About

I studied the brain through big data and high dimensional mathematics. I improved my data practices from Brainhack events and the ReproNim/INCF fellowship, now I hope to make some contributions outside of academia.

This website is built from the personal jekyll theme. You can click on the following links to star and fork the original repo to replicate the website for your own.

Latest Blog Post

28 Jul 2022 . thoughts . TensorFlow & probabilistic ML - Regression Comments

The examples displayed here are taken from Kevin Murphy’s probabilistic machine learning Colab notebook. I found the code to be very instructive when paired with the math formulations, and thought I’d expand the logic here for people hoping to explore probabilistic modeling with tensorflow-probability.

Linear regression is a basic curve fitting technique using a straight line model to approximate the data trend. However, when the data is noisy, scientists need to understand the assumptions and quantify the reliability of their curve fitting methods. A probabilistic approach to modeling enables the quantification of uncertainty, but implementing this...

Archive

Timeline

  • October 2022

    Became a data scientist!

  • December 2021

    Finished the Ph.D!

  • August 2021

    Attended Neuromatch Deep Learning!

  • June 2020

    Organized Brainhack NY!

  • February 2021

    Settled back home in NYC!

  • March 2020

    Became a ReproNim/INCF Fellow!

  • August 2018

    Attended Neurohackademy in Seattle!

  • April 2018

    Moved to San Francisco!

Contact

Drop me an email about cool data projects or questions about my work!