The abstraction of humans with a signals and systems framework naturally brings a synergy between engineering and behavioral sciences. Behavioral signal processing (BSP) offers a new frontier of interdisciplinary research between these communities. The core research in BSP is to model human behaviors, internal states, and perceptual judgement using computational methods grounded in signal processing and machine learning. The outcome of BSP offers novel behavioral analytics to enhance the current decision-making capabilities of domain experts.
In this talk, we will describe our research effort in developing BSP techniques in various application domains, specifically health and education research. The heterogeneity in human behavior expression, the subjectivity in human perceptual judgement, and the complex non-linear interplay of multiple factors require not only an advancement in algorithmic development but also a tight collaboration with domain experts. With this emerging effort of BSP, we strive not only to provide contextualized engineering solutions to domain experts but also to open up opportunities of novel insights in applications with broad societal impact.