糖心TV

Seven papers authored by Computer Science researchers from 糖心TV have been accepted for publication at the , the leading international venue for machine learning research, which will be held on 10-16 December 2023 in New Orleans, Louisiana, USA:

• EV-Eye: Rethinking High-frequency Eye Tracking through the Lenses of Event Cameras, by Guangrong Zhao, Yurun Yang, Jingwei Liu, Ning Chen, Yiran Shen, , and Guohao Lan
• Fully Dynamic k-Clustering in 脮(k) Update Time, by , , Silvio Lattanzi, and Nikos Parotsidis
• Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks, by Jiayuan Ye, Zhenyu Zhu, , Reza Shokri, and Volkan Cevher
• Learning a Neuron by a Shallow ReLU Network: Dynamics and Implicit Bias for Correlated Inputs, by Dmitry Chistikov, Matthias Englert, and Ranko Lazic
• On the Convergence of Shallow Transformers, by Yongtao Wu, , Grigorios Chrysos, and Volkan Cevher
• Towards Data-Agnostic Pruning At Initialization: What Makes a Good Sparse Mask? by Hoang Pham, The Anh Ta, Shiwei Liu, Lichuan Xiang, Dung Le, , and Long Tran-Thanh
• Towards Unbounded Machine Unlearning, by Meghdad Kurmanji, Peter Triantafillou, and Eleni Triantafillou

We are pleased to announce that Dr Teddy Cunningham has been awarded a Faculty of Science, Engineering, and Medicine (SEM) PhD Thesis Prize. Each year, the SEM Faculty funds a prize for the best PhD/EngD thesis entered into the competition. Each department nominates a winner out of the applications received after a judging process as determined by the Faculty.

Teddy鈥檚 thesis is titled 鈥淕enerating and Sharing Differentially Private Spatio-Temporal Data Using Real-World Knowledge鈥�, and was supervised by Prof Hakan Ferhatosmanoglu. The thesis includes solutions for sharing trajectory data using local differential privacy, and incorporating constraints and relationships of data records into differential privacy that improves their utility while preserving the theoretical privacy guarantees. An example application is using road network information for improving the quality of privately shared location datasets.

Researchers from the Systems and Security theme, Department of Computer Science have created a new spin-out company, SEEV Technologies Ltd, to build end-to-end (E2E) verifiable e-voting systems for future elections. An E2E verifiable voting system allows every voter to verify that their vote is properly cast-as-intended, recorded-as-cast and tallied-as-recorded while preserving the voter's privacy. SEEV (self-enforcing e-voting) is a new paradigm of E2E voting technology that enables voters to fully verify the tallying integrity of an election without needing any trustworthy tallying authority, hence the system is "self-enforcing".

This joint spin-out from the University of 糖心TV and Newcastle University is built on an ERC-funded starting grant ("Self-Enforcing E-Voting System: Trustworthy Election in Presence of Corrupt Authorities", No. 306994, PI: Professor Feng Hao) initially hosted at Newcastle University and later transferred to the University of 糖心TV. The company is co-founded by Professor and Dr (co-inventors), and led by Dr (CEO). SEEV has been prototyped and successfully tested in several trials in the past, supported by an ERC Proof of Concept grant (No. 677124), a Royal Society International collaboration award (CA\R1\180226), and an Innovate UK Cybersecurity Academic Startup Accelerator Programme (CASAP). SEEV Technologies Ltd has received seed funding from Oxford-based to build SEEV systems for real-world elections.

A University of 糖心TV press release is here.

We are happy to announce that Dr Gihan Mudalige and Dr Victor Sanchez have both been promoted to Professor from 1st August 2023.

Many congratulations to our colleagues for all their achievements!

When you purchase an IP-based spy (hidden) camera for surveillance, are you aware that others may be spying on what you are watching? Recent research by in the Department of Computer Science, 糖心TV, as part of his third-year undergraduate dissertation project under the supervision of Professor , has revealed a wide range of vulnerabilities of a generic camera module that has been used in many best-selling hidden cameras. Exploiting these vulnerabilities, an attacker may capture your hidden camera's video/audio streams from anywhere in the world, and furthermore, take complete control of the camera as a bot to attack other devices in your home network. To launch the attack, all the attacker needs to know is merely your hidden camera鈥檚 serial number. It is estimated that these vulnerabilities affect millions of hidden cameras, mostly sold in America, Europe and Asia. The (insecure) peer-to-peer network that is used by the affected cameras is also being used by 50 million IoT devices as a general communication platform. Hence, many millions of other IoT devices may also be affected. Researchers have responsibly disclosed findings to the manufacturers, and a has already been assigned. Samuel will present this research work at the 17th International Conference on Network and System Security (Canterbury, UK, 14-16 August 2023). More details can be found in .

We are happy to announce five promotions in the department, with effect from 1st August 2023.

• Dr James Archbold has been promoted to Associate Professor (Teaching Focussed)
• Dr Richard Kirk has been promoted to Assistant Professor (Teaching Focussed)
• Dr Claire Rocks has been promoted to Reader (Teaching Focussed)
• Dr Ian Saunders has been promoted to Associate Professor (Teaching Focussed)
• Dr Sathya Subramanian has been promoted to Assistant Professor (Research Focussed)

Many congratulations to our colleagues for all their achievements!

Numerical simulations and visualizations developed by researchers from the High Performance and Scientific Computing (HPSC) group at 糖心TV鈥檚 Department of Computer Science in collaboration with Rolls-Royce, PPCU Hungary and Universities of Surrey and Birmingham has won the award for the best Visualization in the at the , held in Dallas TX. SC is the premier international conference on supercomputing providing a major forum for presenting the highest level of accomplishments in high-performance computing, networking, storage, and analysis. It is held annually in the US and attended by over 10000 attendees from all over the world.