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Meet our new academic staff from the Department of Mathematics

Our interview series introduces new researchers who started this academic year in the Faculty of Natural, Mathematical & Engineering Sciences.

In this instalment, we spoke to Vasiliki Koutra from the Department of Mathematics.

Vasiliki Koutra

Dr Vasiliki Koutra is a Lecturer in Statistics within the Department of Mathematics. Her research is focused on developing efficient designs on networks and designs for multi-objective experimentation. These designs can be applicable in a wide variety of marketing, agricultural, healthcare and industrial contexts. She also collaborates with research groups from the Alan Turing Institute and provides statistical support to medical researchers.

 

What first attracted you to the field of Mathematics?

Mathematics is the language of nature and everything around us can be represented and understood through numbers. Patterns emerge everywhere from the ocean waves to the spirals of galaxies. The balance and disciplined thinking pushed me to kickstart my journey in mathematics. It was also the beauty of symmetry and its harmony in proportions that attracted me, which funnily enough after many years I am still intrigued by and continue to explore as part of my research in design of experiments on symmetric real-world networks.

 

What do you think is the biggest misconception people have about Mathematics?

I recently saw in one of my daughter’s books on professions, if you are good at mathematics, you can be an accountant! Mathematics is an essential subject that provides a strong foundational knowledge for many fields and different careers in science, commerce and industry. From a Statistician to Investment Analyst to Aerospace Engineer. Also, mathematics encourages an abundance of skills; it is an effective way of building mental discipline, critical thinking, reasoning abilities and problem-solving skills.

 

Tell us about something you are working on at the moment - what is exciting about it?

Carefully planned and executed experiments that allow valid inference for connected experimental units (i.e. described via a network) are key to effective decision making in an increasing number of research disciplines, medical trials and industrial settings. For large networks, for example derived from social media, existing optimal design approaches are too computationally expensive to be employed in a practicable time. Hence, heuristic and sub-optimal treatment selections are often applied. It is this gap that I am currently working on. In particular, I am developing novel methods to design experiments on large networks to estimate, either separately or jointly, the direct and indirect (viral) effects of treatments, by exploiting the particular topology of the network ultimately leading to faster and cheaper experimentation benefiting the economy and society.

 

What advice would you give to someone considering studying Mathematics?

Ignore the rules but remember the principles! Advice that can also be applied elsewhere. Understand the problem you are trying to solve, but be flexible, you may have to go off the beaten path to achieve your goals.

 

What do you do in your spare time?

Outside work I enjoy travelling with my family, meeting friends, swimming and reading.

In this story

Vasiliki Koutra

Vasiliki Koutra

Lecturer in Statistics

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