Dr Sandy Brownlee

Senior Lecturer in Computing Science

Computing Science and Mathematics - Division Room 4B125 University of Stirling, Stirling, FK9 4LA

Dr Sandy Brownlee

Contact details

About me

Contact: if you have an enquiry about the Big Data or AI MSc Programmes, please email big-data@stir.ac.uk or artificial-intelligence@stir.ac.uk. For any other communications, I can be reached at alexander.brownlee@stir.ac.uk or on +44 (0)1786 467454.

I'm a Senior Lecturer within Computing Science and Mathematics at Stirling, leader of the Data Science and Intelligent Systems research group and also a member of Computational Mathematics and Optimisation research group. I am co-lead of the AI Theme for SICSA, helping to connect and support the AI research community in Scotland. I am also a Visiting Fellow in Civil and Building Engineering at Loughborough University. I'm interested in explainable or value-added optimisation: techniques that yield optimal or near-optimal solutions but also reveal underlying information about the problem to help people make informed decisions. My main focus is in metaheuristics, including evolutionary algorithms and estimation of distribution algorithms; related issues such as fitness modelling (and mining such models), handling constraints and multiple objectives, and decision support. I am also interested in the underlying theory of what makes particular algorithms suited to particular problems. I have applied this work to application areas including scheduling and simulation-based optimisation in civil engineering and transport, software engineering, healthcare, and art.

More detail on my interests and activities can be found on my CSM webpages, under "My personal webpage" above.

I'm broadly interested in optimisation and machine learning, including real world applications of these and underpinning theory.

More details can be found here: https://www.cs.stir.ac.uk/~sbr/research.html

Background to my work

I have always been fascinated by computing and in particular artificial intelligence techniques. I particularly enjoy the interplay between the theoretical side of understanding what makes different algorithms tick and the huge range of interesting application areas that have meaningful real-world value (or are just fun!). My work has settled around approaches to dealing with real-world optimisation problems; handling uncertainty, solving problems with hard constraints and multiple objectives, dealing with long simulation run-times and analysis of optimisation results to better help with decision making. I completed a Computer Science BSc(hons) in 2005 at Robert Gordon University in Aberdeen, Scotland. During the last year of that degree I was funded by the Carnegie Trust to conduct a short-term research project in applying genetic algorithms to cancer chemotherapy scheduling. My interest in this area grew, leading to an honours project in timetabling with memetic algorithms. I then progressed to work for a PhD, entitled Multivariate Markov Networks for Fitness Modelling in an Estimation of Distribution Algorithm. This covered a range of applications for evolutionary algorithms, and focussed on the construction of fitness models to support the evolutionary process. I continued to research alongside a job as a software engineer in industry during 2008-2010, where I was working in the sector of oil, gas and renewable energy. I returned to full-time as a research associate in the building energy group at Loughborough University, and subsequently came to the CHORDS research group (now part of the Data Science group) here at Stirling in 2013.  

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