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Deep Learning · Computer Vision · 3D Geometry
Check out my homepage here for detailed info about me: danieldetone.com My interests are in: • Computer Vision • 3D Geometry • Deep Learning I have recent project experience in: • Convolutional Neural Networks • Graph Neural Networks • Recurrent Neural Networks and LSTMs • Deep Learning for Geometric Tasks • IMUs and Sensor Fusion • Deep Learning in RGBD and 3D domains • Real-time Text Detection and Recognition • Markerless Augmented Reality • Human Tracking • Structure from Motion (SfM) / SLAM • Autonomous Robotics
University of Michigan
Master of Engineering (M.Eng.), Computer Engineering
January 1, 2013 – January 1, 2015
University of Michigan
Bachelor of Engineering (BEng), Computer Engineering
January 1, 2009 – January 1, 2013
Los Angeles Astra
Minority Investor / Owner
November 1, 2024 – Present
Research Scientist
August 1, 2020 – Present
Magic Leap
Lead Software Engineer
March 1, 2019 – July 1, 2020
San Francisco Bay Area
Magic Leap
Senior Software Engineer
March 1, 2017 – March 1, 2019
San Francisco Bay Area
Magic Leap
Software Engineer
August 1, 2015 – March 1, 2017
San Francisco Bay Area
University of Michigan
Graduate Student Instructor
September 1, 2014 – January 1, 2015
Ann Arbor, MI
Occipital
Computer Vision Intern
May 1, 2014 – August 1, 2014
San Francisco, CA
Michigan Student Artificial Intelligence Lab
Vice President
September 1, 2013 – May 1, 2014
Ann Arbor, MI
University of Michigan - Collaboratory Project
Graduate Researcher
May 1, 2013 – August 1, 2013
Ann Arbor, MI
University of Michigan - Collaboratory Project
Lead Computer Vision Researcher
September 1, 2012 – May 1, 2014
Ann Arbor, MI
GE Aviation Systems
Software Engineering Intern
June 1, 2012 – August 1, 2012
Grand Rapids, MI
US Army - TACOM
Engineering Intern
June 1, 2009 – September 1, 2009
Warren, MI
Projectile Prediction and Retrieval using Kinect
April 1, 2013 – Present
We developed a fully automated projectile-catching robot by affixing a small basket to a mobile robot and predicting the projectile's landing position. We implemented a detection algorithm using RGBD data from a Kinect and a estimation algorithm using linear regression. Once the landing position was calculated, we used dead-reckoning and PID control to navigate the mobile robot to the landing zone and return the fetched ball to the return zone.
Simultaneous Localization and Mapping (SLAM)
March 1, 2013 – Present
Our team was awarded 2nd place out of 8 total teams. We entered our mobile robot (equipped with a fisheye camera and laser pointer) in a robotics competition. Points for the competition were awarded for (a) mapping a small area (20'x20') marked with blue tape along the area walls (b) detecting green triangles in the map and firing a laser pointer at them and (c) returning to the original starting position. Highlights: -Implemented graph-based Simultaneous Localization and Mapping (SLAM) for mapping -Devised and implemented fast agglomerative line fitting algorithm to the HSV filtered image to robustly detect blue lines -Utilized a memory efficient quad-tree for map storage
Automatic Cruise Control System
April 1, 2012 – Present
Implemented an Automatic Cruise Control System for a car on a MPC5553 embedded processor and and simulated it using Matlab, Simulink and CAN networks
Assistant Power Vinyasa Yoga Instructor
Funky Buddha Yoga Studio
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background is heavily skewed towards Computer Vision, Robotics, and AI/ML engineering, with significant experience in research and development. While these fields involve data, the direct alignment with a 'Data Analyst' role is not strong. The projects demonstrate analytical thinking and data manipulation, but the focus is on engineering and algorithmic implementation rather than business intelligence, reporting, or statistical analysis typical of a Data Analyst. The 'Minority Investor / Owner' role suggests entrepreneurial interest but doesn't directly contribute to cultural fit for a Data Analyst position. The breadth of skills is deep in specific technical areas but lacks explicit mention of common data analyst tools and methodologies (e.g., SQL, advanced Excel, BI tools, A/B testing, specific statistical packages).
Soft Skills & Operational Fit
The candidate's experience as a Lead Software Engineer and Vice President of an AI Lab suggests leadership, project management, and potentially strong collaboration skills. The detailed project descriptions indicate problem-solving abilities and a structured approach to complex technical challenges. However, without specific psychometric test results or interview data, a definitive assessment of soft skills and operational fit is limited.