This project leverages recent advancements in conversational artificial intelligence (AI), speech-to-text, natural language understanding (NLU)[1], and finite-state machines to automate protocols, specifically in research settings. This application must be generalized, fully customizable, and irrespective of any research study. These parameters allow new research protocols to be created quickly once envisioned. With this in mind, I present SmartState, a fully-customizable, state-driven protocol manager combined with supporting AI components to autonomously manage user data and intelligently determine the intention of users through chat and end device interactions to drive protocols.

[1] T. Bocklisch, J. Faulkner, N. Pawlowski, and A. Nichol, Rasa: Open source language understanding and dialogue management, 2017. DOI: 10.48550/ARXIV.1712.05181. [Online]. Available:

Code: GitHub

arXiv Link: SmartState: A Protocol-Driven Human Interface, Submitted to AMIA 2023 Annual Symposium