schlining_brian-180

Brian Schlining

Software Engineer

Monterey Bay Aquarium Research Institute

7700 Sandholdt Road

Moss Landing, CA 95039

Phone: (831) 775-1855

email: brian@mbari.org

Brian is a Software Engineer at MBARI working in the Information Engineering group of the Research and Development division. He has a bachelor’s degree in Biology from the University of Maryland, College Park and a master’s degree in Marine Science/Physical Oceanography from Moss Landing Marine Laboratories.

Brian has developed software systems supporting science at Moss Landing Marine Laboratories, the Naval Post-graduate School and at MBARI. Employed at MBARI since 1998, he has worked on numerous projects involving video and image analysis, video annotation, numerical analysis, user-interface development, and data-management systems.

Bintray | Bitbucket | GitHub | JIRA

2019 Projects

Core CTD Data (200103)

Brian is integrating data from the mini ROV, a shared MBARI asset, into MBARI’s data processing systems.

Video Annotation Data Management (500055)

MBARI has collected over 27,000 hours of underwater video since 1984. Working alongside the research and video staff, Brian develops systems for assisting MBARI staff with managing and analyzing this video data. MBARI’s video management and annotation tools are open-source and freely available to other researchers.

MBARI provides a Deep-Sea Guide for identifying and characterizing deep-sea organisms. As the lead engineer, Brian provides support, development and updates to the Deep-Sea Guide.

Environmental Sample Processor (901205 – 708129)

The MBARI Environmental Sample Processor—the ESP—provides on-site (in situ) collection and analysis of water samples from the subsurface ocean. Brian provides tools for analyzing images collected by the ESP.

Big Ocean Big Data (800136)

As the volume and velocity of ocean data increases, new tools and techniques need to be established to process and integrate this data. This project is investigating new techniques to efficiently process and analyze visual datasets using machine learning. Due to the sparsity of image datasets of deep sea animals, a new platform, FathomNet, is being developed to provide the expertly curated data required to support machine learning.

Biodiversity and Biooptics of Zooplankton (901103)

The Zooplankton Biodiversity Group at MBARI uses a 20+ year time series of data to investigate the diversity and community structure of the ocean’s midwater zone. Brian provides expertise for the development of tools used to extract information from MBARI’s long-term data archives.

Midwater Time Series (901221)

Between the surface of the sea and the ocean floor lies a vast fluid universe, Earth’s least-known environment. MBARI has sophisticated systems that have spent thousands of hours surveying and describing the deep waters of the ocean. In support of MBARI’s Midwater lab, Brian develops tools, technology, and analytical techniques for working with this large collection of data.

Data Technical Advisory Group (901602)

Along with other members of the information engineering group, Brian is involved with work on MBARI’s data management systems. The group’s goals for 2018 include:

  • Develop methods for merging molecular data with other environmental observations.
  • Assimilate data into four-dimensional coupled physical and biological models.
  • Create tools for preserving, exploring and mining multi-disciplinary data sets

Video Technical Advisory Group (901603)

This group researches and evaluates new developments and innovations in deep learning and machine vision as applied to underwater image and video analysis.

Pelagic-Benthic Coupling (901618)

This project studies ecological responses of marine communities in extreme environments to changes in climate and carbon cycling. Brian provides tools for managing and analyzing the large amounts of imaging data collected for this research.

Improving the Impact of MBARI’s Data (901915)