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Jacob Alford is a mathematics major, full-stack developer, machine learning enthusiast, successful cryptocurrency investor, and professional photographer.  He graduated with an Associates of Science degree at New Mexico State University - Grants in 2016, and will graduate with a Bachelor's degree in Mathematics in Spring, 2020.  Most recently, he's devoted his time to Matrix_js, an all inclusive matrix library for Javascript emulating the ease of Tensorflow.js. 


JavaScript (ECMAScript2017)

Experience coding front-end websites, node.js applications, and p5.js.


Experience coding back-end server applications like user management and profile storage; with cryptographically secure hashing such as Argon2i.

Machine Learning and TensorFlow.js

Designed an assortment of multilayer perceptrons and studied long short-term-memory units (LSTM).

Information Technology

Designed Network Servers using Microsoft Group Policy, Remote Surveillance Servers, Apache Web Servers with PHP, VPN Tunneling Servers


Designed a craps simulator for Intel International Science and Engineering Fair (Intel ISEF).  Recently re -familiarized with the underlying syntax structure.


SEBAL is an algorithm that calculates the relative soil saturation from a series of images; I use tensorflow for superior memory management and processing aptitude.  RPN stands for reverse polish notation - it's a really efficient calculator! My implementation can be found on my website.  Matrix_js is a javascript matrix library which emulates Tensorflow.js - namely its tidy method call stacking.

Work experience


Information Technician Intern

New Mexico State University



Social Media Administrator

Ice Cave and Bandera Volcano

Mathematics Tutor

New Mexico State University


2014 2016

Associate of Science

New Mexico State University