Welcome to my site.
I am currently an Interactive Artificial Intelligence CDT candidate studying at the University of Bristol. My plan is to document as much of my PhD as possible to help give guidance and insight for prospective PhD students.Industry Placement
From June, I will begin my 6 month placement as an AI Research Engineer at Imagination Technologies.
Current Research
I am based in the Data-Intensive Astronomical Analysis research group where I am currently working on source classification (star, galaxy, AGN, QSO separation) using Active Learning and Outlier Detection methods.
To take advantage of the experience I gained from undergrad, as well as being one of the key aims of the CDT, I have a strong interest in creating software that aids researchers in applying machine learning methods to their respective fields.
Supervisory Team
Sotiria Fotopoulou , Malcolm Bremer and Oliver RayRecent Publications
G. Stevens, S. Fotopoulou, M.N. Bremer, O. Ray
Journal for Open Source Software
PDF DOI BIB ABSTRACT PROJECT
Recent Posts
My Experience of Being a Student Ambassador
Published:
Why widening participation and outreach projects are so important for prospective students from underrepresented backgrounds. Read more
Recent Talks
The Hidden Difficulties of Machine Learning
Presented at Access To Bristol, 2021
On-campus presentation to 30 local sixth form students who intend to study Engineering at university. This presentation immediately followed the AI & ML:Cutting Through The Hype talk and was used to show how ML tasks are often not as straightforward as they may seem. This talk is very interactive with the aim that the students are able to discover the problems that appear themselves and see why certain solutions may not be sufficient for a problem. Read more
AI & ML: Cutting Through The Hype
Presented at Sutton Trust Summer School, 2021
Webinar presented to 60 sixth form students who intend to study Engineering at university. The presentation starts with an introduction to what Computer Science is (and is not) like at university. Following this, the (very brief) foundations of what Machine Learning and AI really are. Unfortunately, the adoption of these tools has led to a large amount of over-exaggeration and overuse of certain buzzwords throughout the industry, making it seem like companies are doing super complicated and ground-breaking things when most of the time they’re doing nothing more than the Maths the students use in their A-Level studies. I also show the Dot-Com Boom and the AI Winter as examples for how overhyping can be damaging for research progress and the economy. Read more