Valentina Markova

Papers

Total Citations

115

H-Index

About

Valentina Markova is a leading researcher in affective computing and human-computer interaction, with a primary focus on the automated recognition of cognitive and emotional states. Her most influential contribution is the development of the CLAS database (Cognitive Load, Affect and Stress Recognition), a multimodal resource that has garnered over 115 citations since its publication in 2019. This dataset, designed to support research and technology development, provides a standardized foundation for building systems that can detect cognitive load, emotional affect, and stress from physiological and behavioral signals. Markova’s work directly addresses the challenge of creating machines that can understand and respond to human mental states, with applications ranging from adaptive learning environments to mental health monitoring. Her research is notable for its rigorous experimental design and its emphasis on real-world applicability, bridging the gap between laboratory studies and practical deployment. Through the CLAS dataset and her ongoing investigations, Markova has established herself as a key figure in advancing the field of affect-aware technology, enabling more intuitive and responsive human-machine interactions.