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Using the readr package to sidestep a common problem


A guide to using the R-Ladies xaringan slide theme


A guide to getting up and running with blogdown, GitHub, and Netlify



Automated Measurement of Language Outcomes for Neurodevelopmental Disorders - NIDCD R01

Improving conversational use of spoken language is an important goal for many new interventions and treatments for children with neurodevelopmental disorders. However, progress in testing these treatments is limited by the lack of informative outcome measures to indicate whether or not an intervention or treatment is having the desired effect on a child’s conversational use of language (i.e., discourse skills). The goal of this project is to evaluate whether Natural Language Processing methods can be translated into meaningful outcome measure for individuals with a range of neurodevelopmental disorders. This project was recently funded by the National Institute of Deafness and Other Communication Disorders.

Multi-modal Autism Phenotype Snapshot (MAPS): Automated measurement of outcomes for children with autism

The goal of this project is to develop and validate a novel objective measurement tool, the Multi-modal Autism Phenotype Snapshot (MAPS), for use in clinical trials targeting core symptoms of autism. This project was funded by a Catalyst Award from the Oregon Clinical & Translational Research Institute.

Computational Characterization of Language Use in Females and Males with Autism Spectrum Disorder

The objective of this project is to further understanding of sex differences in the fundamental patterns of behavioral and social functioning relevant to the clinical presentation of ASD. Guided by our previous research, we applied Natural Language Processing based methods to transcripts of natural language samples in order to quantify features of atypical language use in females with ASD.


I teach the following courses in OHSU’s Computer Science and Electrical Engineering (CSEE) graduate education program:


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