UCL Computer Science


Student Profiles

Find out about the current PhD students at the Centre for Doctoral Training in Cybersecurity

From left: Niamh Healy, Sergi Bray, Antoine Vendeville, Antonis Papasavva, Henry Skeoch, Hawra Milani, Arianna Trozze 

Phil Demetriou

I am a Doctoral Student in the Center for Doctoral Training in Cybersecurity at University College London, advised by Prof Stephen Hailes and Dr Ingolf Becker and funded by the EPSRC. My research concerns anomaly and intrusion detection in the context of cyber-physical systems and critical infrastructure.

Read Phil's profile here

My research interests lie in Systems Security, Machine Learning and Distributed Systems and my prior industrial engagements include projects in link analysis, data aggregation, anomaly detection, semantic modelling, post-quantum cryptography and Byzantine Fault Tolerant protocol design.

Beyond my doctoral research, I organise the weekly UCL Computer Science Hacking Seminar and serve as postgraduate teaching assistant for COMP0016 Systems Engineering and SECU0043/SECU0049 Cybercrime.

Henry Skeoch

I was attracted to the Cyber Security CDT by the strong multidisciplinary training elements it contains and the opportunity to acquire structured knowledge across the various fields associated with cyber security alongside pursuing a PhD in one of the UK’s leading Computer Science Departments.

Read Henry's profile here

Being part of a cohort of students with diverse backgrounds and interests also greatly enhances the overall experience and creates a real sense of community as well as bringing a deep set of perspectives to the academic challenges we encounter.

My research aims to combine the established field of insurance economics with the newer area of security economics, with the goal of developing models able to offer useful practical insights into cyber insurance markets. Organisations and individuals are increasingly facing a rapidly evolving threat from activities in the cyberspace domain that have the potential to cause severe damage to information technology equipment and/or loss of confidential data, potentially incurring significant economic costs.

This has created a natural demand base for cyber insurance, but the market is underdeveloped especially outside the US. Many important related questions, such as whether cyber attacks are classified as an act of warfare and how to systematically model cyber attacks, present exciting research opportunities.

Prior to joining the Cyber Security CDT, I was employed as a Research Analyst for a major global investment bank focusing on interest rate and inflation markets, which followed an MSc in Finance from Imperial College Business School. Before changing paths to Finance, I was originally a Scientist graduating with an MSci in Natural Sciences (Chemistry) from the University of Cambridge with a final year project focused on Chemical Informatics, specifically systematic extraction of information regarding current research activities.

Hawra Milani

After spending the beginning of my career in computer hardware engineering, I moved to software engineering during my university years, and then made a career change into education, where I trained to teach computer science in secondary schools.

Read Hawra's profile here

Through that experience, I realised the lack of girls entering the field and the effects this was having on future generations, and thus decided to focus my studies in 'gender in computing'.

I went on to study a Masters in Computing Education at King's College, which also involved a level of research on cyberbullying in schools, and its effects on students' wellbeing. This interest pushed me to combine my knowledge and experience in computing and education to follow up with a PhD in Cyber Security.

I am really happy to be part of UCL's CDT in Cyber Security, where I feel supported in an environment where all backgrounds are celebrated, and that I am able to use my research skills to contribute to an interdisciplinary atmosphere, knowing I will always have experts in a variety of fields guiding me throughout my research projects.

The title of my PhD thesis is: "Using Machine Learning and Natural Language Processing to automatically detect cyberbullying within educational institutions in order to predict and prevent such occurrences."

A summary: Bullying affects millions of children throughout the world each year. The Department for Education states that in the UK alone, 1 in 6 children aged 10-15 have reported being bullied, and 7% of these children have experienced some form of cyberbullying and cyberthreats made to them.

Automatic cyberbullying detection is a task of growing interest, particularly in the Natural Language Processing and Machine Learning communities. As a result, it can be used to prevent individuals from receiving harmful online content in social networks, therefore aiding in the reduction of the incidence of cyberbullying.)

Antoine Vendeville

I graduated and proceeded to complete a Master’s degree in mathematics in France. I did two research internships on the mathematical modelling on social networks and developed a keen interest on the subject. I was then eager to conduct deeper research in that area, and the CDT Cybersecurity gave me the perfect opportunity to do so.

Read Antoine's profile here

I applied for a PhD project regarding fake news propagation and was very happy when I got accepted. I now have the chance to be working on the topic that drives my interest, in a prestigious academic environment under the guidance of top-world researchers.

My PhD project revolves around the question: How may a group of user be able to prevent sufficiently in time the spreading of some undesirable piece of content among them?

As Online Social Platforms have gained a lot of importance over the past years, I aim to develop mathematical methods to describe how users of such platforms form their opinions and influence one another.

We are in dire needs of such analysis as social media have quickly become part of our everyday lives, and users regularly find themselves to be the target of malicious attacks: fake news, illegal advertising campaigns, bot invasions and more.

The goal of my research is to give us a better understanding on the social structure and opinion dynamics in these networks, which could in turn help us prevent such episodes.

Arianna Trozze

I am a PhD researcher at UCL’s CDT in cybersecurity, focusing on financial crime. My academic and research experience has primarily centred on international policy and human geography, with a particular emphasis on environmental policy and international information and communication technology (ICT) policy.

Read Arianna's profile here

I completed my master’s thesis at the University of Oxford in 2015 on deliberative democracy and international ICT policy and my honours undergraduate thesis at Franklin University Switzerland in 2014 on ICT policies across Latin America.

