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Find out about the current PhD students at the Centre for Doctoral Training in Cybersecurity.
Cohort 3
Filippo Blancato
I am a doctoral student at UCL’s CDT in Cybersecurity, where I work under the supervision of Prof. Madeline Carr. At present, my research focuses on the geopolitical dimension of cloud computing. Starting from the observation that advancements in Cloud computing represent a crucial opportunity for economic development and competitive advantage, I intend to analyse the challenges the Cloud poses in terms of resilience, diversity, and data protection.
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Particularly, I am interested in investigating how polities such as the US, the UK and the EU try to reconcile the need for developing a competitive Cloud ecosystem with issues of dependency from (largely American) cloud providers and data sovereignty.
My background is in international relations and European Affairs. During my studies, I realized that is not possible to understand much about our world without appreciating the impact of technology on politics and society, and developed a keen interest in the subject. Thus, I integrated my knowledge with courses on issues such as the regulation of Artificial Intelligence and the impact of online disinformation on political polarization. As a research intern, I drafted policy briefs on the geopolitics of standard-setting, 5G and, IoT.
When I decided to pursue doctoral training, I was looking for an interdisciplinary program that would allow me to develop a technical understanding of today’s technologies while stressing the policy dimension of their use. The CDT in Cybersecurity, which focus on interdisciplinarity and actionable research, seemed to be the perfect fit for my ambitions. The program allows to work with people from a very diverse set of backgrounds, and I am convinced this to be the best approach to tackle the challenges that emerging technologies pose to our societies.
Prior to joining UCL, I worked at Microsoft’s Government Affairs office in Brussels, where I dealt mainly with cloud policy and regulation, as well as telecommunications policy and the cybersecurity of 5G networks. I also interned at the European Commission, where I worked in telecommunications and supported the implementation of a toolbox for the mitigation of cyber risks in 5G networks.
Jay Dwyer-Joyce
I’m a current PhD student with the Cybersecurity department at UCL supervised by Dr Steven Murdoch. I graduated with a BSc (Hons) Computer Science from Newcastle University and was looking to further my knowledge in computer science and cybersecurity in a way that is unique to me and that can advance research in the field.
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My research interests include classical cryptography and cryptographic certainty. Cryptographic certainty is the assurance that data has not been tampered with or manipulated, and that any changes are detectable. I am exploring how cryptographic certainty can be achieved with modern technologies and distributed systems such as blockchain. Also, different situations where cryptographic certainty is essential and how modern technologies can be applied to achieve verifiable systems.
Aliai Eusebi
I am a doctoral researcher in the Center for Doctoral Training in Cybersecurity at University College London (UCL), advised by Dr Enrico Mariconti, Dr Marie Vasek and Dr Ella Cockbain and funded by the EPSRC. I hold a BSc in Security and Crime Science from UCL and have completed study programmes in International Security and Intelligence at Cambridge University, and Machine Learning and Data Science at Fudan University.
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Before joining the CDT programme, I developed machine learning solutions for clients in the security domain for the identification, assessment, and management of risk in the arena of child exploitation with a key focus on machine learning transparency and explainability. My PhD research is designed to operationalise the role of ethics in AI in the defence domain, with an emphasis on online exploitation. Currently, the technical reality of machine learning is permeated by a constellation of ethical concerns related to transparency, fairness, and robustness, among others. Numerous soft governance mechanisms have emerged as a consequence, but a significant gap still exists between abstract principles (the ‘what’ of AI ethics) and practices. Hence, my PhD research aims to advance the question of ‘how’ to reach the ‘what’ when machine learning is employed in high impact and socially sensitive contexts.
Nadine Michaelides
Nadine Michaelides is a Sociotechnical Psychologist with a background in Stakeholder Engagement and Communications through high-profile Change and Transformation programmes. She has worked as an Expert Cyber Psychologist for the European Agency of Cybersecurity (ENISA), and supported multiple global organisations in securing their infrastructure and assets through the measurement of human factors and appropriate interventions.
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Research Summary - Human Factors of Cybersecurity - specifically the psychological contract and how this influences cybersecurity behaviour.
Marilyne Ordekian
I am a Ph.D. candidate at the CDT in Cybersecurity, supervised by Dr. Marie Vasek and Dr. Ingolf Becker. My current research interests lie in studying the interdisciplinary dilemmas arising from the intersection of regulation, businesses, and consumers within the cryptocurrency field. With the application of diverse methodologies, my research intends to highlight cybersecurity, privacy, and crime risks stemming from inapt policies and regulations.
