Bonjour à tous,

Nous avons le plaisir de vous inviter au troisième séminaire de la session d'hiver 2021 du LATECE. 

Lieu: Zoom : https://uqam.zoom.us/j/85977067999

Titre: Affective computing in real and immersive environments

Conférencier :Tiago H. Falk

Abstract: Real-time measurement of a user’s mental state can be fundamental for reliable human-machine interaction (HCI), operator functional state assessment, quality-of-experience measurement, and remote patient monitoring, to name a few applications. Measuring such factors, however, can be challenging, specially when dealing with ambulant users under multi-tasking situations. In this talk, I will review some of the work we have done at the MuSAE Lab (INRS-EMT, University of Quebec) on measuring human affective states in highly ecological settings, ranging from nurse burnout in hospitals, to first responders' mental workload and stress levels, to arousal and valence states while interacting with voice-control HCIs. Challenges regarding movement artifacts, confounding factors, and context-awareness will also be addressed. Finally, I will describe our latest developments in embedding sensors directly into a virtual reality headset, thus allowing for real-time tracking and assessment of immersive media experience.

Bio : Tiago H. Falk is an associate professor in INRS-EMT and director of the Multimedia/Multimodal Signal Analysis and Enhancement (MuSAE) Laboratory. He is also an Adjunct Professor at McGill University (ECE Dept.) and an Affiliate Researcher at Concordia University (PERFORM Centre). Prof. Falk is a Senior Member of the IEEE, an elected member of the Global Young Academy (GYA), a member of the Sigma Xi Research Society, Academic Chair of the Canadian Biomedical and Biological Engineering Society, Co-Chair of the IEEE SMC Brain-Machine Interface Technical Committee, a Board-of-Governor’s member of the IEEE SMC Society, and a voted member of the IEEE SPS Audio and Acoustic Signal Processing Technical Committee (2018-2020; 2021-2023). His research interests lie at the crossroads of signal processing and machine learning, with the former providing contextual cues and intelligence to the latter. Applications across numerous domains, including affective human-machine interfaces, human-inspired multimedia/immersive technologies, and in-the-wild human performance/health monitoring, have been explored. He received the BSc degree from the Federal University of Pernambuco, Brazil, in 2002, and the MSc and PhD degrees from Queen’s University, Canada, in 2005 and 2008, respectively, all in electrical engineering.