Principal AI Engineer | Computer Vision | Experienced Machine Learning Professional | Patent Agent
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Data Scientist, Inventor, AI Engineer, Marathoner, and Millennial Technologist with 10 years professional experience. #PatentPractitioner #iBuildBots & #AutonomousVehicles for #Society. #GeorgiaTech
Georgia Institute of Technology
B.S., Electrical Engineering
January 1, 2008 – January 1, 2012
LiveReach AI
Senior Data Scientist
April 1, 2022 – February 1, 2023
LiveReach AI
Principal AI Engineer
April 1, 2022 – Present
McDermott Will & Emery
Patent Agent
February 1, 2022 – February 1, 2022
San Francisco, California, United States
USPTO
Patent Examiner
September 1, 2020 – June 1, 2021
San Jose, California, United States
Stealth-mode Startup
Software Lead
August 1, 2020 – August 1, 2021
San Francisco Bay Area
Pronto.ai
Senior Software Engineer
August 1, 2018 – November 1, 2019
San Francisco, California
Udacity
Mentor/Code Reviewer - The School of Artificial Intelligence
January 1, 2017 – November 1, 2018
Udacity
Student Mentor Services - Artificial Intelligence/Self-Driving Car
October 1, 2016 – November 1, 2018
Alston & Bird LLP
Patent Agent
November 1, 2015 – October 1, 2016
Atlanta Metropolitan Area
Clockwise.MD by Lightshed Healthcare
Senior Software Engineer
January 1, 2015 – November 1, 2015
Atlanta, GA
CareerBuilder.com
Software Engineer II
September 1, 2012 – January 1, 2015
Norcross, GA
UPS
Plant Engineering PT Supervisor - Inventory Control Engineer
February 1, 2007 – September 1, 2012
Sugarloaf Country Club
Waiter
July 1, 2005 – April 1, 2006
Kentucky Fried Chicken
Team Member/Leader
June 1, 2004 – July 1, 2005
Dockerized Installation of TensorFlow 1.0 (From Source with GPU Support)
February 1, 2017 – Present
I used Docker-Machine to build Tensorflow 1.0 from source for Ubuntu 14.04. In addition, this container provides many of the common Data Science libraries and integrates with Jupyter remotely. My blog post describing my technique is: https://medium.com/@deanofthewebb/dockerized-installation-of-tensorflow-1-0-from-source-with-gpu-support-77646cd25f92#.wh74ae5a1
Vehicle Detection and Tracking
February 1, 2017 – March 1, 2017
● Developed an automated vehicle detection and tracking pipeline for autonomous vehicles using machine learning techniques to (a) process video camera input, and (b) detect and tract other vehicles. ● Performed a Histogram of Oriented Gradients (HOG) feature extraction on a labeled dataset and trained a Linear SVM classifier based on a real feed from an autonomous vehicle camera system.
European Road Signs Classifier (Python)
December 1, 2016 – Present
- Designed a custom Convolutional Neural Network using TensorFlow to classify European road signs to 92% test-accuracy (99% validation accuracy). - Developed a generic Preprocessing Engine that automates the downloading, extracting, preprocessing, and caching of image datasets for neural network training with Tensorflow. - Developed a Tensorflow api wrapper similar to mini-Keras framework.
Automated Lane Lines Annotation over Video Feed (Python)
November 1, 2016 – Present
- Developed an automated lane-tracking pipeline using Computer Vision concepts. - Implemented Canny Edge Detection and Hough Transforms to detect, analyze, and filter for lane lines.
Spotify Streamer (Android App)
August 1, 2016 – Present
- Developed a Spotify inspired Media Player application and utilized key Android components, such as Content Providers, Loaders, and Services. - Designed User Interface, optimized performance to production-ready state by (a) caching user preferences, and (b) implementing a ViewHolder design pattern.
aiVision (Android App)
November 1, 2015 – Present
- Developed an environmental recognition and navigation application for the visually impaired - The app was awarded “Best Technical App” title at Google’s Android Developer Career Summit Conference (November 2015).
Cultural Fit Analysis
The candidate has a diverse career path, including significant time in patent law, which is unusual for an ML Engineer. While their personal projects and earlier roles align well with an ML Engineer profile, the recent career trajectory shows some shifts. The breadth of experience, from software engineering to patent examination and then back to AI engineering, suggests adaptability. However, the lack of detailed descriptions for recent AI roles makes it challenging to fully assess their current cultural fit and alignment with a fast-paced, dedicated ML engineering environment. The project diversity is strong, but the professional role alignment has some gaps.
Soft Skills & Operational Fit
The candidate's experience as a mentor and code reviewer at Udacity suggests strong communication and teaching abilities, which are valuable for team collaboration and knowledge sharing. Their past roles as a Software Lead and Senior Software Engineer indicate leadership potential and experience in managing technical aspects of projects. However, the descriptions for recent roles at LiveReach AI are very brief ("I write code"), which limits the ability to assess current operational fit and specific soft skills in those contexts.