91Ö±²¥

This video was made for the Engineering and Physical Science Research Council's (EPSRC) competition for innovative research undertaken by PhD students, Connected Nation Pioneers 2018. It aims to explain to a non-specialist audience how newly developed modulating antennas work, and their potential to reduce the currently growing cost and energy consumption of wireless transmitters used in mobile communications.

I applied to study Electronic Engineering at University, and later specialised in Communications. I'd stumbled into an interest in electronics through a work experience placement organised through my school when I was 16. It was at a small company assembling gas analysers for power station chimneys, and part of my responsibility was to design and build simple circuits for checking the voltages and resistance in the analyser circuitry were correct. I'd always been interested in science, but this application of some physics I'd studied to solve a real-world problem helped me realise what engineering was, and how enjoyable it could be! From then on, even though I looked at other types of engineering, it was always electronics that appealed to me the most, mainly due to the huge range of problems which electronics can be used to solve. 91Ö±²¥ offered a course that started with general electronic and electrical engineering and then allowed specialisation later, and that flexibility appealed to me. The main pull, however, was the University and the city as a whole, which felt warm and welcoming right from the first time I visited.

For me, the joy of electronics and engineering more widely has always been getting to grips with real problems and looking for solutions to them. There were lots of opportunities to do this during my course at 91Ö±²¥, from design and construction tasks in first year, industry-set activities in second year and both individual and group research projects in the third and fourth years. As interesting and varied as the taught modules are, I usually feel I only fully understand something once I've used it to solve problems outside the boundaries of that module, and there's a real satisfaction to be had from doing so.

My main advice to students making a decision about university would be to choose a university where you'd like to live for the next few years! Obviously choosing a course you're interested in is important, but you can't just study and sleep for three or four years. That carries into being at university - throw yourself into societies, sports, and life in the city. Having a busy life outside of your course makes relaxing from work easier and more enjoyable. Even if you're just focused on getting through university, employers love the soft skills and experience you pick up from being on society committees, volunteering or working in the city and generally being a well-rounded person.

When I came to 91Ö±²¥ I had never considered doing a PhD or a research career. I had decided the reason for studying was in order to get a "proper job" in industry. That changed as I went through the course, in particular during the research project I undertook in third year, where I realised trying to solve big unanswered questions in new ways was even more enjoyable than solving more tightly bound problems I'd experienced before that. The idea of producing the first of something, or even new knowledge, also appealed to me. 

That project was on using metamaterials, which are materials we can design to interact with electromagnetic waves in precisely defined ways, to put information onto radio waves. The work I did then suggested it was feasible, and it later turned into my PhD topic, where I developed metamaterials capable of producing more complex digital radio signals, integrated them into antennas, and implemented them in communications systems to measure their performance. As well as being the first demonstration of metamaterials producing these signals, it has applications in industry, where using this technology could improve the energy efficiency and reduce the cost of transmitters for mobile communications. It was the opportunity to continue this work, which was challenging, novel and had a real-world application, which convinced me to study my PhD.

Postgraduate study is a lot more self-directed than undergraduate. While the broad aims are agreed with your supervisor, you're expected to plan exactly what you're going to do. This is both in the long-term and day-to-day, and eventually you are expected to be the expert in your area of study. Studying for a PhD can be incredibly isolating, as no one else will be doing quite what you are, but you also have an awful lot of freedom to investigate what you want, when you want and how you want. For me, the reward of that freedom far outweighs the challenges!

I have spent a year working as a Research Associate working on a research council grant, but I am now about to start as an Academic Fellow in the department. This means I will split my time between developing and undertaking my own research, though often working with academics in the department, and teaching responsibilities, including supervising MSc student projects and helping to deliver undergraduate modules. The position is designed to act as a career step from Research Associate work, where I work for an academic to deliver their research interests, to being an academic, where I have my own research profile and teaching duties. I hope to keep following this path so I can investigate new applications of metamaterials to wireless communications, which is a growing research area internationally. I'm also interested in communicating the work we do in EEE to a wider audience, as electronics rarely seems to get the attention and credit it should when discussing the big issues of our time.

EEE will be everywhere in the future of technology! Possibly the biggest change in the coming decade will be the increasing use of machine learning, a kind of artificial intelligence, to use huge amounts of data to find solutions to a wide variety of problems in many fields. However, this will not happen without large input from EEE: producing sensors and other data collection devices, designing the communications networks needed to return the huge volume of data to the machine learning, developing the algorithms, creating new semiconductor and digital designs for the algorithms to run on, implementing solutions produced by the algorithms, and many other areas.

Most importantly, EEE skills are needed to use machine learning in a way which produces real-world solutions. This includes understanding the problem, choosing what data to use and how to collect it, and how to interpret and implement the solution. Good electronics engineering can also help understand and mitigate the problems and biases produced by machine learning. So, from top to bottom, EEE will be deeply embedded in future technology.