During and following my master’s degree, I worked for the United Nations International Telecommunications Union in Geneva, focusing on digital inclusion initiatives and policies. After working in international policy for approximately a year, I found myself more interested in the enforcement arena and joined an international litigation firm.

As a legal analyst, I assisted lawyers on government enforcement defence and international judgment enforcement matters. I later joined the company’s corporate strategy department as the product manager for internal investigations and monitorships and asset forfeiture defence. My roles at this company sparked my deep academic interest in financial crime and money laundering research.  

My PhD research involves detecting and prosecuting financial crime involving cryptocurrencies. My project will adapt data science-based fraudulent transaction detection methods used in traditional financial services to the cryptocurrency market and demonstrate how they can be used to effectively prosecute financial crimes involving cryptocurrencies.

The results of this project will provide a roadmap for prosecution of these offences, as well as an empirical basis for policymakers to develop evidence-based legislation surrounding digital currencies worldwide. It will also enable innovation, facilitating the entry of conventional financial services companies into the cryptocurrency arena by providing a method for conducting due diligence on these transactions in the absence of accepted anti-money laundering processes.

Niamh Healy

I began my university education studying Law with International Law. A year abroad at the University of Leiden exposed me to the field of international relations and I realised this where my real academic interest lay. After I graduated from my BA, I began an MA in National Security Studies with King’s College London’s War Studies department. 

Read Niamh's profile here

Following this MA I worked for a small consultancy working on different security issues, mainly nuclear non-proliferation. While working here I became interested in the international political aspects of cyber security, particularly how cyber security issues affect nuclear order and other nuclear weapons issues.

It’s exciting to join the Centre for Doctoral Training, especially as someone from a non-technical background. I’m really enjoying learning from and with my cohort about all aspects of cyber security. 

My research approaches the question of cyber from an international relations perspective. I was originally focused on how ‘cyber’ was affecting how we make sense of nuclear weapons internationally (‘global nuclear order’) but I am increasingly interested in how ‘cyber’ is affecting how we make sense of international order generally, with specific reference to the English School. I am particularly interested in global governance on cyber, including the UN’s new Open-Ended Working Group as well as other bodies like the UN Group of Governmental Experts and the Global Commission on the Stability of Cyberspace.

Antonis Papasavva

I am a PhD Student under the supervision of Prof Emiliano De Cristofaro. In 2016 I received my BSc degree in Computer Science from Frederick University of Cyprus where my research was in the fields of robotics, unmanned surface vehicles, and autopilot software systems.

Read Antonis' profile here

The work and efforts of my BSc research resulted in two IEEE publications. 

In 2019 I received my MSc degree in Data Science and Engineering from the Cyprus University of Technology. During my studies at the Cyprus University of Technology my research focused on device-centric authentication, federated identity management, cyber safety, and the detection and characterization of inappropriate content online. I have demonstrated experience with working on EU-funded projects. Specifically, I took over highly responsible roles and actively contributed to ReCRED, CONCORDIA, and ENCASE projects. Part of the research I conducted during my MSc studies is published in one of the most influential conferences on Social Media Measurement: AAAI CWSM.
Currently, my research focuses on the characterization and detection of racism, misogyny, and other types of discriminating behaviour in mainstream and non-mainstream online social networks, large scale data processing, and deep learning networks.

Sergi Bray

When I tell someone that I completed a BA (/MA Ox) in Classics – that is, Ancient Greek and Latin literature, language, and philosophy – before taking on an MSc degree in Computer Science, I usually get a quizzical eyebrow or two. What does Plato have to do with Python? What do the humanities have to offer the sciences, and vice versa?

Read Sergi's profile here

My response is, invariably, everything – and in both directions. Technology is in effect a toolkit. The tools do not act on their own: humans can pick them up and use them, and it is from this that any boon or harm will come.

Humans can use tools to do great things: to save lives, to explore new dimensions, to make the world a safer place. In attempting to reach these goals, however, a split often occurs due simply to the continuation of a tradition in which study is boxed into distinct disciplines – a tradition which has been useful but which in a growing array of domains is no longer valid. The extent to which technology has involved itself in humanity’s everyday life means that there are urgent problems in this joining of science and humanity. Many of these problems end up under the umbrella term “cybersecurity”, simply for the reason that technology has met humanity in a way that endangers any elements of society ranging from the international to the private and personal.

Being lucky enough to find a Centre for Doctoral Training that shares my mindset, and to get onto its PhD programme, I am eager to waste none of the opportunity that I have been given. Problems abound at this intersect between disciplines: I will be focusing on an emergent technology whose meeting with humanity will resonate across innumerable domains. A “Generative Adversarial Network” is a type of Machine Learning invented in 2014 which has since catalysed the development of “talking head” synthesis, among other technologies, producing convincingly realistic fake media colloquially known as “deepfakes”. We have recently reached the stage at which this development threatens the trust that we currently place in visual and auditory evidence. Until now, it has been impossible or at least very costly to realistically fabricate, or to unnoticeably manipulate, such evidence. A great number of systems will be at risk due to this nascent technology, and protections need to be put into place as fast and as effectively as possible.

My PhD research will evaluate the threat that this technology poses via the UK’s systems of news propagation, and will attempt to propose low-cost technical solutions that would fix the problem in the right way, alongside work supporting policy proposals that would implement such solutions. A clue to understanding what “the right way” will be is the fact that the development of “deepfake detection” technologies will be an arms race in which we must assume that we are behind our opponent: this means that the only solutions will be found in ways that are relevant to the contexts of the domains that this threatens. The context of each case will be a different complex systematic blend of humanity and technology, which is part of what makes these problems such enjoyable and rewarding challenges