Dr Ruth Misener

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Job title: Senior Lecturer
Division: Department of Computing
Organisation: Imperial College London
Tags: Engineering, Fellowship: Early Career, Imperial College London, Manufacturing the future, Mathematical sciences, Researcher
Related theme: Engineering Manufacturing the future Mathematical sciences


Ruth is a Senior Lecturer in the Department of Computing at Imperial College. Foundations of her research are in numerical optimisation algorithms; current applications include bioprocess optimisation under uncertainty and petrochemical process network design and operations. She received the 2017 Sir George Macfarlane Medal from the Royal Academy of Engineering.

My Fellowship

This fellowship develops GALINI, new decision-making software constructing and deploying next generation process optimisation tools dealing with combinatorial complexity, disparate temporal/spatial scales, and safety considerations. The GALINI project proposes step-changes in optimisation algorithms that are immediately applicable to efficiency challenges in process systems engineering (PSE): safely operating batch reactors, retrofitting heat-exchanger networks, intermediate blending, and integrating planning and scheduling. We aim to freely release our software on open-source platform Pyomo and build an international user community.

The primary GALINI research aim is to develop optimisation software that pushes the boundary of computational tractability for PSE energy efficiency applications. Effective optimisation software in the process industries answers: How can we best achieve a definite engineering objective? Given constraints such as an existing plant layout or a contractual obligation to produce specific products, the software supports novel engineering by quantitatively comparing the implications of different options and identifying the best decision. GALINI is particularly interested in design: How should we build new facilities or modify existing ones to achieve our design goals with maximum efficiency?

GALINI develops deterministic global optimisation software for mixed-integer nonlinear programs, a type of optimisation problem highly relevant to energy efficiency and process systems engineering. Energy efficiency instances may exhibit the mathematical property of non-convexity, i.e. have many locally optimal solutions; global optimisation mathematically guarantees the best process engineering solution. GALINI proposes transformational shifts in algorithms that creatively re-imagine the core divide-and-conquer algorithm typically applied to this type of optimisation problem.

Motivation to Apply

Ruth was motivated to apply for the EPSRC Early Career Fellowship in "Software development for novel engineering research" because she highly values both fundamental engineering research and translating that research into practice. With the fellowship, her group has funding not only for innovative engineering but also for software development and maintenance. She is delighted that the EPSRC is supporting software development because distributing high-quality, usable code allows her research group to engage with practitioners worldwide.

Career benefit of Fellowship

The EPSRC Early Career Fellowship in "Software development for novel engineering research" allows Ruth to advance her career as a: (i) mathematical optimisation researcher developing novel methodology, (ii) process systems engineer interested in energy efficiency, and (iii) software developer interested in providing high-quality code. The fellowship also helps her to support her group of talented and motivated researchers. She appreciates the time that the fellowship gives her to focus on research.

Advice for future applicants

Ruth advises applicants to carefully read the EPSRC Person Specification and the individual fellowship call. She realises that this sounds obvious, but applicants should be carefully studying the EPSRC guidance: (i) before starting to write the proposal, (ii) while writing the proposal, and (iii) while editing and revising the proposal. Closely following EPSRC guidance not only helps convince reviewers and panel members, but it also helps effectively re-but negative reviews.