Summary:-Optimist, Software Engineer, Marine Scientist
-PhD Student in Marine Science and Conservation with Dave Johnston in the Marine Robotics and Remote Sensing Center at Duke University
- machine learning approaches to remote sensing analysis
- the intersection of ocean and space exploration
- drones and autonomous systems for marine science and exploration
- machine learning for large-scale environmental monitoring
- adventure sports (paddle boarding, climbing, sailing, surfing)
Work and Focus
I'm currently a PhD student with Dave Johnston
in the Marine Robotics and Remote Sensing Lab at the Duke University Marine Laboratory.
My doctoral research focuses on machine learning approaches to remote sensing analysis, coordinating satellite, drone, and in-situ
environmental monitoring, and understanding how autonomous systems will benefit field scientists - with an emphasis on coastal
and oceanographic environments. I'm particularly interested in systems that will be relevant for marine science as well as for exploring
and understanding other bodies within our solar system.
Before joining the Duke Marine Lab, I worked at Harvard University as a research technician in the Girguis Lab, spent time at Moon Express as a Software Engineer developing their ground data systems and engineering team tools, and served a year and a half as Chief Technology Officer at WayPaver Foundation. I graduated from the University of North Carolina as a Morehead-Cain Scholar with a degree in Computer Science where I started UNC Students for the Exploration and Development of Space, helped start the Sigma Phi Society, and researched computer vision in the Alterovitz Lab.
Open Source Coding Projects
Quick overview of open-source projects.
A curated list of deep learning papers in ecology.
Educational Resources on Neural Networks for Ecology and Remote Sensing.
Tutorial of remote sensing and GIS methodologies using open source software in python.
Open source code and data for the manuscript "Drones and Convolutional Neural Networks Facilitate Automated and Accurate Cetacean Species Identification and Photogrammetry."
Summary of recent journal and conference publications.
Integrating Drone Imagery into High Resolution Satellite Remote Sensing Assessments of Estuarine Environments
Patrick C. Gray, Justin T. Ridge, Sarah K. Poulin, Alexander C. Seymour, Amanda M. Schwantes, Jennifer J. Swenson, and David W. Johnston
Published in Remote Sensing - 2018
A Convolutional Neural Network for Detecting Sea Turtles in Drone Imagery
Patrick C Gray, Abram B Fleishman, David J Klein, Matthew W McKown, Vanessa S Bézy, Kenneth J Lohmann, David W Johnston
Published in Methods in Ecology and Evolution - 2018
Drones and Convolutional Neural Networks Facilitate Automated and Accurate Cetacean Species Identification and Photogrammetry
Patrick C Gray, KC Bierlich, Sydney A Mantell, Ari S Friedlaender, Jeremy A Goldbogen, and David W Johnston
Published in Methods in Ecology and Evolution - 2019
Toward Generalized Change Detection on Planetary Surfaces with Convolutional Autoencoders and Transfer Learning
Kerner, H. R., Wagstaff, K. L., Bue, B., Gray, P. C., Bell III, J. F., Ben Amor, H.
Published in Journal of Selected Topics in Applied Earth Observations and Remote Sensing - 2019
Writings and Readings and Talks
My reading history.
In addition to my reading history I've included link to various writings of mine and presentations that may be of interest.
Writings and Docs:
- SEDS SpaceVision - November 2014
- NC Governor's School - July 2015
- New Worlds - October 2015
- USC, Space Studies - December 2015
- TTU SEDS March - 2016
- NewSpace WayPaver Foundation Presentation - June 2016
- NC Governor's School Campus Wide Presentation - Becoming a Spacefaring Species - June 2016
- NC Governor's School Seminar - Lunar Settlement - June 2016
- NC Governor's School Main Presentation - Searching for Life and Spreading our Own - June 2017
- NC Governor's School Seminar/Elective - Exploration as a Mechanism for Survival - June 2017
- UNC SEDS - Vision for Space and Careers within the Industry - November 2017