Song Sangmin

Oceanographic Researcher • University of Washington • Seattle, WA

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PhD Candidate in Oceanography
MSc in Oceanography (2023)

Research Interests

My dissertation explores new ways of modeling carbon exchange between the ocean and atmosphere by leveraging observations from a growing, global fleet of drifting oceanic robots called Argo floats. Our regression model, CRUSOE, is a novel machine learning approach to reconstructing the variability of carbon uptake in the dynamic Southern Ocean (i.e. the region around Antarctica) each year. Incredibly, this region is thought to make up around 40% of global oceanic uptake but remains difficult to observe and understand due to its remote location and harsh conditions. The novel surface ocean carbon product generated by CRUSOE will provide a key missing piece for improving the quantification of the Southern Ocean carbon sink, which will ultimately be essential for reducing uncertainties in the Global Carbon Budget.

Highlighted Projects

Publications

Conferences and Presentations

2026-04
Technologies for Innovation, Design, & Environmental Stewardship (Seattle, WA)
2026-02
Ocean Sciences Meeting* (Glasgow, Scotland, UK)
2025-06
Southern Ocean Carbon and Climate Observations and Modeling (San Diego, CA)
2024-02
Ocean Sciences Meeting (New Orleans, LA)
2024-04
UW Foundation Board Meeting, research showcase (Seattle, WA)
2023-08
UW Data Science in Oceanography Summer Program* (Seattle, WA)

*oral presentation

Additional Experience

Teaching and Service
  • Foundations of Ocean Sensors (UW), Python Assistant Instructor (2023)
    Dean A. McManus Excellence in Teaching Award, Runner-up (2023 Oct)
  • UW Program on Climate Change, Graduate Steering Committee Member (2022–2024)
  • UW Graduate Application Mentorship Program, lead (2021–2023)
Fieldwork
  • UNOLS R/V Endeavor, EN-681 (Gulf Stream, 7 days at sea, 2022 May)
  • CCGS Amundsen, ArcticNet (Baffin Bay/Greenland, 20 d.a.s., 2019 Jul–Aug)