Helene Haugerud

Papers

Total Citations

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About

Helene Haugerud is a researcher advancing the frontier of surgical data science, with a primary focus on automated activity recognition and multi-view video analysis in robot-assisted surgery. Her work addresses a critical challenge in modern operating rooms: enabling machines to understand and interpret complex surgical workflows from multiple camera perspectives. Haugerud’s most-cited paper, “Multi-view Surgical Video Action Detection via Mixed Global View Attention” (2021), introduces a novel attention mechanism that fuses information from different camera angles to improve action detection accuracy—a key step toward real-time surgical assistance and post-operative analytics. Her earlier study on automatic operating room activity recognition (2020) laid foundational methods for identifying surgical phases and gestures from robotic system data. Though her citation counts are still growing, Haugerud’s contributions are notable for their technical innovation in handling the spatial and temporal complexity of surgical video, directly supporting efforts to enhance patient safety, training, and workflow efficiency. Her work sits at the intersection of computer vision, deep learning, and clinical robotics, offering promising tools for the next generation of intelligent surgical environments.