Nsf Graduate Research Fellow (Nsf Grfp)
CurrentProposal Title: Discovering Digital Phenotypes of Childhood Internalizing Disorders for Point-of-Care DiagnosticsResearch Scientific Objective: Develop a digital health approach for assessing childhood anxiety and depression. By developing the digital health technology to identify anxiety and depression in young children, I aim to improve availability, sensitivity, and effectiveness of childhood mental health assessments.Research Output Objective: Facilitate broad access to mental health assessment for young children so that they can be directed to care when it has the highest chance of long-term success.Intellectual Merit Aims:(1) Leverage machine learning to discover digital phenotypes of childhood internalizing disorders(2) Develop a framework to optimize system architecture for cross-domain digital phenotyping (2a) Validating digital phenotyping platforms for this population can directly improve transdiagnostic digital phenotyping technologies overall through robust opensource feature extraction pipelines and validation frameworks.Broader Impacts Aims:Raise awareness on digital health toolkits for childhood mental illness detection, triaging, and intervention by...(1) Directly coordinate and conduct public speaking engagements to educate a variety of age groups on digital health(2) Design and conduct mini-workshops showcasing and testing the engineered platform(3) Host a small hackathon based on the developed opensource platform for 40 K-12 students