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I am a passionate Machine Learning Engineer applying research to products. I am most effective conducting pragmatic research and building prototypes of future thinking technologies. I enjoy reasoning about systems, thinking through problems and applying technology with intent to create tooling where none exists. I hold multiple engineering degrees with experience in diverse fields including Bio-medical Research, Sensor Design and Manufacture, Robotics, Automation, Cloud Software and Document Processing.

At Work

I have served as a visionary IC, research engineer and developer of first party software, ML and AI solutions at early and growth stage companies, spearheading many efforts related to ML including R&D, datascience and engineering.

Day to day, I foster a friendly work atmosphere that promotes passionate, curious engagement around challenging problems. I champion the pragmatic use of agile process, the appropriate introduction of automation, and the application of a product mindset.

With a focus on Deep Learning, I have identified and defined problems fit for ML, translated state-of-the-art research to production systems, and deployed scalable closed loop ML solutions to solve complex real-world challenges.

I bring a wealth of hands-on experience applying deep learning to robotics, computer vision, image processing, NLP and document understanding. I have also presented on vision, R&D, technology and roadmaps to diverse audiences.

For comprehensive work experience, checkout my Resume

For insight into my engineering process, checkout my ML Practitioner's Guide

At Play

My passion projects combine data driven design, art and engineering.

I love generative AI, interactive 3D graphics and rapid physical prototyping.

You can usually find me playing music, mountain biking or adventuring outdoors.

You can checkout side projects on my tech blog: dcyoung.github.io

Get in touch

I'd love to connect. Please feel free to reach out on LinkedIn or via email.

David Young's Projects

battle-tank icon battle-tank

An open-world head-to-head tank fighting game with simple AI, terrain and control systems in UE4.

circuitsolver icon circuitsolver

Creates and solve digital logic circuits. Uses a digraph to represent circuits composed of a finite set of primitive elements. Elements currently include: -Logic Gates (AND, OR, NAND) -Sources Solves the circuit using topological sort.

coffee-table icon coffee-table

Tools, visuals and CAD related to the design of a custom coffee table derived from bathymetry data.

data-vis-art icon data-vis-art

A collection of artistic data visualization experiments.

flowpath icon flowpath

Visualizing runtime flowpath in the context of interactive circuits formed of finite primitive elements. Creating an interactive VR sandbox for the creation of digital logic circuits and graphical scripting.

fps-highlights-cnn icon fps-highlights-cnn

A CNN (deep learning) based approach to detecting highlights in FPS game footage.

gpu-fluid-experiments icon gpu-fluid-experiments

Experimenting coupling a CPU-based rigid body simulation with a GPU-based fluid simulation.

imagealign icon imagealign

Aligns two images that share a camera center. Estimates homography using RANSAC

ml-triangulation icon ml-triangulation

Experiments using ML to triangulate targets based on observations from nodes in a network.

multishaderprogramenvmapping icon multishaderprogramenvmapping

A raw webgl program that loads obj models, generates terrain from heightmaps using texture mapping, and reflects environment using a cubemap.

numpy-char-rnn icon numpy-char-rnn

Character-level language model using a simple RNN built with Python + numpy

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