Skip to main content
Dr Alexia Zoumpoulaki

Dr Alexia Zoumpoulaki


School of Computer Science and Informatics

Available for postgraduate supervision


I am a Lecturer (assistant professor) in Computer Science and Informatics at Cardiff University, UK, specialising in AI, machine learning for Human Factors Applications. In the past I have worked in various interdisciplinary research projects, including memory classification, deception detection and crowd simulations. A lot of my work has focused in developing methods for analysing and classifying time series data.

Currently I am interested on multimodal processing of videos. Facial (micro) expressions - emotion recognition, text analysis, voice analysis in the area of deception detection using machine learning. I am interested in incorporating features extracted from these modalities with other psychological factors as well as features from eyetracking.

Broadly I am interested in congitive (computational) (neuro) science and how computer science can help model behaviour and cognitive processes. This understanding will help us build exciting new applications.


  • PhD in Computer Science (Computational Neuroscience) - University of Kent, Canterbury, UK
  • MSc in Advanced Computer Science (Computational Intelligence): Distinction - University of Kent, Canterbury, UK
  • MSc Product & Systems Design Engineering: Distinction - University of the Aegean, Syros, Greece
  • BEng Information & Communication Systems Engineering - University of the Aegean, Samos, Greece










Computational Thinking CM6114/CM6614: The course aims to enable students to translate real world problems into computer code. The focus is on developing the ability to apply core concepts by writing code that solves basic problems, laying the foundation for productive coding in later modules. On successful completion of this module, it is expected that students are able to approach problems in a computational way through logical thinking, reformulation, abstraction, decomposition and appropriate data representation. Students will also develop a basic understanding of the most popular problem solving algorithms (search, sort, routing, resource allocation), describe them in a scientific way and evaluate their complexity. Finally, they will cover how information is stored and accessed in a computer and they will be able to translate across different number systems.

Undergraduate and Postrgraduate project supervision: Past and current projects include: 

  • High Frequency Oscillation Detection Using Wavelet Analysis and Convolutional Neural Networks
  • Deception Detection in Text with Tranfer Learning
  • An Application for Comparing and Visualising M/EEG Pre-processing Pipelines
  • Detecting Lies using Eyetracker and video analysis
  • An Explorative Study into the Effects of Visualisation On Deception Detection Accuracy
  • Multimodal deception detection in Videos with Deep Learning

Research interests

I am interested in applying AI, machine learning techniques to build human factors appliactions, focusing on areas suchs as attention, multitasking and decision making. I am using physiological measurements such as gaze, pupil dilation, eeg in combination with video, text and voice analysis to study the above areas. 

I am interested in behaviours under stressful situations, and how to develop technologies to help humans with decision making and task perfomance. 

I have expertise in analysing and classifying neuroimaging/time series data.


I am currently looking to support PhD applications in the area of automatic deception detection. 

I am also interested in supervising PhD students in the areas of:

  • Video analysis - automatic micro expressions, gestures detection
  • Text analysis - deception detection using machine learning/neural networks
  • Voice analysis - features for deception detection
  • Eyetrackers - feature extraction for classification
  • HCI - visual attention, multitasking and problem solving - using eyetracking and/or neuroimaging

Current supervision

Asmail Muftah

Research student

Andrea Rossi

Research student