Dr Elaheh (Ela) HomayounVala

Staff details

Position Lecturer in Computer Science
Department Computing
Email e.homayounvala (@gold.ac.uk)
Phone +44 (0)20 7 919 7856
Dr Elaheh (Ela) HomayounVala

Elaheh Homayounvala (PhD King’s College London) is a Lecturer in Computer Science at Goldsmiths, University of London. Her research is multi-disciplinary and is focused on Technology and People to understand how people interact with technology and how to adapt technology to needs and preferences of people, which are usually named “User Modelling and Personalisation”.

Research Interests

Some of her research topics are, but not limited to user modelling and personalisation, Human-Computer Interaction (HCI), adaptive and context-aware user interfaces, technology acceptance and persuasive technologies. Some of the research projects she has supervised so far are as follows:

  • User modelling and personalisation for context-aware augmented reality maintenance software
  • Personalisation and usability evaluation of mobile interactive recommender systems (In collaboration with Technical University of Munich)
  • Modelling and automatic detection of learners’ learning style in Moodle for personalised e-learning systems
  • Modelling learner’ knowledge level with Fuzzy Cognitive Maps for personalised e-learning systems
  • User preferences in health information systems
  • Adaptive user interfaces in health/e-learning
  • Usability and user acceptance evaluation of persuasive self-tracking applications
  • Usability evaluation of multimodal in-car user interfaces
  • Automatic usability evaluation of user interfaces (web and augmented reality user interfaces)
  • User acceptance of mobile augmented reality software in the tourism industry
  • Cross-system user modelling for social networking websites
  • Usability evaluation and adaptation of medical data visualisation
  • User-centric digital identity management systems



Homayounvala, Elaheh and Alavian Ghavanini, Sanaz. 2019. Comparing Usability and User Acceptance of two Mobile Mood Tracking Applications with Different Input Methods. International Journal of Technology and Human Interaction (IJTHI), ISSN 1548-3908

Conference or Workshop Item

Homayounvala, Elaheh; Nabati, Mohammad; Shahbazian, Reza; Ghorashi, Seyed Ali and Moghtadaiee, Vahideh. 2019. 'A Novel Smartphone Application for Indoor Positioning of Users based on Machine Learning'. In: UbiComp 2019 Workshop - AppLens. London, United Kingdom 9-10 September 2019.