26th of October, at 16h00, Haytham Hijazi will give a presentation entitled“Cognitive Load Monitoring Through wearables: A Machine Learning Perspective”
Location: G4.1
Bio
A Ph.D. research fellow, Centre of Informatics and Systems, University of Coimbra (CISUC), Coimbra, Portugal. Haytham Hijazi received a B.Eng. degree in Computer Systems Engineering from Palestine Polytechnic University with an excellent grade and an M.Sc. degree in Information Technology Engineering from the University of Stuttgart, Germany, in 2012 (a DAAD scholarship holder).
From 2012 to 2019, he worked with Palestine Ahliya University, Bethlehem, as a Lecturer, researcher, Data Centre Director, and Quality Assurance Manager.
Since 2019, Hijazi has been a Ph.D. Research Fellow with the Center for Informatics and Systems, University of Coimbra (CISUC). During this time, Hijazi published his work in top journals and conferences and translated one of his works into an internationally published patent application by WIPO.
Hijaz’s research interests include Explainable Machine Learning, Wearable Data Analysis, and Neuro Software Engineering (NeuroSE). His current thesis work focuses on developing intelligent biofeedback systems for augmenting content comprehension, including software engineering applications. Hijazi has broad managerial skills, including project management, academic quality assurance, and curriculum development.
Abstract
Although we are witnessing enormous growth in wearables technology (e.g., smart watches), which enables us to extract physiological measures daily, monitoring individuals’ cognitive load while performing a mental task (e.g., content comprehension) through these measures remains challenging.
Among those challenges are the inter- and intra-variability of individuals in exhibiting responses to mentally demanding tasks, models overfitting, and explainability issues.
This talk aims to introduce the results of the machine learning pipeline used in our work to predict comprehension difficulty in reading digital content using the Emaptica E4 wearable and a desktop eye-tracker. While showing the results, this talk will highlight the main challenges encountered and the measures to mitigate them.