* **2020 WITS Best Paper Award**
* **2021 HICSS Best Paper Nomination**
We propose a deep learning approach which incorporates prior domain knowledge into a principled probabilistic matrix factorization framework to enhance complain behavior predictions as well as their interpretability.
We systematically evaluated evidence from controlled studies of interventions using virtual humans on their effectiveness in health-related outcomes. The design and implementation characteristics of these systems were also examined.