Constantinos Loukas

National and Kapodistrian University of Athens

Papers

Total Citations

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About

Constantinos Loukas is a leading researcher in surgical data science and medical robotics, with a primary focus on advancing automated analysis of minimally invasive procedures. His work bridges computer vision and machine learning to enhance surgical skill assessment and intraoperative decision-making. Loukas’s most cited study, "Surgical Gesture Recognition in Laparoscopic Tasks Based on the Transformer Network and Self-Supervised Learning" (2022, 17 citations), introduces a modular deep learning framework that combines 3D convolutional networks with Transformer architectures for video-based gesture recognition. This pioneering approach leverages self-supervision to overcome the scarcity of labeled surgical data, enabling robust encoding of spatial and short-term temporal features from laparoscopic video clips. By automating the identification of surgical gestures, his research directly supports objective skill evaluation and training feedback in robotic-assisted surgery. Loukas’s contributions are particularly impactful in the context of data-efficient learning, where his self-supervised methods reduce reliance on expensive manual annotations. His work has been recognized for its translational potential, influencing the design of next-generation surgical AI systems. With a growing citation footprint, Loukas continues to shape how computational models interpret complex surgical workflows, making him a key figure in the evolution of intelligent operating rooms.