Thomas M. Marchitto

University of Colorado Boulder

Papers

1

Total Citations

96

H-Index

1

About

Thomas M. Marchitto is a leading paleoceanographer whose research reconstructs past ocean circulation, climate dynamics, and biogeochemical cycles using geochemical proxies preserved in marine sediments. His work has been instrumental in understanding how deep ocean currents and surface water properties have evolved over glacial-interglacial timescales, particularly in the North Atlantic and Pacific. Marchitto’s most-cited study, “Automated species-level identification of planktic foraminifera using convolutional neural networks, with comparison to human performance” (2019, 96 citations), represents a pioneering application of machine learning to micropaleontology, dramatically accelerating the identification of these key climate indicators while matching human accuracy. This work bridges traditional paleoceanographic methods with cutting-edge computational tools, enabling high-throughput analysis of foraminiferal assemblages. Beyond this, his research has been widely cited for quantifying the role of deep water formation in past carbon storage and abrupt climate shifts. Marchitto’s contributions have shaped our understanding of ocean-atmosphere coupling, earning him recognition as a leader in proxy development and paleoclimate reconstruction. His interdisciplinary approach continues to inspire new generations of climate scientists.

Research Focus

Key Achievements

1
H-Index
1
Papers
96
Total Citations
96
Avg Citations/Paper
🏆 Most Cited Paper
Automated species-level identification of planktic foraminifera using convolutional neural networks, with comparison to human performance
96 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: University of Colorado Boulder

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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