School of Computer Science

PGR Poster Session

The School held a successful PGR Poster Session on Monday 27th January, which was very well attended. The posters displayed were impressive and well presented by the PGR students. Well done to all who attended and took part! 👏

PhD Viva Success: Thomas Hansen

On behalf of the School, we would like to congratulate Thomas Hansen supervised by Dr Edwin Brady who has successfully defended his thesis. Thanks to Dr Adam Barwell who was internal examiner and Dr Jeremy Yallop from University of Cambridge as external examiner. Many congratulations to Thomas! 🎉  

Getting into the festive spirit

Michael Young, Ruth Hoffmann, and Mun See Chang are getting into the festive spirit, creating gingerbread houses during coffee break.

Winter Graduation 2024

On behalf of the School of Computer Science, we would like to congratulate all of graduating students. We wish you all the very best of luck! 🎓

PGR Seminar with Zhongliang Guo

The next PGR seminar is taking place this Friday at 2PM in JC 1.33a Below is a title and Abstract for Zhongliang’s talk– Please do come along if you are able. Title: Adversarial Attack as a Defense: Preventing Unauthorized AI Generation in Computer Vision Abstract: Adversarial attack is a technique that generate adversarial examples by PGR Seminar with Zhongliang Guo

PGR Seminar with Carla Davesa Sureda

The next PGR seminar is taking place this Friday 22nd November at 2PM in JC 1.33a Below is a Title and Abstract for Carla’s talk – Please do come along if you are able. Title: Towards High-Level Modelling in Automated Planning Abstract: Planning is a fundamental activity, arising frequently in many contexts, from daily tasks PGR Seminar with Carla Davesa Sureda

Fully funded PhD scholarship in Algorithms for Data Science

Lead supervisor: Dr Peter Macgregor Application deadline: 1 March 2025 Project description: Modern data science and machine learning applications involve datasets with millions of data points and hundreds of dimensions. For example, deep learning pipelines produce massive vector datasets representing text, image, audio and other data types. The analysis of such datasets with classical algorithms Fully funded PhD scholarship in Algorithms for Data Science