Adrian Guel holds both a bachelor's and a master's degree in Engineering, with experience in research, design, and education. Specifically, Mr Guel's experience lies in Control Engineering, Dynamical and Complex Systems, Statistics and Programming. Mr Guel has developed: Control Algorithms, Control Implementations, System identification and Modelling, Forecasting Methods, and Optimisation Algorithms. Currently, he is in the final stage as a PhD candidate at Coventry University. In his thesis, Adrian Guel focused on the analysis of models and control for Complex Systems using stochastic methods and information theory. 

Information geometry or the application of differential geometry to
the information sciences has become a promising tool for the analysis of
complex dynamical systems. From the information geometry tools, we have the concept of information length defined as the integral of the information rate and describing the total amount of statistical changes that a time-varying probability distribution takes through time.
We introduce the definition of information length and its application to stochastic thermodynamics, abrupt events detection, time series analysis and control engineering. All this is in the light of linear and non-linear non-autonomous stochastic systems.

Fractional calculus was used in this work as a tool to design control feedback algorithms for linear fractional and non-fractional order, time-invariant systems with time delay and as a mathematical modelling
tool for large-scale mechanical systems. The feedback control algorithm considered consists of a fractional PD and a fractional PI called: PD μ and PI λ , respectively. These new types of controllers have more
degrees of freedom and new dynamical characteristics being explored in this work. We search for practical applications and implications of using fractional-order controllers. Another important contribution of this work lies in the proposal and analysis of new mathematical models for a type of distributed parameter systems with special geometrical physical constructions implying multivalued complex function analysis.

Control theory, Complex Systems, Information Theory, Stochastic Thermodynamics, Stochastic Systems, and Fractional Calculus applications