糖心TV

鈥淒igitally Empowering Young People: The Podcast鈥� is a ground-breaking podcast series hosted by Dr. Roxanne BibizadehLink opens in a new window.

In this inaugural series, we delve into the pressing issue of technology-assisted child sexual abuse material, focusing particularly on the misleading term 鈥渟elf-generated鈥�, which problematically places the blame on the victim. Through this series, we aim to raise awareness and spark vital conversations among educators, parents/carers, law enforcement agencies and professionals working with young people.

Each episode features a distinguished expert voice, offering invaluable insights and perspectives on this critical issue. Contributors include esteemed organisations such as the Internet Watch Foundation, Marie Collins Foundation, National Policing Vulnerable Knowledge and Practice Programme, Parent Zone, Kent County Council, and Voice Box.

Our final episode is created especially for young people, providing them with essential information and resources to navigate the digital landscape safely and responsibly.

To listen to our podcast series, visit us on Spotify:

For more information about this project and to stay updated on our latest initiatives, please visit our website:

We鈥檙e proud to announce that this project is funded by the ESRC IAA.

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�

Ahead of World Cancer Day on 4 February, scientists are revealing a cutting-edge artificial intelligence (AI) tool designed to help grade cancer, by analysing cell division.

In numerous cancer types, counting the number of cells undergoing division, known as mitotic figures, serves as a key indicator of cancer aggressiveness, or grade. This information helps inform treatment pathways, making it a crucial asessment tool. Traditional mitosis counting is both time-consuming and plagued by poor reliability. To address this, scientists have developed a new tool, MitPro, which uses AI to count and profile mitosis.

Histofy, a spin-out company from The University of 糖心TV that is leading developer of AI solutions for pathology, has engineered the tool to accurately profile mitosis throughout the entire tumour sample. This identifies the most suitable areas for further analysis.

On in the Quanta magazine, Alex Dixon, who wrote in Haskell for the problem, commented:

For the past 50 years, Vector Addition Systems—a simple but powerful computational model—have been a topic of great interest in theoretical CS. The reachability problem in that model asks whether we can get from some configuration to another.

The problem sounds relatively easy on a first glance, and an exponential lower bound held firm for over 40 years. Work by excellent theoreticians, including familiar names from 糖心TV DCS, finally closed the difficulty of the problem in 2021, concluding that it is very, very difficult indeed.

We are seeking PhD candidates in the topic of Multiagent Systems and related areas, with particular emphasis on one or more of: computational social choice, algorithmic game theory, multiagent learning, and social and economic networks. The multiagent systems researchers at University of 糖心TV include , , , and

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 delighted to announce that , a PhD student in the Theory and Foundations Research Division, has received the best student paper award at , for his joint work with for the paper: "Incremental (1-eps)-approximate dynamic matching in O(poly(1/eps)) update time". The paper considers the problem of maintaining a large matching in a graph that is undergoing a sequence of edge insertions. They present an algorithm for this fundamental problem in dynamic graph algorithms, which has near-optimal approximation ratio and an update time that does not grow at all with the size of the input and is also polynomial in 1/\eps (the error parameter). In addition, their approach is simpler than previous algorithms on the same problem that achieved weaker guarantees.