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Kieran Donovan

Kieran Donovan

Senior Servo Engineer

Engineering / Architecture

London, Greater London

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About Kieran Donovan:

An ambitious individual with strong mathematical skills looking for a role at the intersection of control theory, algorithms, and engineering focused software development.

Significant programming experience with Python and Matlab; knowledge of C, C++, R, SQL, Git, DOORS; Learning C# and keen to learn other programming languages.

A proven track record of high grades and numerous awards for academic performance.

SC Cleared

Experience

Senior Servo Engineer

MBDA UK
October 2022 - Present
- Individually designed and implemented (ongoing) an OOP codebase for the

servo team to facilitate the pipelining and semi-automation of data generation and analysis with respect to hardware testing and proving. The design opens up the potential for seamless cross-project capabilities and aids the standardisation of data presentation and analysis across projects.

- Produced model and test specification documents derived from technical requirements.

- Conducted hardware testing and data analysis to validate the design of a fin actuation system.

- Designed and implemented Simulink models of the actuation system to support design verification, and the assessment of performance under parameter variation via Monte Carlo simulation.

- Investigated the use of sensor-less Field Orientated Control algorithms.

Education

University of Southampton

September 2019 - September 2023
PhD By Research - System identification of time-varying dynamical systems

Expected completion - September 2023

TECHNICAL OVERVIEW

My PhD research focused on an “energy-based” approach to the modelling of time- varying dynamical systems, relying heavily on the use of orthonormal basis functions to represent and manipulate signals of interest in both the time and frequency domain. In addition to the wide range of advanced mathematics I have been introduced to (Linear algebra, function spaces, dynamical systems, signal representations and transforms), I have developed a familiarity with a range of modern techniques of mathematical modelling (machine learning, state space methods, Monte Carlo simulation), and built significant skills in the use of Matlab and Python for the purpose of computational modelling and simulation. As part of my research I have authored several signal processing scripts and system identification algorithms using Matlab, and gained experience with PID and LQR control methods.

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