PhD

PGR Seminar with Leonid Nosovitsky + Xinya Gong

The next PGR seminar is taking place this Friday 11th April at 2PM in JC 1.33a

Below are the Titles and Abstracts for Leonid and Xinya’s talks – Please do come along if you are able.

Leonid Nosovitsky

Title: Bridging Theory and Practice: Advancing Multiparty Session Types for Industry Use

Abstract: Multiparty Session Types (MPST) provide a typing discipline for communication protocols. They allow to statically check that a code implementation conforms to a specified protocol; they can also verify that a protocol satisfies many safety properties like liveness and deadlock freedom, which are crucial in concurrent communicating systems.  Despite huge improvements in MPST research, different extensions have limitations.  For example, one of extensions is crash-handling. This branch was motivated by lack of network reliability to make MPST framework more applicable and usable in industrial scenarios. The crash-semantics theory introduced by Barwell et al. does not involve any constraints relaxations, which makes it very intricate for adoption in practical scenarios.  Our project concentrates on addressing usability limitations to make MPST more integrable into industrial applications.

Xinya Gong

Title and Abstract TBC

PGR Seminar with Zihan Zhang + Berné Nortier

The next PGR seminar is taking place this Friday 4th April at 2PM in JC 1.33a

Below are the Titles and Abstracts for Zihan and Berné’s talks – Please do come along if you are able.

Zihan Zhang

Title: FedOptima: Optimizing Resource Utilization in Federated Learning

Abstract: Federated learning (FL) systems facilitate distributed machine learning across a server and multiple devices. However, FL systems have low resource utilization limiting their practical use in the real world. This inefficiency primarily arises from two types of idle time: (i) task dependency between the server and devices, and (ii) stragglers among heterogeneous devices. We propose FedOptima, a resource-optimized FL system designed to simultaneously minimize both types of idle time; existing systems do not eliminate or reduce both at the same time. FedOptima offloads the training of certain layers of a neural network from a device to server using three innovations. First, devices operate independently of each other using asynchronous aggregation to eliminate straggler effects, and independently of the server by utilizing auxiliary networks to minimize idle time caused by task dependency. Second, the server performs centralized training using a task scheduler that ensures balanced contributions from all devices, improving model accuracy. Third, an efficient memory management mechanism on the server increases scalability of the number of participating devices. Four state-of-the-art offloading-based and asynchronous FL methods are chosen as baselines. Experimental results show that compared to the best results of the baselines on convolutional neural networks and transformers on multiple lab-based testbeds, FedOptima (i) achieves higher or comparable accuracy, (ii) accelerates training by 1.9x to 21.8x, (iii) reduces server and device idle time by up to 93.9% and 81.8%, respectively, and (iv) increases throughput by 1.1x to 2.0x.

Berné Nortier

Title: Shortest paths and optimal transport in higher-order systems

Abstract: One of the defining features of complex networks is the connectivity properties that we observe emerging from local interactions. Nevertheless, not all networks describe interactions which are merely pairwise. Recently, different frameworks for modelling non-dyadic, higher-order, interactions have been proposed, garnering much attention. Of these, hypergraphs have emerged as a versatile and powerful tool to model such higher-order networks. However, the connectivity properties of real-world hypergraphs remain largely understudied. A first, data-driven, work introduces a measure to characterise higher-order connectivity and quantify the relevance of non-dyadic ties for efficient shortest paths in a diverse set of empirical networks with and without temporal information. The analysis presents a nuanced picture.

A second work (in progress) considers higher-order simplicial networks within the context of optimal transport, where shortest paths do not always lead to optimal resource allocation. We extend the existing framework to the higher-order setting to explore to what degree this additional degree of freedom influences the flux of resources in a system of interest.

Distinguished Lecture Series 2025

This years Distinguished Lecture series was delivered yesterday ( Tuesday 1st April) by Professor Arthur Zimek, University of Southern Denmark in Odense, Denmark.

In his talk on, ‘Data Mining and the “Curse of Dimensionality”’ he considered the challenges of the “curse” from the perspective of data mining. In Talk 1, he discussed the “curse” in more detail, identifying relevant aspects or problems. In Talk 2, he considered clustering facing these problems and discussed some strategies and example methods for subspace clustering. In Talk 3, he discussed outlier detection, considering strategies for improved efficiency, effectiveness, and subspace outlier detection.

PhD student project showcase in CyberASAPY8 Demo Day

A group of PhD students: Yaxiong Lei and Zihang Zhang, in our school have been awarded a CyberASAP project. This is funded by the Department of Science, Innovation, and Technology (DSIT) and organised by InnovateUK. CyberASAP aims to fund innovative cybersecurity solutions from academics. Their project, LockEyeGaze, confronts the cybersecurity challenge of sophisticated computer vision and 3D modelling technologies such as deepfake and AI-generated tampering. They are leveraging the dynamic patterns of eye movements for security, which are significantly more difficult to replicate than static biometric features like static face, iris and fingerprints. Their project is selected to present at CyberASAP Year 8 Demo Day in Canary Wharf, London today.

