July 6, 2017

2017 Summer Intern Profile: Nathaniel Yee

Name: Nathaniel Yee

Project/Mentor: Automated detection and classification of deep-sea imagery with Danelle Cline and Duane Edgington

School: Franklin W. Olin College of Engineering

Hometown: Alameda, California

Tell us about your project: My project is centered around automated detection and classification of deep-sea imagery. Put simply, if you give a computer an image, we want it to be able to locate where and what the animals are. This type of technology is valuable as it would allow MBARI to automate oceanographic surveying given enough cameras in the water. To accomplish this task, we are using a machine learning technique known as deep learning. This technique is a data-driven approach that is highly effective at solving computer vision tasks. Throughout my project, I am both curating a set of nicely annotated images and using them to teach computers how to solve the particular problem of detecting and classifying animals.

Why did you want to intern for MBARI: When I was in middle school, I learned to love and appreciate the ocean through the Monterey Bay Aquarium’s Student Oceanography Club. When I learned that MBARI was applying machine learning to solve various problems, I saw it as an opportunity to learn more about real-world data science and to contribute to exploration in oceanographic research.

What’s been your favorite part of MBARI so far: Some of the highlights include: seeing mini beta versions of my project actually work, meeting a bunch of interesting individuals, listening to people present super interesting work, and making friends with my fellow interns. I’ve also had the opportunity and time to revise how I work with and manipulate data, as well as had access to more GPU computing than I’ve ever had before.

And, if you had a boat, what would you name it? “This yacht, my bigger yacht, or my submarine”

As in, “Hey guys, do you want to go out on This yacht, my bigger yacht, or my submarine?”

Meet the rest of MBARI’s 2017 Summer Interns


Data repository
Data policy
Deep-Sea Guide
What is happening in Monterey Bay today?
Central and Northern California Ocean Observing System
Chemical data
Ocean float data
Slough data
Mooring ISUS measurements
Southern Ocean Data
Mooring data
M1 Mooring Summary Data
M1 Asimet
M1 download Info
M1 EMeter
Molecular and genomics data
ESP Web Portal
Seafloor mapping
Soundscape Listening Room
Upper ocean data
Spatial Temporal Oceanographic Query System (STOQS) Data
Image gallery
Video library
Creature feature
Deep-sea wallpapers
Previous seminars
David Packard Distinguished Lecturers
Research software
Video Annotation and Reference System
System overview
Data Use Policy
Video Tape User Guide
Video File User Guide
Annotation Glossary
Query Interface
Basic User Guide
Advanced User Guide
Query Glossary
VARS publications
VARS datasets used in publications
Oceanographic Decision Support System
MB-System seafloor mapping software
How to download and install MB-System
MB-System Documentation
MB-System Announcements
MB-System Announcements (Archive)
MB-System FAQ
MB-System Discussion Lists
MB-System YouTube Tutorials
Matlab scripts: Linear regressions
Introduction to Model I and Model II linear regressions
A brief history of Model II regression analysis
Index of downloadable files
Summary of modifications
Regression rules of thumb
Results for Model I and Model II regressions
Graphs of the Model I and Model II regressions
Which regression: Model I or Model II?
Matlab scripts: Oceanographic calculations
Matlab scripts: Sound velocity
Visual Basic for Excel: Oceanographic calculations
Educational resources
Navigating STEM careers
MBARI Summer Internship Program
2017 Summer Interns Blog
Education and Research: Testing Hypotheses (EARTH)
EARTH workshops
2016—New Brunswick, NJ
2015—Newport, Oregon
2016 Satellite workshop—Pensacola, FL
2016 Satellite workshop—Beaufort, NC
EARTH resources
EARTH lesson plans
Lesson plans—published
Lesson plans—development
Lesson drafts—2015
Lesson drafts—2016 Pensacola
Adopt-A-Float Program
Center for Microbial Oceanography: Research and Education (C-MORE) Science Kits
Science at home: Curriculum and resources
Sample archive
SciComm Resources