Analytics and Machine Learning:
I’ve spent a few years working with analytics, handling data for companies like Olipop, Dr. Bronners, Clif Bar, True Classic Tees, and more. I studied Machine Learning at Flatiron in 2022 specializing in text and language analysis. I’ve also done a number of projects applying LLMs to do things like organize internet browsing history, study the virality of information, interpret research paper abstracts, and analyze market conditions to generate business or product concepts.
If you have software, data, or machine learning needs, let me know and I may be able to help!
Click these to read about some of my projects:
Analyzing machine learning communities on Twitter with three different natural-language processing strategies, and then using six different machine learning algorithms to see how much you can predict which tweets and topics are most likely to go viral
Building a machine vision system using deep learning techniques to detect pneumonia in children’s x-rays
Looking at large amounts of real-estate data in Seattle to identify key predictors of home value, and then use a linear-regression algorithm to identify homes that may be undervalued in the market & plot them on a map
Experiments in making AI tools that friends and family actually use
Visualize your web-browsing history as a network of connected topics and websites. An AI pipeline interprets internet browsing sessions and feeds these descriptions into a graph-based notetaking software called Obsidian to map out your habits and interests.
An experiment using an ensemble AI to analyze changing market conditions, come up with product definitions, and generate product or business plans
An experiment in extracting features from whitepaper abstracts to see how much explanatory power they have to predict research impact
Using machine learning systems to interpret data from the Taiwan stock exchange to identify or predict companies which are at risk of bankruptcy.
Programming for Embedded Systems
I’ve also developed systems using Arduino, ESP32, & Raspberry Pi for sensors and motion control. A good project illustrating this is the scanning hyperspectral microscope I developed, which can be read about here.
A pipeline for identifying and visualizing the important semantic dimensions of text, like seeing how themes in books evolve, or seeing how your tweets and writing change over time