I am a software development instructor at a back-end development bootcamp, where I teach Python, Postgres, and DevOps. My background is in data analytics, neuroimaging, and digital demography.
My career began in a neuoimaging lab at the University of Washington, where I used bash scripts to analyze neuroimaging data and earned a $5,000 scholarship to analyze functional MRI data and better understand social anxiety in Autism Spectrum Disorder. Following my experience working in medical imaging research, I began working in digital demography, where I published a paper with researchers from the Max Planck Institute, MIT, and the University of Washington. Now, I work as a tutor and trainer for undergraduate students, graduate students, and working professions in personal programming projects. I have created over 4,000 hours of personalized, private tutoring and/or consulting gigs in programming for students from University of California--Santa Cruz, Syracuse, Stony Brook, University of Chicago, University of Illinois--Urbana Champaign, Penn State, Vanderbilt and many others. My software training consisted of clear and engaging lessons on using various programming languages and tools: Java, Python, Bash Scripting, SQL, R, Android Studio, and other tools as needed. When I am not tutoring, I am consulting litigation lawyers, accountants and programmers from companies such as Cisco, McDonald's Corporate, and many others in their day-to-day processes. I also teach at a coding bootcamp: teaching back-end development with Python, Postgres and DevOps.
I am searching for students and individuals with exciting projects that I can contribute to.
University of Washington, United States 2014 - 2018
Mary Gates Research Scholarship
Mary Gates Research Endowment
Investigated the functional processes underlying social anxiety in adults diagnosed with Autism Spectrum Disorder.
Analyzing the Effect of Time in Migration Measurement Using Georeferenced Digital Trace Data
Georeferenced digital trace data offer unprecedented flexibility in migration estimation. Our results demonstrate the need for evaluating the internal consistency of migration estimates derived from digital trace data before using them in substantive research.