Beatrice Biancardi

Beatrice Biancardi is a Teacher-Researcher (Associate Professor) at CESI LINEACT, a research laboratory within CESI, a French engineering school network. Her work focuses on the intersection of human behavior analysis and artificial intelligence, with particular emphasis on social signal processing and human-machine interaction.

Dr. Biancardi's educational background includes:

• Doctorate in Human-Computer Interaction from Sorbonne University (2016-2019)
• International Master in Cognitive Sciences, Language and Multimodal Interaction from University of Trento (2013-2015)
• Degree in Applied Cognitive Psychology from University of Trento (2010-2013)

Her primary research interests center around understanding human social behavior through computational methods, with specific focus on social signal analysis, human-human and human-machine interaction, group dynamics, virtual agents, and non-verbal behaviors. She develops computational models to analyze and replicate human social behaviors in virtual environments, particularly in contexts of public speaking, team collaboration, and social interaction with AI systems.

Analysis of her publication record reveals consistent focus on transactive memory systems in group interactions, multimodal analysis of social behaviors, and the development of virtual agents capable of sophisticated social interaction. Her work bridges cognitive science, computer science, and social psychology, with increasing emphasis on practical applications in training and educational contexts.

Her scientific recognition includes:

• Nomination for Best Article at the 22nd ACM International Conference on Multimodal Interaction (ICMI) 2020 for her work on the WoNoWa Dataset

Dr. Biancardi actively supervises doctoral research, currently guiding three PhD candidates on projects related to collective intelligence in immersive environments, multimodal attention models for public speaking evaluation, and avatar embodiment in virtual training environments. Her educational activities span multiple disciplines including human-computer interaction, statistics, research methodology, and innovation, teaching across various engineering programs at the 3rd, 4th, and 5th year levels.

As a member of the CESI LINEACT research team, she contributes to advancing knowledge in social signal processing and human-machine interaction, with her work having significant implications for virtual training environments, public speaking education, and collaborative AI systems.