Theo Assiotis

Dr Theo Assiotis is new to Edinburgh, having joined the School of Mathematics faculty within the last academic year (2020-21). In my interview with him we discussed a range of topics, from his early life to what he enjoys most about his job as an Academic.

Childhood and University

Theo said that he was “always interested in maths”; all of the sciences appealed to him, but mathematics was the one he remembers enjoying the most. So, it is no surprise that he ended up doing a degree in the subject at the University of Cambridge. It was intense, and he wasn’t particularly fond of how competitive it was, however he enjoyed his time there and learned a lot. When he started at university, he didn’t know he was going to continue to Masters and beyond; indeed, in his own words he “wasn’t one of those people who at 15 wanted to be a professor”, however the allure of mathematics was strong and he found himself wanting to continue. The people who surrounded him as he studied for his PhD and postdoc were particularly influential to him.

Research

Theo works in the areas of probability theory and mathematical physics. On how he ended up here, he explained that he “knew [he] wanted to do something related to probability” but didn’t know exactly what. Theo’s research interests are broad, and we covered a couple of aspects of it: random matrices and branching graphs, to be specific. 

Random matrices originated in statistics, but their applications cover a wide and varied range: they can be used in machine learning, to model the nucleus of an atom and have even seen uses in modelling the synaptic connections in the brain. Theo’s research is more centered around probability, algebra and combinatorics, though the subject is highly connected to other areas of mathematics. Currently, Theo is studying the characteristic polynomials of certain random matrices, and a paper he is working on with two undergraduate students has just been completed.

Graph theory may seem like quite a divergence from Theo’s regular research at first glance, yet the subject of branching graphs is intricately connected to stochastics; Markov chains in particular. As Theo himself said, the “motivation behind [branching graphs] comes from representation theory”. This is a branch of mathematics where more abstract algebraic structures have their elements represented by linear transformations in a vector space. It is possible to associate to a branching graph a canonical Markov chain. Then there is a notion of a boundary for branching graphs, equivalently the boundary of the corresponding Markov chain, which is our stochastic link and what Theo personally researches in the area.

Being an academic

There are many aspects to working in academia, but to loosely break it down it consists of research, teaching and supervising. Research is always a highly enjoyable part of the job, with the greatest attraction for most being that “no-one has ever done this before”, in Theo’s words. However, he finds the most enjoyable part of his job to be supervising students of all levels. This is because it encompasses both research and teaching, but allows for interactions on a more personal level, as “you really get to know the person”. He went on to say that guiding someone else is a really rewarding part of the job, and even if you start at a place that you already know, by the end of it you’ve discovered something new.

Tips for students

The theme of Theo’s advice is perseverance. For going on in academia, he said that “it’s challenging, you will be stuck” and that “most of the things your supervisor will ask you to do will not work initially”. It can be disheartening when you’re used to the pre-PhD days of all the problems you’re asked having a known answer, but the key thing is to persevere. Not only in a PhD, should you choose to go that route, but with everything in life.