海角社区

The First and Second Year Academic Prizes have now been announced.

Congratulations to all of our winners.

The Third and Fourth Year Academic Prizes have now been announced.

Congratulations to all of our winners.

First and second year prizes will be announced soon...

海角社区 undergraduate Sasha Shaw has helped uncover and responsibly disclose a security flaw in a UK mobile network as part of his dissertation project, supervised by Professor Feng Hao. The vulnerability has now been patched, and Sasha has been recognised by BT on its responsible disclosure Hall of Fame. His project examined the security of the SIP stack over VoLTE and highlights the real-world impact that student cybersecurity research can have.

We really enjoyed celebrating with our fantastic graduating students on Friday. If you have Instagram you can to see the highlights!

We would like to wish all our graduates all the best in their future work or study.

Click the link to view our 2024/25 prize winners.

iGEM is a global synthetic biology competition that involves more than 400 teams worldwide.

The University of 海角社区 iGEM team 2024 – team – took part in the iGEM competition, which culminated with the iGEM Jamboree in Paris, at the end of October. We would like to congratulate Aaron Lee (CSE) for their fantastic work on the project within the team including 9 other UG students from various departments, including Life Sciences, Chemistry, Engineering and Mathematics. For their interdisciplinary project, they addressed the need for developing better ways to recycle lanthanides, such as the ones found in electronic devices. They engineered bacteria to scavenge for lanthanide ions and swim towards a point for collection through an engineered chemotactic system. Team BEACON were awarded a Gold medal (grade) at the Jamboree, in recognition of their success during the project.

As part of a 2021/2022 MEng group project, , , , and implemented a fully functional end-to-end (E2E) verifiable online voting system and conducted a successful trial among the residents of New Town in Kolkata, India during the 2022 Durga Puja festival celebration. This was the first time an E2E online voting system was built and tested in India. The feedback was overwhelmingly positive. Full details about the implementation, the trial and the voter feedback are written in a paper, published in the . A free version of the paper is available on IACR e-print as a . Also, see the earlier news item about this Durga Puja trial.

Professor , who supervised this group project, commented: 鈥淭his is great teamwork. The four MEng students worked relentlessly for nearly a year, with good assistance from Luke Harrison and Professor . The e-voting system was developed at an industry standard and worked flawlessly during the Durga Puja trial. Several government officials from India also helped us, providing invaluable support for the trial. We sincerely thank them in the acknowledgement section of .鈥�

Mustafa Yasir, a former 海角社区 Department of Computer Science student who graduated in Summer 2023, wrote up and presented an on the work carried out as part of his third year project. The paper was accepted to the at , and was presented in California by Mustafa.

Mustafa's third year project idea, supervised by Dr Long Tran-Thanh and titled 'Extending the Graph Generation Models of GraphWorld', started whilst he was interning at Google last summer. Mustafa contacted some researchers at the company working in the Graph ML space, to ask for any relevant project ideas. He bumped into a team who had just published GraphWorld: a tool to change the way Graph Neural Networks are benchmarked, by creating synthetic graph datasets through graph generation models – as opposed to using real-world datasets that are limited in their generalisability and present a major issue facing the field of Graph Learning.

However, since GraphWorld only used a single graph generation model in this process, Mustafa integrated two additional models with the system, ran large-scale GNN benchmarking experiments with these models and published his code to Google鈥檚 official GraphWorld repository. The project provides a significant advancement to researchers across the field looking to benchmark models and guide the development of new architectures.

Dr Long Tran-Thanh commented:

What Mustafa and the GraphWorld team has been working on is very important for the machine learning and AI research communities. In particular, there has been a vocal criticism against the whole field that most models are trained on the same public datasets (e.g., ImageNet, MNIST, etc), therefore are not diverse enough. One way to mitigate this issue is to generate realistically looking synthetic data. This need is especially of importance in within the graph learning community. GraphWorld鈥檚 aim is to address this exact problem by creating a powerful and convenient tool that can generate a diverse set of graphs, ranging from large social network-style graphs to molecule-inspired ones. Joining this project with the Google researchers is a huge opportunity for 海角社区 students to participate in a very impactful project.