- George Magoulas
- London, United Kingdom
- I conduct interdisciplinary research that seeks to enable systems to exhibit different levels of intelligence, learn from data and transfer knowledge to new contexts. My latest projects are in deep learning for psychophysiological data modelling and classification, and in intelligent learning environments. I design and develop innovative learning algorithms, system components that employ machine learning, sometimes combined with knowledge engineering, learner models and intelligent tutors. I was educated at the University of Patras, Greece (BEng/MEng, Dr. Eng), and hold a PGCE (Brunel University, UK). Before joining academia I held R&D positions in the cement and automotive industries working on embedded systems that used soft computing and machine learning methods. My research received best paper awards from the IEEE (2000 and 2008), the European Network on Intelligent Technologies for Smart Adaptive Systems (2001 and 2004), the International Association for Development of the Information Society (2006), the ACM (2009) and KES International (2010). I am a Fellow of the Higher Education Academy, and a Member of the EPSRC College, UK.
8 Oct 2016
Deep Incremental Boosting at GCAI 2016.
Learning Input Features Representations in Deep Learning
Regularizing Deep Learning Ensembles by Distillation at ECAI's CIMA 2016.
Bounding the Search Space for Global Optimization of Neural Networks Learning Error: An Interval Analysis Approach in JMLR.
A Review, Timeline, and Categorization of Learning Design Tools at ICWL 2016; shortlisted for the ICWL 2016 best paper award.
Approaches to Design for Learning at ICWL 2016.
An Architecture for Smart Lifelong Learning Design at ICSLE 2016.
Ubiquitous Learning Architecture to Enable Learning Path Design across the Cumulative Learning Continuum, in Informatics.