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The ultimate goal is to provide regulators with interdisciplinary scientific evidence that assists in innovative and adequate policy-making.
I am also a licenced junior lawyer with a diverse spectrum of practice areas, ranging from criminal, commercial, and civil law to cybercrime and public policy. Before joining UCL, I was a member of a top-ranked international firm where I worked on emerging and disruptive technologies’ projects.
Academically, I hold a Bachelor’s and Taught Master’s degrees in Law, and a Research Master’s degree in Criminal/International Criminal Law (ranking first in my cohort). My dissertation, one of the first in the Middle East to address cryptocurrencies from a legal and criminal perspective, pinpointed regulatory loopholes under international and national laws. This work yielded two publications in collaboration with governmental agencies.
Demelza Luna Reaver
Demelza Luna Reaver is a PhD candidate in Cybersecurity at the Centre for Doctoral Training (CDT). Demelza’s research focuses on the use of technology as a tool to facilitate abuse within intimate partner relationships. This research seeks to develop a clearer understanding of the risks of technology-facilitated abuse for dynamic safeguarding purposes.
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Alongside providing support to domestic abuse services in their application of technology-facilitated safeguarding into achievable service interventions. Demelza is passionate in ensuring that her research provides visibility to marginalised communities who have been impacted by this form of harm. Prior to Demelza’s PhD candidacy, she was a Domestic Abuse Advocate and Tech Abuse Lead for charities such as; Refuge, and Advance, a service manager for the IRIS service at Victim Support, and within the Modern-Day Slavery and Human Trafficking sector with the charity Hestia as a caseworker. Demelza holds an MSc from the school of Psychology, Psychiatry, and Neuroscience at King’s College London (KCL) where she studied War and Psychiatry. Demelza holds her BSc from the school of Psychology at London South Bank University (LSBU) where she studied Clinical Psychology.
Charles Westphal
After completing my MChem in Chemistry in 2018 I worked as a cement scientist for a year. During this time, it became clear that I didn't have the programming or mathematics skills I needed to pursuit career paths I was interested in.
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For this reason, I completed an Msc in Physics at Leeds, where I specialized in using chaotic differential equations as a means to encrypt sensitive data. Specifically focusing on how chaos arises when operating on permutations. After my Msc I again did another year in industry, this time working as a research analyst in the telecoms market, before applying to UCL.
Here I am co-supervised by Prof. Mirco Musolesi and Prof. Steve Hailes, where my project focuses on using deep reinforcement learning to understand, predict and counteract deception and the spread of misinformation.
Karolina Skrivankova
My interests have long resided in the realm of systems - first following the medical science route to explore the systems of the human body, only to switch to studying man-made systems upon commencing my university studies.
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After finishing my undergraduate degree in Computer Science at UCL, I joined the Cybersecurity CDT as a doctoral student under the supervision of Steve Hailes, Mark Handley and Madeline Carr.
My research topic follows from my interest in systems and networks: how they are designed and built to fulfill desired properties in theirrespective environments. More specifically, I am looking at infrastructure systems (currently building systems) and the necessary aspects of distributed coordination, ecosystems and policy required to connect the system components to each other and/or the Internet without creating more chaos than benefit - an issue made more apparent via the direct links with the physical world characteristic of these systems accompanied by current industry standards. The aim of my project is to build foundations for sophisticated smart systems beyond the boundaries of a single organization in an effort to enable applications such as those touted by smart city visionaries (or whatever they call themselves).
I also spend my time as a postgradual teaching assistant for Principles of Programming (COMP0002), the Computer Science-specific part of Engineering and Professional Skills (ENGF0002) and Computer Systems (COMP0019).
Current students
Project Title: The Use of Computational Text-Mining Methods to Understand and Detect Intimate Partner Abuse. Summary: The project seeks to use computational text mining and information retrieval methods to research intimate partner abuse in large datasets. The work is currently in two parts: firstly, applying computational text mining to recognise reports of psychological abuse on social media forums, and examine the prevalence and content of these reports.
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Secondly, using computational text analysis to investigate the prevalence of Non-Fatal Strangulation and tech-facilitated stalking and harassment in a large dataset of police case summaries.