Dr. Carlos Gallo conducts research that aims to facilitate the implementation evidence based programs (EBPs) by local agencies, particularly those involved in reducing health inequities in the LGBT and ethnic minority’s populations. He is interested in developing computational methods that monitor and provide real-time feedback of implementation indicators useful for health care providers and funding agencies. He has successfully applied his knowledge in system engineering and computational linguistics in parent-training preventive interventions such as Familias Unidas and New Beginning Programs, funded by NIDA. His work has enhanced the delivery of programs that improves outcomes of Hispanic youth on risky sexual behavior, HIV, and drug abuse. He developed the first machine-based methods that recognize linguistic patterns that are evidence of therapeutic alliance between therapist and family during Familias Unidas home visit sessions. These linguistic patterns are linked to fidelity of implementation and are evidence high fidelity to EBPs protocol. He also developed signal engineering methods to automatically recognize emotion in spoken speech during a EBP delivery in recorded audio/video tapes. Important aspects of the EBPs delivery require providers to speak in specific manners that is either neutral or matches the clients emotions. His work sets the stage for efficient methods of measuring implementation and monitoring and feedback systems that closes the gap between research and practice, during the translation of EBPs in real world use.