What sparked your interest in Computing and Mathematics?

When I was in school, I wanted to be an astronaut, but I was not the greatest at physics and I demonstrated a stronger ability in Computer Science and control technology. At secondary school, I built my first ‘robot’ and programmed it using the programme BBC Basic. I was inquisitive about how we could write lines of code to make a machine do specific tasks. I also liked a challenge and studied Artificial Intelligence (AI) as part of my first degree. 

What was your career journey prior to Joining Manchester Met?

After graduating from my degree, I had a good job offer as a Systems Analyst with a large Telecoms company. However, I chose instead to carry on in education and pursue a PhD which involved a teaching role within the University. 

I really enjoyed working with and helping students to understand key Computer Science concepts. I loved seeing them have a ‘eureka’ moment when they finally managed to solve a problem. Over the years, I have had the opportunities to work in hospitals with medical professionals on using ICT, teach elderly people how to use email and work with young people who have left school with no qualifications on Computer Science projects to help them to believe in themselves. 

What is your current role and what are your responsibilities?

I am a Professor in Computational Intelligence at Manchester Metropolitan University and lead the Computational Intelligence Lab at the Centre for Advanced Computing at the University. During my twenty years here, I have been so proud of my PhD students who help me to increase my knowledge on a weekly basis. I believe that the key to successful PhDs is a partnership where supervisors and students are on a research journey together to try and solve societal challenges and positively impact people’s lives.

Currently, my teaching focuses are Data Science, Database Systems and Machine Learning. No two years are ever the same given the rapidly developing fields of Computer Science and Computational Intelligence. 

I have a passion to bring Computer Science opportunities to rural schools in the UK and I can be regularly found in primary schools delivering programming and robotics sessions for children between four and ten years old. I also run Computer Science events at National Festivals and Institute of Electrical and Electronics Engineers (IEEE) Women in Engineering and IEEE Women in Computational Intelligence events that allow young people to have hands-on experiences and get inspired to further their education. 

My research is in the field of Computational Intelligence in which I develop intelligent computer systems that are inspired by humans and biology. The three main areas of Computational Intelligence are fuzzy systems, evolutionary computation and neural networks, and my research involves all three areas. 

In 2000, I started to work on Adapted Psychological Profiling Systems which detect different mental states by analysing micro gestures and non-verbal behaviours. This led to several funded projects across the globe. For example, a project with Family Health International 360 (USA) and the National Institute for Medical Research (Tanzania) led to the development of FATHOM, a computerised, non-invasive psychological profiling system that detects human comprehension. I have also developed an automated deception detection system that uses an adapted avatar to interview passengers prior to taking a trip. 

My research also focuses on the understanding of human language by machines. This has led to the development of semantic similarity measures that analyse human languages in different applications to understand meaning and context. I also work on the development of goal-orientated conversational agents such as ‘Betty’ - an agent to improve the normal aging associated with memory loss and increase subjective wellbeing - and ‘Hendrix’ - an agent designed to deliver java programming tutorials to undergraduates. Hendrix has been linked with work on automated comprehension detection which allows for a system that can detect and adapt to a person’s non-verbal behaviour during a tutorial and automatically help them. 

A theme running through all the areas I focus on is the ethical, social and legal implications of Computational Intelligence. I am the current chair of the IEEE Taskforce on Ethical and Social Implications of Computational Intelligence and contributed to the second edition of the IEEE Global Initiative on the Ethics of Autonomous and Intelligent Systems. 

I believe that industry partnerships are essential to transfer academic research from the laboratory into a solution that can be integrated into an industrial system. I work on two Knowledge Transfer Partnerships with companies in the UK that are designed to provide novel machine learning integrated solutions to industry problems. 

How did your degree prepare you for your current role? 

In my undergraduate degree, I learned the fundamentals of Computer Science, how to code and was introduced to AI. My final year project working on the Staff Accidents database at Stepping Hill Hospital gave me the challenge of understanding, managing and processing data and performing data analytics. This degree helped me to gain experience working in teams on larger projects and taught me the importance of good communication. 

I’d advise students to practise your coding, and then practise more. Understand the ethical
implications of work you do that involves data, especially artificial intelligence. Get yourself a mentor. Learn from both achievements and failures. Don’t be a label – you are an individual and we are all different.

What do you enjoy about your current role? 

The everyday variety: teaching, exchanging ideas with industry, working with local SMEs and businesses, volunteering with IEEE, performing STEM outreach, working on Knowledge Transfer Partnership, innovating new ideas, designing experiments, writing bids and papers and much more. 

People make the world go around. By this, I mean all colleagues that I work with and students who I get the chance to work and share ideas with. Being involved with Degree Apprenticeship programmes has also enabled me to work with apprentices and their line managers on real-world problems. 

What are your future plans?

In the future, I hope to help support a variety of people in thinking about the ethical uses of AI in the lifecycle of developing systems. I also want to contribute to ensuring that all members of society have access to education about how decisions are made by AI systems and to mentor others.  

Prepare for your future.