I am a Computer Science & Engineering PhD candidate at Oregon Health & Science University (OHSU) in Portland, Oregon, USA. My advisor is Steven Bedrick . My PhD research involves developing computational and statistical methods to detect and quantify different aspects of the language of children with Autism Spectrum Disorder (ASD).
I am also a Data Science Mentor at Posit (previously known as RStudio) for Posit Academy . I mentor small groups of working professionals as they develop and hone their data science skills in R or Python.
I recently presented two papers at the SIGDIAL 2023 conference in September: “A Statistical Approach for Quantifying Group Difference in Topic Distributions Using Clinical Discourse Samples” and “Computational Analysis of Backchannel Usage and Overlap Length in Autistic Children” .
**I am expecting to graduate in December 2023 and am currently on the job market!**
PhD in Computer Science & Engineering, Expected Dec 2023
Oregon Health & Science University
BA in Mathematics, 2017
Lewis & Clark College
What is Multidimensional Scaling? Multidimensional Scaling (MDS) is a dimensionality reduction technique that is useful for exploratory data visualization. Some other popular dimensionality reduction techniques include Principle Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE). Given a similarity matrix (e.g. a distance matrix), MDS projects the data points into an N-dimensional space while minimizing the amount of similarity information lost. In the ideal case, the closer the projected points are to one another, the more similar the are while the farther apart they are, the less similar they are.
A continuation of a sentiment analysis of child language acquisition data using the Kuczaj Corpus from the CHILDES database.
A sentiment analysis of child language acquisition data using the Kuczaj Corpus from the CHILDES database that I did for my final visualization project for CS 632.