualifications

PhD in Computer Science, University of York, 2022
MSc in Computer Science, Uppsala University, 2017
MSc in Information Security, Lulea University of Technology, 2016
BA in English Literature, Umea University, 2023
BSc in Computer Science, Uppsala University, 2013
BSc in Computer Engineering, Linnaeus University, 2013

Career

Research Associate, University of York, 2022-