Postgraduate Computer Science Students Impress at Annual Poster Day Exhibition

Earlier this month saw the annual Research Student Poster Day exhibition take place at the School of Computer Science and Informatics when postgraduate students designed and displayed posters that represented their current research project status.

The event offered an engaging platform in which students were able to showcase and discuss their research projects with fellow colleagues and tutors through design and creativity. The standard of work at this year’s event was excellent with each poster giving a fascinating insight into the varied and thought-provoking research projects currently being undertaking by the students; there was even a cash prize for the winner in each year group.

There were 35 students involved in the exhibition all offering unique and creative information about their individual research projects. Dave Marshall, Director of Postgraduate Research Studies said “There were many outstanding posters and breadth and quality of the research never ceases to amaze me.  The Poster day is one of the best days in the School calendar and a superb showcase for our PhD students’ research. The event had PhD students at all levels, some only a few months into their PhD studies, present their work and benefit from the experience of having to explain their work to staff members and other students. All good professional development and practice for their research.”

SCHOOL PRIZE for Best Poster

• Year 1 – Matilda Rhode, Deep learning techniques for malware classification using sequential data
• Year 2 – Beryl Noë,  Mood states, smartphone usage and smartphone addiction
• Year 3 – Jonathan Slade, Automatic Semantic & Geometric Enrichment of 3D geo-spatial Building Models using HOG-based Template Matching for varying architectural styles

STUDENT VOTE for Best Poster

• Year 1 – Eirini Anthi, Network layer security in the Internet of Things system
• Year 2 – Beryl Noë, Mood states, smartphone usage and smartphone addiction
• Year 3 – Aled Owen, Context Matters: Self Supervised Tasks for Video Representation