My name is Daniel, and I am a Bioinformatics Software Engineer living in SoCal.
I am a Computer Science(B.S.) and Political Science(B.A.) graduate from the University of California, Irvine.
I love to code - I specialize in Genomics, Python applications, and Cloud Infrastructure.
I am currently expanding my skill set in Bioinformatics with my new role in Product Development as a Sr. Bioinformatics Software Engineer.
When I am not coding you might find me sailing, traveling, cycling, or volunteering with a Diabetes non-profit.
BS in Computer Science, 2015
University of California, Irvine
BA in Political Science, 2014
University of California, Irvine
Machine Learning Methods Certificate, 2020
University of California, San Diego Extension
Predicting with 79% accuracy which days I exercised based on Blood Glucose Data with Neural Networks
Personal Website and Blog.
Using Python to create Armenian words flashcards with a custom pronunciation guide
Using ML to predict if I exercised a certain day based on Blood Glucose Readings
Creating Sound From My Glucose Numbers
Programmatic acces to super critical information like if it is my birthday.
Jupyter notebook inspecting the coronavirus genome.
Display Blood Glucose in iTerm2
A serverless function to scrape glucose data from dexcom servers and upload it to a DynamoDB table.
I hosted a Python Lunch and Learn for associates at Capital Group. This is the repo I created for that session.
A person without Type 1 Diabetes has an average blood glucose reading of 120. The graphic shows whether I am above, below, or at average. Leveraging an open source project called Nightscout I am able to scrape the data from the continous glucose monitor that I wear on my body. I hope to develop analytics and insights into glucose readings to help Type I Diabetics better manage their Diabetes.