Summer Research Series: Aaron Waldron - Mathematical Sciences

Mathematical Sciences student Aaron Waldron is participating in the summer research programme at the Faculty of Science and Engineering. We recently met with Aaron to ask about the programme and what he was investigating.

Course: LM124 Mathematics (Common Entry)

Supervisor: Associate Professor Shirin Moghaddam

Name of Research Project/Activity: Assessment of the efficacy of E.U. policy decisions in the automotive space, examining how vehicle trends align with climate goals.

Why did you decide to study Mathematics at UL? 

I am a Limerick native and enjoy living here. Having UL so near to where I grew up made it an obvious choice for third level and being able to commute and continue to live at home eased the transition into college life. I have always enjoyed math and chose to study applied math, physics and accountancy for the Leaving Cert. I also participated in the Irish maths Olympiad in fifth year.  My other interests lie in sport, reading and playing the piano. I decided to apply for the general Mathematics entry course in UL because it offered a broad introduction to mathematics allowing me the time to consider what direction I wanted my future career to go in. I was sure I wanted it to be suitably quantitative and involve problem solving, therefor this course seemed like the natural path.

What motivated you to apply for the Summer Bursary Programme? 

I was interested in gaining insight about what a potential future in research could look like. In addition, I usually pursue some further studies over the summer and so this programme appealed to me.

What are you doing as part of your research here at UL? 

The main goal of my research is to analyse EU automotive adjacent policies and assess how effective they are. This involves accruing data sources and the subsequent handling, be that exploratory data analysis to find and remove outliers and leverage points or imputing. I then use statistical methods, namely logistic regression and time series analysis to assess and discuss the effectiveness of a policy under different definitions, including the other actors it influences, the predicted outcome compared to targets, or the cohesion of trends across the EU’s member states. As part of my research, I need to be aware of the statistical method used and its suitability for the data given, the assumptions of the models, and have learned of the difficulties of “before-after” policy evaluation when treatment is applied en masse with no control groups.

What skills have you developed over the summer? 

I have massively improved my knowledge of the R programming language which is the principal way in which I handle and analyse data. This will be of great help given its ubiquity in future courses and indeed in many careers. In addition, I have been exposed to “Business Intelligence” tools like Tableau and have gained insight into how data can be visualised and presented depending on the form and levels it comprises. I have learned to manipulate datasets and understand the nuances that large datasets are comprised of. 

What has this experience taught you and what would you recommend it to others? 

This experience above all else has taught me to be flexible. Often data is not available or methods you have worked on have failed in their final assumption test. It showed me how many different considerations need to be made before an actual body of research can be prepared to ensure that the work produced is an appropriate use of the methods employed and something from which valuable insights can be gained. I would highly recommend this experience on the basis that there are very few opportunities for a first-year student to understand what research as a potential career could look like, this coupled with the potential of great upskilling under the supervision of an established researched made it an invaluable opportunity.

What are your future career plans, would you consider a career in research? 

As of now I plan to move forward with a more statistical and applied interest in mathematics. My future career plans reflect this with many options in the data analytics space being attractive. I would deeply consider pursuing research as a form of further education, but I would very much like to experience the world of work first. Ultimately from my experience thus far I can be confident that a career in research would suit me and will always exist as a potential path forward.