SPRITE+ Member Spotlight – Sotiris Moschoyiannis

This article was edited by SPRITE+ Research Associate Dmitry Dereshev, with responses and edits from Reader in Complex Systems Sotiris Moschoyiannis.

The spotlight today is on Sotiris Moschoyiannis – Reader in Complex Systems at the University of Surrey, and a SPRITE+ member. Some of Sotiris’ latest publications include:

A bit about you and your role

How would you describe your job to a 12-year-old?

I come up with computational and mathematical methods to solve real-world problems, which can improve peoples’ lives. So, I do a lot of reading and writing (or typing).

I also try to get young people to love science and engage in challenging the limits of what we know and understand.

Could you describe what you do during a typical workday?

My workday involves a lot of reading and writing, and usually a few meetings. If I am teaching, I will spend some time looking at the material of the previous week as well as a few weeks ahead and try to remind myself of the interesting questions students might have asked a week prior. Based on that I adjust the material (lecture notes, handout exercises, lab exercises) for the next class and lab.

If I am doing research, I will spend most of the morning reading, and then exchanging ideas with my research students and other collaborators, including industrial partners, government, and sponsors.

Could you describe a challenging project that you have recently worked on?

In a recent research project we set out to model and predict flows of people and trains in large cities – we had a case study looking at Manchester and then London. This included working through 6 years’ worth of data from Network Rail and trying to predict whether a train would be late or not. In addition, the use cases from the industrial partners imposed strict real-time requirements. This was far from trivial. We had to rely on some clever engineering over state-of-the-art industrial strength platforms (serverless) that allowed us to deploy our deep learning models on demand, very close to real-time, and predict train movements across the UK networks. The whole research team was pleased with this.

What training/experience did you have at the start of your career?

I consider my PhD studies (Computer Science, University of Surrey, UK) as the start of my career. I attended a few modules such as Research Methods from reputable successful researchers to get me going, but perhaps more importantly I had a supervisor who would fill the whiteboard about 10 times in each supervision meeting! The research seminars, even those on topics that seemed a bit removed from my core research area, were also invaluable. And a lot of reading!

How did you get into your current role?

Almost by accident. Maths was always my favourite subject at school. Unsurprisingly, I did my first degree in Maths (University of Patras, Greece) and then went for a computing-related MSc (University of Surrey, UK) to become a bit more applied. Maths was wonderful and I loved it at Uni, but I had not quite grasped where it was useful until I did my MSc dissertation on error detection/correction codes – this showed me how the elegant theory of Galois fields came to life when one wants to transmit information reliably over noisy channels (by the way, Évariste Galois developed this theory before he was 20). This excited me. My MSc supervisor became my PhD supervisor, and then I kept working on research projects as I wanted to publish my latest results before going to industry to get a proper job… Well, I ended up getting a proper job in academia and now I am working with industry on research projects, which is rather cool!

What do you wish you had known when you started your career?

I wish I were more patient. I am focused and I have always been persistent, but research and academia are all about being patient. And reading. And writing.

What would you recommend to people who want to follow in your footsteps?

Remain sceptical about everything, including what is known and what is not known. Use that curiosity to fuel a passion for research, for advancing the current state-of-the-art. And then be patient in producing some good research outputs.

Also, if you teach, try to remember you were a student too.

What troubles did you have progressing through your career?

The timings need to work, and they do not always work. Often, you have the funding but not the right people. More often perhaps, you want to keep some good researchers on board but there is no funding at the right time. Also, people in academia move a lot, so you need to adapt to change quickly during your journey.

What stereotypes would like to dispel about your job or industry?

That theory is far removed from practice, or that something is “purely academic”. Some breakthroughs take longer to affect peoples’ everyday lives but when they do, they may have a profound effect. So, again, patience!

A bit about your involvement with SPRITE+

How would you describe your research or business interest in relation to SPRITE+?

The vision of SPRITE+ aligns with my interest in ultimately solving real-world problems, which can improve peoples’ lives, whether that is by making the world more safe or more prosperous. Today’s problems tend to be complex and evolve fast. To have a better chance, one needs to bring together a community of researchers, the stakeholders, and build a combined vision for the future.

How do you hope to benefit from working with SPRITE+ network?

SPRITE+ is a vibrant community with an array of interests, resources, and ideas. It is exciting to be able to tap into this.

Which of the SPRITE+ Challenge Themes can you relate to from the job that you do?

Digital Vulnerabilities, Digital Technologies, and Change.