Links:

https://web-eur.cvent.com/event/4a986031-294f-4ad0-9a9b-a4863690bd19/summary

https://iuk-business-connect.org.uk/events/cyberasap-year-8-demo-day/

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! 🎉

 

PGR Seminar with Mustafa Abdelwahed and Maria Andrei

The next PGR seminar is taking place this Friday 6th December at 2PM in JC 1.33a

Below is a title and Abstract for Mustafa and Maria’s talks – Please do come along if you are able.

Mustafa Abdelwahed:

Title: Behaviour Planning: A toolbox for diverse planning

Abstract:

Diverse planning approaches are utilised in real-world applications like risk management, automated streamed data analysis, and malware detection. These approaches aim to create diverse plans through a two-phase process. The first phase generates plans, while the second selects a subset of plans based on a diversity model. A diversity model is a function that quantifies the diversity of a given set of plans based on a provided distance function.

Unfortunately, existing diverse planning approaches do not account for those models when generating plans and struggle to explain why any two plans are different.

Existing diverse planning approaches do not account for those models when generating plans, hence struggle to explain why any two plans are different, and are limited to classical planning.

To address such limitations, we introduce Behaviour Planning, a novel toolbox that creates diverse plans based on customisable diversity models and can explain why two plans are different concerning such models.

Maria Andrei: 

Title: Leveraging Immersive Technology to Enhance Climate Communication, Education & Action

Abstract: Climate change represents one of the most pressing challenges of our time, not only in its environmental impacts, but also as a pivotal science communication problem. Despite widespread scientific consensus on the causes and mitigation strategies for climate change, public understanding remains deeply fragmented and polarized. This disconnect hinders the collective action required from individuals, organizations, and policymakers to combat global warming effectively. My research explores the potential of immersive technologies to bridge the gap between scientific knowledge and public understanding by leveraging experiential learning experiences to inspire the attitudinal and behavioural shifts necessary to address climate change.

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 adding imperceptible perturbations to clean images. These adversarial perturbations, though invisible to human eyes, can cause neural networks to produce incorrect outputs, making adversarial examples a significant security concern in deep learning. While previous research has primarily focused on designing powerful attacks to expose neural network vulnerabilities or using them as baselines for robustness evaluation, our work takes a novel perspective by leveraging adversarial examples to counter malicious uses of machine learning. In this seminar, I will present two of our recent works in this direction. First, I will introduce the Locally Adaptive Adversarial Color Attack (LAACA), which enables artists to protect their artwork from unauthorized neural style transfer by embedding imperceptible perturbations that significantly degrade the quality of style transfer results. Second, I will discuss our Posterior Collapse Attack (PCA), a grey-box attack method that disrupts unauthorized image editing based on Stable Diffusion by exploiting the common VAE structure in latent diffusion models. Our research demonstrates how adversarial examples, traditionally viewed as a security threat, can be repurposed as a proactive defense mechanism against the misuse of generative AI, contributing to the responsible development and deployment of these powerful technologies.

AI Seminar Wednesday 27th November – Lars Kotthoff

We have another exciting AI seminar coming up on Wednesday 27th November at 1pm.

This time our speaker is an alumnus!

When? 27/11/24, 1pm

Where? JCB 1.33B

Who? Lars Kotthoff

Lars Kotthoff is the Templeton Associate Professor of Computer Science, Founding Adjunct Faculty at the School of Computing, and a Presidential Faculty Fellow at the University of Wyoming. His research in foundational AI and Machine Learning as well as applications of AI in other areas (in particular Materials Science) has been widely published and recognized. Lars is a senior member of the Association for the Advancement of AI and the Association of Computing Machinery.

What?

Title: AI for Materials Science: Tuning Laser-Induced Graphene Production

Abstract: AI and machine learning have advanced the state of the art in many application domains. We present an application to materials science; in particular, we use surrogate models with Bayesian optimization for automated parameter tuning to optimize the fabrication of laser-induced graphene. This process allows to create thin conductive lines in thin layers of insulating material, enabling the development of next-generation nano-circuits. This is of interest for example for in-space manufacturing. We are able to achieve improvements of up to a factor of two compared to existing approaches in the literature and to what human experts are able to achieve, in a reproducible manner. Our implementation is based on the open-source mlr and mlrMBO frameworks and generalizes to other applications.

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 to industrial processes. The planning task consists of selecting a sequence of actions to achieve a specified goal from specified initial conditions. The Planning Domain Definition Language (PDDL) is the leading language used in the field of automated planning to model planning problems. Previous work has highlighted the limitations of PDDL, particularly in terms of its expressivity. Our interest lies in facilitating the handling of complex problems and enhancing the overall capability of automated planning systems. Unified-Planning is a Python library offering high-level API to specify planning problems and to invoke automated planners. In this paper, we present an extension of the UP library aimed at enhancing its expressivity for high-level problem modelling. In particular, we have added an array type, an expression to count booleans, and the allowance for integer parameters in actions. We show how these facilities enable natural high-level models of three classical planning problems.

Doughnuts will be available! 🍩