QCR Marine Robotics Seminar | Jordan Pierce | 29th June, 2026
This seminar is part of the Marine Robotics Seminar Series hosted by the QUT Centre for Robotics. You can see the full list of seminar recordings, and a schedule of upcoming talks here: https://scarlettraine.com/marine-robo... Title: From in-situ to in-silico: A Brief History of Computer Vision and Coral Reef Ecology Speaker: Jordan Pierce, UCSD Bio: Jordan Pierce is an interdisciplinary scientist specializing in the development of software and AI-driven tools for marine ecology and ocean mapping. He holds a Bachelor of Science in Geography / GIS from Texas A&M University and a Master’s in Oceanography from the University of New Hampshire’s Center for Coastal and Ocean Mapping. With a background spanning computer science, oceanography, and geospatial analysis, Jordan is working to advance machine learning for coral reef analysis and applications of computer vision to marine identification. Jordan is currently a Ph.D. student within the Computer Science department at UCSD, working under Falko Kuester of the Cultural Heritage Engineering Initiative (CHEI). Abstract: Coral reefs face global threats, demanding rapid and scalable monitoring solutions. Traditional in-situ survey methods are highly accurate but limited by depth, time, and human labor. In this talk, we will explore the history documenting the transition to in-silico ecology, where computer vision and machine learning automate visual data analysis. By reviewing seminal works, we will track the pivotal shifts from manual pixel annotation to modern deep learning workflows. Furthermore, we will examine how widespread adoption of these technologies has fundamentally altered existing ecological analysis workflows. Despite these advancements, significant bottlenecks remain, particularly regarding model generalization across diverse geographic regions, out-of-sample distributions, a lack of standardized data pipelines, fragmented resource sharing, and overall scalability. Finally, we will discuss emerging future directions and how these innovations may help solve existing problems.

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