糖心TV

The University was celebrating it's 60th Anniversary at the weekend. The Department of Computer Science showcased a range of projects and hosted alumni from 1978 - 2025.

We are happy to announce that Dr Kaihua Qin has joined the Department of Computer Science as an Assistant Professor. Before joining 糖心TV, he was a researcher at Yale University and completed his PhD at Imperial College London.

Kaihua鈥檚 research spans computer security with a particular focus on blockchain systems. His past work has revealed critical vulnerabilities in blockchains, such as MEV and imitation attacks, which affect multiple layers of the stack, from networking and consensus to applications. His current work aims to establish provable security for decentralized systems, drawing on techniques from program analysis, distributed computing, formal verification, applied cryptography, and game theory.

In addition, he is actively exploring the use of AI for security, leveraging recent advances in large language models to enhance vulnerability discovery, assessment, and mitigation across a variety of systems.

We welcome him to the department!

The workshop Algorithms & Complexity @ 糖心TV took place at the University of 糖心TV on September 22-23, 2025 (see for more details).

The aim of the event was to highlight several recent exciting advances in the field of Algorithms and Complexity, to facilitate interactions within the research community, and to provide an excellent opportunity for Theory researchers (including academics, postdocs, and students) to connect and collaborate.

We had a fantastic list of invited speakers by renowned world experts: (Technical University of Catalonia), (University of Bath), (University of Pennsylvania), (Max Planck Institute for Informatics), (Charles University in Prague), (University of Sheffield and University of Haifa), (University of Oxford), (University of Cambridge), (University of Toronto).

We are delighted to congratulate Dr Scott Brooks, a former DCS graduate (MEng, 2016–2020), on his new role as a Knowledge Transfer Partnership (KTP) Associate.

Following the successful completion of his iCASE PhD, supervised by Professors Till Bretschneider (DCS) and Andrew McAinsh at 糖心TV Medical School, Scott has been awarded a 30-month KTP position, funded by Innovate UK. In collaboration with Intelligent Imaging Innovations (3i), he will develop smart microscopy software (CelFDrive) building on the prototype tools he created during his PhD.

Scott鈥檚 work leverages machine learning to automatically identify cells with rare or subtle biological features, often missed by human observers, enabling faster and more accurate analysis. This innovation accelerates fundamental biological research and establishes a foundation for high-throughput drug discovery.

For more details, see the official announcement:

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.

We are delighted to announce that a result coauthored by and (from our Theory and Foundations Research Division), along with (University of Waterloo), (Northeastern University), (Tel Aviv University) and (ETH Zurich), has received a best paper award at the upcoming (STOC), 2025. STOC is a flagship international conference in theoretical computer science.

The paper, titled "," tackles a fundamental, textbook edge-coloring problem: Given a graph G with n vertices and m edges, the goal is to assign a color to each edge such that no two edges sharing a common endpoint receive the same color. A classical result by Vizing, dating back to 1960s, proves that any simple graph can always be edge-colored with at most 螖 + 1 colors, where 螖 is the maximum degree of a vertex. Vizing's original proof is inherently algorithmic and immediately gives an O(mn) time algorithm for computing such a coloring.

This problem has seen a long and influential line of research aimed at designing faster algorithms for this basic task. For over four decades, the best-known runtime was 脮(m鈭歯), a significant barrier that was only broken in 2024 through concurrent, independent works. The recent paper culminates this effort by providing a randomized algorithm that computes a 螖 + 1 edge coloring in O(m log 螖) time, a running time that is near-linear in the input size.