Alexander Reynolds

Data scientist in home automation @Beaconhome. Research in signals & computer vision @USAF Research Lab, @Wright State, and @ASU. Honors BS Math @ASU '16. (650) 665-9566
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Data Scientist


January 2018–Current San Mateo, CA

Algorithm R&D, model training, and real-time prediction and decision systems for a hardware-focused startup in the home automation space. Cloud and edge computing with data from a variety of hardware sensors.

Research Associate II, Sensors Directorate

US Air Force Research Laboratory

September 2016–January 2017 Dayton, OH

Research position in computer vision at the premier US Air Force research facility. Investigated the propagation of uncertainty in image registration algorithms. Collected and analyzed registration data for evaluation of computer vision algorithms. Developed video stabilization scripts for truthing in machine learning research software. Support from USAF.

Research Intern, Automatic Target Recognition Center

Wright State University

May 2016–August 2016 Dayton, OH

Summer research position in computer vision. Developed fully Bayesian techniques to obtain consistent uncertainty estimates in georegistration algorithms for UAV video feed. Participated in weekly seminars on computer vision and image processing. Support from DoD and USAF.

Research Assistant, Mathematics

Arizona State University

May 2015–April 2016 Tempe, AZ

Research in applied Fourier analysis; focus in analysis of edge detection methods with spectral data in synthetic aperture radar signals. Participated in weekly group meetings with professors, post-docs, and doctoral candidates from multiple disciplines and attended seminars on applied and computational mathematics. Support from DoD and NSF.

Educator, Designer, Room Acoustics

GIK Acoustics

August 2012–April 2016 Atlanta, GA (Remote)

Developed acoustic absorbers and diffusors tested at Riverbank (US) and University of Salford (UK), conducted in-situ acoustic measurements using free-field test microphones, designed neutral acoustic spaces for clients, authored articles to disseminate knowledge of room acoustics, and modeled acoustic elements and spaces.



Honors Bachelor of Science, Mathematics

Barrett, the Honors College, Arizona State University

August 2013–May 2016 Tempe, AZ

Focus in scientific computing, signal processing, and abstract algebra. Graduate-level courses in algebra, graph theory, and philosophy. Awarded the Bidstrup Foundation Research Fellowship. Graduated magna cum laude.

Thesis, Edge Detection from Spectral Phase Data

Barrett, the Honors College, Arizona State University

April 2016 Tempe, AZ

Analysis of methods to create edge maps constructed from noisy and intermittent spectral phase data with post-processing techniques. Supervised by Dr. Anne Gelb and Dr. Douglas Cochran, in partial fulfillment for the requirements of a Barrett Honors degree.

Nanodegree, Self-Driving Car


May 2017–Current Online (Remote)

Nine month program spanning machine learning, computer vision, robotic controls, localization, and path planning.

Open-Source Contributions

Firefly Automation

Backend; Python, Google Firebase

August 2017–Current GitHub

Firefly is an open-source home automation system. It is lightweight and can run on a Raspberry Pi. The Python based framework allows for easy development of apps and new components, and currently supports Google Home, Amazon Echo, Philips Hue, ZWave, and many other popular home automation devices. I work on the Python core with the head developer, friend and Security Engineer Zachary Priddy.


Template Matching Module; C++

September 2017–Current GitHub

OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library. I am working on building out support for masks on the matchTemplate() function. The implementation supports masks only for two of the six possible template matching methods currently, and I will be opening up mask support for all six methods. Masks will allow both boolean and float masks to either allow pixel selection or pixel weighting respectively.


Magic Wand Selector

Python, OpenCV

August 2017 GitHub

I originally developed this project to test an object oriented approach for image display windows in OpenCV. I wanted to implement an OpenCV copycat of Adobe Photoshop's Magic Wand tool, which allows a user to select a region of similar colored pixels, but also outputs a selection mask and some statistics of the colors in the selected region.

Colorspace Filtering

Python, OpenCV, JS, Node, Docker

June 2017 GitHub (Native/OpenCV UI), Web App (in development), GitHub (Web UI)

This project was brought on by the dozens of users on Stack Overflow asking for robust methods for color selection in OpenCV when simple colorspace thresholding would suffice. Provides an easy interface for trying out threshold ranges in different colorspaces to produce binary images which identify colors. Includes a native OpenCV interface on Python and currently building out a web interface for a more robust UI, co-developed with a friend, UI/UX Designer and Front-end Developer Shaun Sweet.

Padded Transformations

Python, OpenCV

July 2017 GitHub

Homographies can be a tricky subject for beginners in computer vision, especially for those without a background in mathematics. A few Stack Overflow questions have been popping up recently with people unsure of how to transform images without cropping them. The method to remove cropping from OpenCV's warpAffine and warpPerspective functions can be easily automated without user input, so I created a Python module with padded versions of the OpenCV functions.

Label Finder

Python, OpenCV

July 2017 GitHub

This project was an open challenge for a position at Intelligent Flying Machines. IFM makes drones which buzz around warehouses primarily for inventory management. The goal of the challenge was to produce annotated images showing the location of labels attached to boxes, both on high-res still images and low-quality motion-blurred video frames. All parameters were to be configurable via an interface, which I provided natively in OpenCV with trackbars. My program found the labels in the provided images, as well as in some synthetic images I created for testing purposes.

Lane Lines

Python, OpenCV

May 2017 GitHub, YouTube

Detected highway lane lines from a video stream. Used Canny edge detectors and Hough transforms, along with other image processing techniques to separate out and average lines. Completed by using the algorithm on my own video stream from a GoPro mounted to my windshield.

Template Tracking Mario

Python, OpenCV, Matlab

May 2017 GitHub, YouTube

What's an easy way to track Mario in Super Mario Bros game-play? Uses frame-by-frame template matching via summed square differences to track a template through a video, and includes optimizations to dynamically reduce the search area as needed to find the template.

Spectral PDE Solver

Matlab, paper

May 2017 Read paper

Honors project for a course in Numerical Analysis to explore a topic outside the curriculum. Program to solve second order linear PDEs via spectral methods. Outputs a sequence of solutions at varying time steps and computes error between the numerical solutions and exact solutions.

Semidirect Products


May 2017 Read paper

Honors project for a course in Abstract Algebra to explore a topic outside the curriculum. Paper on semidirect products, complete with motivation, recognition theorems, proofs of various properties of semidirect products, and classifications of groups arising from semidirect products.

Honors Thesis Work

Presentations, posters

Arizona State University 2015–2016

Acoustical Articles

Web publications

GIK Acoustics 2012–2014
References available upon request.
Updated June 22, 2017.