portfolio

I am a Machine Learning Engineer who also delves into the worlds of Data Engineering and Web Development. Currently, I am a Data Engineer at Red Bull, where I focus on creating scalable end-to-end machine learning models for Recommender Systems.

I graduated from the University of California, Los Angeles with a BS in Astrophysics. During that time, I completed four years of research as part of a research fellowship and was also a co author in a paper (details below).

Machine Learning Engineering

Data Engineering

Data Analysis

Web Development

For Machine Learning Engineering, some of my responsibilities have included:

Actively researching and prototyping machine learning models to personalize product recommendations
Deploying machine learning models on cloud services as part of an end-to- end machine learning workflow
Developing & maintaining end-to-end machine learning pipelines that are scalable and cost effective

Technologies:

Tensorflow

Tensorflow Probability

Scikit-Learn

Numpy

Pandas

For Data Engineering, some of my responsibilities have included:

Deploying machine learning models on cloud services as part of an end-to- end machine learning workflow
Collaborating with back-end engineers to integrate APIs and microser- vices with the platforms
Creating efficient and scalable ETL pipelines for machine learning models

Technologies:

SQL

BigQuery

Apache Beam

Python

Pandas

Tensorflow

Tensorflow-Extended

GCP

Docker

For Data Analysis, some of my responsibilities have included:

Creating repeatable exploratory data analysis in Jupyter notebooks, with visualizations to aid the story-telling process of data
Integrating model analysis using rigorous mathematical methods
Analyzing machine learning performance

Technologies:

SQL

BigQuery

Apache Beam

Python

Pandas

Tensorflow

LaTex

For Web Development, some of my responsibilities have included:

Implementing major features that increased scalability while reducing latency
Researching and integrating machine learning models to personalize UI

Technologies:

Javascript

Typescript

HTML/Haml

CSS/SCSS

Vue

Node.js

Study of Filaments Near the Galactic Center

Astrophysics Research: UCLA

(2014-2018)

Conducted image processing and statistical analysis on data take by space telescopes WISE and SPITZER on gas filaments AFGL-5376 and Double Helix Nebula in the Galactic Center.

Radio Transient Classification

Astrophysics Research: UC Berkeley

(Summer 2016)

Used clustering techniques to classify fast radio transients. This work was done under the mentorship of Dr. Casey Law and Dr. Carl Heiles.

Search for Technosignature in TRAPPIST-1

Astrophysics Research: UCLA

2016-2017

Collected over three terabytes of observational data from the 100m Green Bank telescope to identify possible technosignatures near TRAPPIST-1.

Lead Machine Learning Engineer

Logos

(2017-now)

Leading the data science team toward researching, developing & experimenting machine learning models to solve problems in Natural Language Processing, personalized UI/UX, and business-oriented analysis.

Data Engineer

Red Bull

(2019-now)

Research, prototype, and deploy machine learning models on cloud services to personalize product recommendations as part of an end-to-end machine learning workflow.

I'm always open for discussions, so feel free to contact me!

Email Resume