Hichem Sahli studied Mathematics and Computer Science at Université Louis Pasteur –Strasbourg (France) and holds a PhD in Computer Science (Informatics/Photonics) from Ecole Nationale Sup. De Physique Strasbourg (France). Since 2000, he is Professor (20%) of Computer Vision & Machine learning in the Electronics and Informatics Dept. (ETRO) of the Vrije Universiteit Brussel, and Junior Scientists at the Interuniversity Micro Electronics Center (IMEC).

His research interests lie in the fields of health informatics, affective computing, computer vision, representation learning and machine learning.

Hichem Sahli has worked in computer vision, mathematical image and signal analysis, and machine learning since 1987. He has 27 completed PhD supervisions since 2000 when he joined VUB, coordinated 5 European projects. He has authored over 300 journal, conference publications and book chapters.

Here are his Google ScholarORCID

Research Interests 

Hichem’s team focuses on building the computational foundations to enable computers with the abilities to analyze, recognize and predict subtle human communicative behaviors during social interactions. Central to this research effort is the technical challenge of multimodal machine learning: mathematical foundation to study heterogeneous multimodal data and the contingency often found between modalities. This multi-disciplinary research topic overlaps the fields of multimodal interaction, social psychology, computer vision, machine learning and artificial intelligence, and has many applications in areas as diverse as medicine, robotics and education.

We conduct fundamental and applied research in

Multimodal Machine Learning

·       Probabilistic modelling of acoustic, visual and verbal modalities

·       Learning the temporal contingency between modalities

Human Communication Dynamics

·       Analyze, recognize and predict subtle human communicative behaviors during social interactions.

Health Behavior Informatics

·       Technologies to support clinical practice during diagnosis and treatment of mental health disorders