Institute for Analytics and Data Science

Completing your PhD with the Institute for Analytics and Data Science

The Institute for Analytics and Data Science at the University of Essex is globally renowned for its world-class interdisciplinary expertise in the analytics and data science to develop lasting solutions that transform the world for the benefit of individuals and communities.


Our experts include computer and electronic engineering scientists, statisticians and mathematicians, bioinformatics and biomedical scientists, social and political scientists, economists and finance experts, digital humanities experts, human rights experts, ethics and legal experts.

We are proud to have supported the generations of postgraduate researchers who go on to transcend disciplinary boundaries and create a real change in industries such as insurance, financial analysis and management, charities and NGOs, and the public sector, while also starting their own businesses and consultancy services.


Our research supervisors

IADS has a multidisciplinary and interdisciplinary research community of over 200 experts from three faculties and 13 disciplines. More information about our academics and researchers is available on the ‘Our people’ page.

Core institute members and alumni include:

Professor Haris Mouratidis

Professor and Director of IADS

School of Computer Science and Electronic Engineering (CSEE)

Supervision areas: Security and Privacy Requirements Engineering.

Dr Spyros Samothrakis

Senior Lecturer and Deputy Director of IADS

School of Computer Science and Electronic Engineering (CSEE)

Supervision areas: Reinforcement Learning, Machine Learning, Neural Networks, Role Playing Games.

Dr Amanda Cole


Department of Language and Linguistics

Supervision areas: Language Attitudes, Sociolinguistics, Language Variation and Change, Sociophonetics.

Dr Jennifer Hoyal Cuthill


School of Life Sciences

Supervision areas: Biological Machine Learning, Computational Palaeobiology, Quantifying Evolutionary Convergence, Ediacaran Palaeobiology and Palaeoecology

Professor Maria Fasli

Executive Dean (Science and Health) and Founding Director of IADS

School of Computer Science and Electronic Engineering (CSEE)

Supervision areas: Multi-Agent Systems and Autonomous Adaptive Systems, Data Exploration Analysing and Modelling Complex Data Big Data Analysis and Modelling of Structured and Unstructured Data, Machine Learning Modelling Opponents Learning Behaviours from Data, Reasoning and Analytics over Multiple Streams of Data Internet of Things (Iot) Reasoning and Analytics, Individual and Collective User Profiles Profile Adaptation Contextualised Profiles, Recommender Systems Collaborative Filtering Reputation Systems, Complex Systems Modelling Dynamics of Financial Systems and Markets, Market Mechanisms Negotiation Protocols Strategic Interaction Supply Chain Management, Semantic Matching Resource Search Cloud Computing Resource Allocation, Trust in Agent Societies Trust Mechanisms Trust in Decision Making, Formal Theories of Agents and Multi-Agent Systems BDI Agents, Cognitive Agents Knowledge and Belief Self-Reference, Software Engineering Methodologies for Agents and Multi-Agent Systems, Social Dynamics Regulation of Agent Societies Roles and Power Institutions, Self-Organisation Team Formation, Serious Games for Education and Learning Collaborative Learning.

Dr Ana Matran-Fernandez


School of Computer Science and Electronic Engineering (CSEE)

Supervision areas: Brain-Computer Interfaces, Machine Learning Applied to Biomedical Signals, Event-Related Potentials (ERPs), Memory, Neural Engineering.

Dr JunKyu Lee

Research Fellow

School of Computer Science and Electronic Engineering (CSEE)

Supervision areas: Energy-Efficient AI, Trustworthy AI, Machine Learning, Tinyml, Federated Learning, Kernel Methods, Signal Processing, Fpgas, Numerical Linear Algebra, Resource-Efficient Convolutional Networks, Real-Time Object Detection.

Dr Haider Raza

Senior Lecturer

School of Computer Science and Electronic Engineering (CSEE)

Supervision areas: Big Data and Analytics, Brain-Computer Interface, Deep Learning, Transfer Learning, Non-Stationary Learning and Domain Adaptation, Artificial Intelligence (AI) and eXplainable AI (XAI), EEG and MEG Signal Processing, EEG and MEG Signal Processing.

Past postgraduate research projects

Over the years students have researched many different themes and topics alongside the Institute:

  • Analysis of Some Domain Adaptation Methods in Causality
  • An Extended Ant Colony Optimisation Approach for the Mass Customisation Paradigm
  • Developing Event Identification Methods for Structured and Unstructured Data Streams
  • Developing Learning Methods for Non-Stationary and Imbalanced Data Streams
  • Did 9/11 Change Everything? Security and Human Rights Tradeoffs in International Cooperation
  • Enhancing Recommendations in Specialist Search Through Semantic Based Techniques and Multiple Resources
  • Exploring Embedding Vectors for Emotion Detection
  • Food Security and Preferential Trade Agreements
  • Modelling the High-Frequency Fx Market: An Agent-Based Approach
  • Natural Language Processing Methods for Short Informal Text
  • Resource Discovery in Self-Organising Distributed Systems
  • Social Media for Social Good: Understanding, Creating and Harnessing the Strength of Parasocial Relationships
  • Task Recovery in Self-Organised Multi-Agent Systems for Distributed Domains
  • Text Generation for Small Data Regimes

Study with us

Our expertise attracts major funding from UK research councils to deliver ground-breaking doctoral training programmes in a range of areas including:

  • exploring the most challenging social science issues of the 21st century
  • investigating the interplay between a person's biology, experiences and behaviour
  • artificial intelligence, machine learning, bioinformatics and genomic analysis of big data


Find out more about Postgraduate Research Study at Essex, including funding and how to apply

The Institute is superbly place to support doctoral research in any area of interest that engages with its remit. This includes students wishing to research the area of data science and analytics and study for a postgraduate research degree in other departments. Including: